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

5038 lines
1.3 MiB
Raw Blame History

/*
Human library
homepage: <https://github.com/vladmandic/human>
author: <https://github.com/vladmandic>'
*/
var x4=Object.create,ch=Object.defineProperty,w4=Object.getPrototypeOf,_4=Object.prototype.hasOwnProperty,b4=Object.getOwnPropertyNames,v4=Object.getOwnPropertyDescriptor,bf=e=>ch(e,"__esModule",{value:!0}),vf=(e,t)=>()=>(t||(t={exports:{}},e(t.exports,t)),t.exports),Kr=(e,t)=>{for(var n in t)ch(e,n,{get:t[n],enumerable:!0})},k4=(e,t,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of b4(t))!_4.call(e,r)&&r!=="default"&&ch(e,r,{get:()=>t[r],enumerable:!(n=v4(t,r))||n.enumerable});return e},ru=e=>e&&e.__esModule?e:k4(bf(ch(e!=null?x4(w4(e)):{},"default",{value:e,enumerable:!0})),e),T4=vf(e=>{bf(e),Kr(e,{MediaPipeFaceMesh:()=>t,load:()=>r});var t=class{constructor(a,s,i,o){this.facePipeline=new S4(a,s,i,o),this.config=o}async estimateFaces(a,s){let i=await this.facePipeline.predict(a,s),o=[];for(let l of i||[]){if(l.isDisposedInternal)continue;let c=l.coords?l.coords.arraySync():null,u=l.rawCoords,h={};if(c&&c.length>0)for(let f of Object.keys(pa))h[f]=pa[f].map(m=>c[m]);let d=s.face.mesh.returnRawData&&l.box?{topLeft:l.box.startPoint,bottomRight:l.box.endPoint}:null,p=l.box?[Math.max(0,l.box.startPoint[0]),Math.max(0,l.box.startPoint[1]),Math.min(a.shape[2],l.box.endPoint[0])-l.box.startPoint[0],Math.min(a.shape[1],l.box.endPoint[1])-l.box.startPoint[1]]:0;o.push({confidence:l.confidence||0,box:p,mesh:c,boxRaw:d,meshRaw:u,annotations:h,image:l.image?Nr(l.image):null}),l.coords&&l.coords.dispose(),l.image&&l.image.dispose()}return o}},n=[null,null,null];async function r(a){n=await Promise.all([!n[0]&&a.face.enabled?I4(a):null,!n[1]&&a.face.mesh.enabled?Yn(a.face.mesh.modelPath,{fromTFHub:a.face.mesh.modelPath.includes("tfhub.dev")}):null,!n[2]&&a.face.iris.enabled?Yn(a.face.iris.modelPath,{fromTFHub:a.face.iris.modelPath.includes("tfhub.dev")}):null]);let s=new t(n[0],n[1],n[2],a);return a.face.mesh.enabled&&Ue(`load model: ${a.face.mesh.modelPath.match(/\/(.*)\./)[1]}`),a.face.iris.enabled&&Ue(`load model: ${a.face.iris.modelPath.match(/\/(.*)\./)[1]}`),s}e.triangulation=N4}),kf=vf(e=>{bf(e),Kr(e,{NUM_KEYPOINTS:()=>n,connectedPartIndices:()=>s,partChannels:()=>o,partIds:()=>r,partNames:()=>t,poseChain:()=>i});var t=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],n=e.partNames.length,r=e.partNames.reduce((l,c,u)=>(l[c]=u,l),{}),a=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],s=a.map(([l,c])=>[r[l],r[c]]),i=[["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"]],o=["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"]}),E4=vf(e=>{var t=function(r,a,s){let i=function(u,h,d){let p=new RegExp("\\b"+h+" \\w+ (\\w+)","ig");u.replace(p,(f,m)=>(d[m]=0,f))},o=function(u,h){let d=r.createShader(h);if(r.shaderSource(d,u),r.compileShader(d),!r.getShaderParameter(d,r.COMPILE_STATUS))throw new Error("Filter: GL compile failed",r.getShaderInfoLog(d));return d};this.uniform={},this.attribute={};let l=o(a,r.VERTEX_SHADER),c=o(s,r.FRAGMENT_SHADER);if(this.id=r.createProgram(),r.attachShader(this.id,l),r.attachShader(this.id,c),r.linkProgram(this.id),!r.getProgramParameter(this.id,r.LINK_STATUS))throw new Error("Filter: GL link failed",r.getProgramInfoLog(this.id));r.useProgram(this.id),i(a,"attribute",this.attribute);for(let u in this.attribute)this.attribute[u]=r.getAttribLocation(this.id,u);i(a,"uniform",this.uniform),i(s,"uniform",this.uniform);for(let u in this.uniform)this.uniform[u]=r.getUniformLocation(this.id,u)},n=function(r){r||(r={});let a=0,s=null,i=!1,o=-1,l=[null,null],c=[],u=-1,h=-1,d=null,p=null,f=r.canvas||document.createElement("canvas"),m={},A=f.getContext("webgl");if(!A)throw new Error("Filter: getContext() failed");this.addFilter=function(N){let F=Array.prototype.slice.call(arguments,1),$=E[N];c.push({func:$,args:F})},this.reset=function(){c=[]},this.apply=function(N){if(y(N.width,N.height),a=0,s||(s=A.createTexture()),A.bindTexture(A.TEXTURE_2D,s),A.texParameteri(A.TEXTURE_2D,A.TEXTURE_WRAP_S,A.CLAMP_TO_EDGE),A.texParameteri(A.TEXTURE_2D,A.TEXTURE_WRAP_T,A.CLAMP_TO_EDGE),A.texParameteri(A.TEXTURE_2D,A.TEXTURE_MIN_FILTER,A.NEAREST),A.texParameteri(A.TEXTURE_2D,A.TEXTURE_MAG_FILTER,A.NEAREST),A.texImage2D(A.TEXTURE_2D,0,A.RGBA,A.RGBA,A.UNSIGNED_BYTE,N),c.length===0)return x(),f;for(let F=0;F<c.length;F++){i=F===c.length-1;let $=c[F];$.func.apply(this,$.args||[])}return f};let y=function(N,F){if(!(N===u&&F===h)){if(f.width=N,u=N,f.height=F,h=F,!d){let $=new Float32Array([-1,-1,0,1,1,-1,1,1,-1,1,0,0,-1,1,0,0,1,-1,1,1,1,1,1,0]);d=A.createBuffer(),A.bindBuffer(A.ARRAY_BUFFER,d),A.bufferData(A.ARRAY_BUFFER,$,A.STATIC_DRAW),A.pixelStorei(A.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0)}A.viewport(0,0,u,h),l=[null,null]}},g=function(N){return l[N]=l[N]||w(u,h),l[N]},w=function(N,F){let $=A.createFramebuffer();A.bindFramebuffer(A.FRAMEBUFFER,$);let D=A.createRenderbuffer();A.bindRenderbuffer(A.RENDERBUFFER,D);let P=A.createTexture();return A.bindTexture(A.TEXTURE_2D,P),A.texImage2D(A.TEXTURE_2D,0,A.RGBA,N,F,0,A.RGBA,A.UNSIGNED_BYTE,null),A.texParameteri(A.TEXTURE_2D,A.TEXTURE_MAG_FILTER,A.LINEAR),A.texParameteri(A.TEXTURE_2D,A.TEXTURE_MIN_FILTER,A.LINEAR),A.texParameteri(A.TEXTURE_2D,A.TEXTURE_WRAP_S,A.CLAMP_TO_EDGE),A.texParameteri(A.TEXTURE_2D,A.TEXTURE_WRAP_T,A.CLAMP_TO_EDGE),A.framebufferTexture2D(A.FRAMEBUFFER,A.COLOR_ATTACHMENT0,A.TEXTURE_2D,P,0),A.bindTexture(A.TEXTURE_2D,null),A.bindFramebuffer(A.FRAMEBUFFER,null),{fbo:$,texture:P}},x=function(N=null){var F,$;let D=null,P=null,H=!1;a===0?D=s:D=(F=g(o))==null?void 0:F.texture,a++,i&&!(N&I.INTERMEDIATE)?(P=null,H=a%2==0):(o=(o+1)%2,P=($=g(o))==null?void 0:$.fbo),A.bindTexture(A.TEXTURE_2D,D),A.bindFramebuffer(A.FRAMEBUFFER,P),A.uniform1f(p.uniform.flipY,H?-1:1),A.drawArrays(A.TRIANGLES,0,6)},_=function(N){if(m[N])return p=m[N],A.useProgram(p.id),p;p=new t(A,T.VERTEX_IDENTITY,N);let F=Float32Array.BYTES_PER_ELEMENT,$=4*F;return A.enableVertexAttribArray(p.attribute.pos),A.vertexAttribPointer(p.attribute.pos,2,A.FLOAT,!1,$,0*F),A.enableVertexAttribArray(p.attribute.uv),A.vertexAttribPointer(p.attribute.uv,2,A.FLOAT,!1,$,2*F),m[N]=p,p},I={INTERMEDIATE:1},T={};T.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(`
`),T.FRAGMENT_IDENTITY=["precision highp float;","varying vec2 vUv;","uniform sampler2D texture;","void main(void) {","gl_FragColor = texture2D(texture, vUv);","}"].join(`
`);let E={};E.colorMatrix=function(N){let F=new Float32Array(N);F[4]/=255,F[9]/=255,F[14]/=255,F[19]/=255;let $=F[18]===1&&F[3]===0&&F[8]===0&&F[13]===0&&F[15]===0&&F[16]===0&&F[17]===0&&F[19]===0?E.colorMatrix.SHADER.WITHOUT_ALPHA:E.colorMatrix.SHADER.WITH_ALPHA,D=_($);A.uniform1fv(D.uniform.m,F),x()},E.colorMatrix.SHADER={},E.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(`
`),E.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(`
`),E.brightness=function(N){let F=(N||0)+1;E.colorMatrix([F,0,0,0,0,0,F,0,0,0,0,0,F,0,0,0,0,0,1,0])},E.saturation=function(N){let F=(N||0)*2/3+1,$=(F-1)*-.5;E.colorMatrix([F,$,$,0,0,$,F,$,0,0,$,$,F,0,0,0,0,0,1,0])},E.desaturate=function(){E.saturation(-1)},E.contrast=function(N){let F=(N||0)+1,$=-128*(F-1);E.colorMatrix([F,0,0,0,$,0,F,0,0,$,0,0,F,0,$,0,0,0,1,0])},E.negative=function(){E.contrast(-2)},E.hue=function(N){N=(N||0)/180*Math.PI;let F=Math.cos(N),$=Math.sin(N),D=.213,P=.715,H=.072;E.colorMatrix([D+F*(1-D)+$*-D,P+F*-P+$*-P,H+F*-H+$*(1-H),0,0,D+F*-D+$*.143,P+F*(1-P)+$*.14,H+F*-H+$*-.283,0,0,D+F*-D+$*-(1-D),P+F*-P+$*P,H+F*(1-H)+$*H,0,0,0,0,0,1,0])},E.desaturateLuminance=function(){E.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},E.sepia=function(){E.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},E.brownie=function(){E.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},E.vintagePinhole=function(){E.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},E.kodachrome=function(){E.colorMatrix([1.1285582396593525,-.3967382283601348,-.03992559172921793,0,63.72958762196502,-.16404339962244616,1.0835251566291304,-.05498805115633132,0,24.732407896706203,-.16786010706155763,-.5603416277695248,1.6014850761964943,0,35.62982807460946,0,0,0,1,0])},E.technicolor=function(){E.colorMatrix([1.9125277891456083,-.8545344976951645,-.09155508482755585,0,11.793603434377337,-.3087833385928097,1.7658908555458428,-.10601743074722245,0,-70.35205161461398,-.231103377548616,-.7501899197440212,1.847597816108189,0,30.950940869491138,0,0,0,1,0])},E.polaroid=function(){E.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},E.shiftToBGR=function(){E.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},E.convolution=function(N){let F=new Float32Array(N),$=1/u,D=1/h,P=_(E.convolution.SHADER);A.uniform1fv(P.uniform.m,F),A.uniform2f(P.uniform.px,$,D),x()},E.convolution.SHADER=["precision highp float;","varying vec2 vUv;","uniform sampler2D texture;","uniform vec2 px;","uniform float m[9];","void main(void) {","vec4 c11 = texture2D(texture, vUv - px);","vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));","vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));","vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );","vec4 c22 = texture2D(texture, vUv);","vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );","vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );","vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );","vec4 c33 = texture2D(texture, vUv + px );","gl_FragColor = ","c11 * m[0] + c12 * m[1] + c22 * m[2] +","c21 * m[3] + c22 * m[4] + c23 * m[5] +","c31 * m[6] + c32 * m[7] + c33 * m[8];","gl_FragColor.a = c22.a;","}"].join(`
`),E.detectEdges=function(){E.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},E.sobelX=function(){E.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},E.sobelY=function(){E.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},E.sharpen=function(N){let F=N||1;E.convolution.call(this,[0,-1*F,0,-1*F,1+4*F,-1*F,0,-1*F,0])},E.emboss=function(N){let F=N||1;E.convolution.call(this,[-2*F,-1*F,0,-1*F,1,1*F,0,1*F,2*F])},E.blur=function(N){let F=N/7/u,$=N/7/h,D=_(E.blur.SHADER);A.uniform2f(D.uniform.px,0,$),x(I.INTERMEDIATE),A.uniform2f(D.uniform.px,F,0),x()},E.blur.SHADER=["precision highp float;","varying vec2 vUv;","uniform sampler2D texture;","uniform vec2 px;","void main(void) {","gl_FragColor = vec4(0.0);","gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;","gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;","gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;","gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;","gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;","gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;","gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;","gl_FragColor += texture2D(texture, vUv )*0.159576912161;","gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x, 1.0*px.y))*0.147308056121;","gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x, 2.0*px.y))*0.115876621105;","gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x, 3.0*px.y))*0.0776744219933;","gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x, 4.0*px.y))*0.0443683338718;","gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x, 5.0*px.y))*0.0215963866053;","gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x, 6.0*px.y))*0.00895781211794;","gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x, 7.0*px.y))*0.0044299121055113265;","}"].join(`
`),E.pixelate=function(N){let F=N/u,$=N/h,D=_(E.pixelate.SHADER);A.uniform2f(D.uniform.size,F,$),x()},E.pixelate.SHADER=["precision highp float;","varying vec2 vUv;","uniform vec2 size;","uniform sampler2D texture;","vec2 pixelate(vec2 coord, vec2 size) {","return floor( coord / size ) * size;","}","void main(void) {","gl_FragColor = vec4(0.0);","vec2 coord = pixelate(vUv, size);","gl_FragColor += texture2D(texture, coord);","}"].join(`
`)};e.GLImageFilter=n});function Ue(...e){let t=new Date,n=`${t.getHours().toString().padStart(2,"0")}:${t.getMinutes().toString().padStart(2,"0")}:${t.getSeconds().toString().padStart(2,"0")}.${t.getMilliseconds().toString().padStart(3,"0")}`;e&&console.log(n,"Human:",...e)}var M2={};Kr(M2,{Abs:()=>zi,Acos:()=>Pi,Acosh:()=>Li,AdadeltaOptimizer:()=>bd,AdagradOptimizer:()=>vd,AdamOptimizer:()=>kd,AdamaxOptimizer:()=>Id,Add:()=>fa,AddN:()=>Ka,All:()=>dh,Any:()=>ph,ArgMax:()=>Za,ArgMin:()=>su,Asin:()=>Wi,Asinh:()=>Bi,Atan:()=>Vi,Atan2:()=>Hi,Atanh:()=>Ui,AvgPool:()=>Ja,AvgPool3D:()=>iu,AvgPool3DGrad:()=>mh,AvgPoolGrad:()=>fh,BackendWasm:()=>N0,BatchMatMul:()=>Ya,BatchToSpaceND:()=>ou,Bincount:()=>Ah,BroadcastTo:()=>D2,Callback:()=>W0,CallbackList:()=>M0,Cast:()=>Qa,Ceil:()=>ji,ClipByValue:()=>ma,Complex:()=>yh,ComplexAbs:()=>lu,Concat:()=>Gi,Conv2D:()=>es,Conv2DBackpropFilter:()=>gh,Conv2DBackpropInput:()=>ts,Conv3D:()=>uu,Conv3DBackpropFilterV2:()=>xh,Conv3DBackpropInputV2:()=>wh,Cos:()=>ns,Cosh:()=>qi,CropAndResize:()=>Xi,Cumsum:()=>rs,CustomCallback:()=>D0,DataStorage:()=>hh,DenseBincount:()=>_h,DepthToSpace:()=>Ki,DepthwiseConv2dNative:()=>as,DepthwiseConv2dNativeBackpropFilter:()=>bh,DepthwiseConv2dNativeBackpropInput:()=>vh,Diag:()=>kh,Dilation2D:()=>cu,Dilation2DBackpropFilter:()=>Nh,Dilation2DBackpropInput:()=>Ih,ENV:()=>bn,EarlyStopping:()=>B0,Elu:()=>Zi,EluGrad:()=>Sh,Environment:()=>$2,Equal:()=>Yi,Erf:()=>Ji,Exp:()=>is,ExpandDims:()=>Qi,Expm1:()=>eo,FFT:()=>Th,Fill:()=>hu,FlipLeftRight:()=>to,Floor:()=>os,FloorDiv:()=>ls,FromPixels:()=>Vh,FusedBatchNorm:()=>us,FusedConv2D:()=>Ws,FusedDepthwiseConv2D:()=>Bs,GPGPUContext:()=>fm,GatherNd:()=>ro,GatherV2:()=>no,GraphModel:()=>V0,Greater:()=>ao,GreaterEqual:()=>cs,History:()=>$0,IFFT:()=>Eh,Identity:()=>so,Imag:()=>Ch,InputSpec:()=>Vt,IsFinite:()=>io,IsInf:()=>oo,IsNan:()=>lo,KernelBackend:()=>au,LRN:()=>fu,LRNGrad:()=>Fh,LayerVariable:()=>F0,LayersModel:()=>ea,LeakyRelu:()=>hs,Less:()=>uo,LessEqual:()=>co,LinSpace:()=>Rh,Log:()=>ds,Log1p:()=>ho,LogSoftmax:()=>O2,LogicalAnd:()=>po,LogicalNot:()=>du,LogicalOr:()=>pu,MathBackendCPU:()=>w0,MathBackendWebGL:()=>mm,Max:()=>ps,MaxPool:()=>ms,MaxPool3D:()=>mu,MaxPool3DGrad:()=>$h,MaxPoolGrad:()=>Mh,MaxPoolWithArgmax:()=>Dh,Maximum:()=>fs,Mean:()=>As,Min:()=>ys,Minimum:()=>gs,MirrorPad:()=>Au,Mod:()=>fo,MomentumOptimizer:()=>Nd,Multinomial:()=>Oh,Multiply:()=>xs,Neg:()=>mo,NonMaxSuppressionV3:()=>yo,NonMaxSuppressionV4:()=>go,NonMaxSuppressionV5:()=>xo,NotEqual:()=>Ao,OP_SCOPE_SUFFIX:()=>P2,OneHot:()=>ws,OnesLike:()=>wo,Optimizer:()=>Qr,Pack:()=>_o,PadV2:()=>_s,Pool:()=>C4,Pow:()=>bs,Prelu:()=>vs,Prod:()=>bo,RMSPropOptimizer:()=>Sd,RNN:()=>Fr,Range:()=>yu,Rank:()=>Nf,Real:()=>zh,RealDiv:()=>ss,Reciprocal:()=>vo,Reduction:()=>sn,Relu:()=>ks,Relu6:()=>Ns,Reshape:()=>ko,ResizeBilinear:()=>Is,ResizeBilinearGrad:()=>Lh,ResizeNearestNeighbor:()=>gu,ResizeNearestNeighborGrad:()=>Ph,Reverse:()=>Ss,RotateWithOffset:()=>Po,Round:()=>Ts,Rsqrt:()=>Es,SGDOptimizer:()=>Uu,ScatterNd:()=>Io,Select:()=>No,Selu:()=>So,Sequential:()=>Yo,Sigmoid:()=>Rs,Sign:()=>Co,Sin:()=>Cs,Sinh:()=>Eo,Slice:()=>To,Softmax:()=>$s,Softplus:()=>Ro,SpaceToBatchND:()=>xu,SparseToDense:()=>Wh,SplitV:()=>Fo,Sqrt:()=>Fs,Square:()=>wu,SquaredDifference:()=>Ds,Step:()=>ya,StridedSlice:()=>Mo,Sub:()=>Os,Sum:()=>Ms,SymbolicTensor:()=>mr,Tan:()=>$o,Tanh:()=>zs,Tensor:()=>Qe,TensorBuffer:()=>Mt,Tile:()=>Aa,TopK:()=>Do,Transpose:()=>Ps,Unique:()=>Bh,Unpack:()=>Oo,UnsortedSegmentSum:()=>_u,Variable:()=>vu,ZerosLike:()=>zo,_FusedMatMul:()=>Ls,abs:()=>$t,acos:()=>Ff,acosh:()=>Mf,add:()=>oe,addN:()=>Kh,all:()=>Zh,any:()=>Nu,argMax:()=>Su,argMin:()=>$f,asin:()=>Df,asinh:()=>Of,atan:()=>zf,atan2:()=>Pf,atanh:()=>Lf,avgPool:()=>Tu,avgPool3d:()=>Wf,backend:()=>Rf,backend_util:()=>C,basicLSTMCell:()=>B4,batchNorm:()=>Vs,batchNorm2d:()=>q2,batchNorm3d:()=>X2,batchNorm4d:()=>K2,batchToSpaceND:()=>Eu,bincount:()=>Z2,booleanMaskAsync:()=>u8,broadcastTo:()=>Cu,browser:()=>ku,buffer:()=>We,callbacks:()=>_8,cast:()=>ye,ceil:()=>Bf,clipByValue:()=>pn,clone:()=>Nr,complex:()=>ga,concat:()=>ct,concat1d:()=>J2,concat2d:()=>Jh,concat3d:()=>Y2,concat4d:()=>Q2,constraints:()=>E0,conv1d:()=>Yh,conv2d:()=>Zr,conv2dTranspose:()=>Qh,conv3d:()=>Vf,conv3dTranspose:()=>V4,copyRegisteredKernels:()=>M4,cos:()=>Ru,cosh:()=>ed,cosineWindow:()=>hm,cumsum:()=>td,customGrad:()=>Sr,data:()=>U0,denseBincount:()=>e0,deprecationWarn:()=>Cf,depthToSpace:()=>Uf,depthwiseConv2d:()=>Uo,deregisterOp:()=>v8,device_util:()=>jh,diag:()=>U4,dilation2d:()=>Hf,disableDeprecationWarnings:()=>D4,dispose:()=>Ce,disposeVariables:()=>O4,div:()=>Ne,divNoNan:()=>jf,dot:()=>t0,dropout:()=>y0,elu:()=>Ho,enableDebugMode:()=>$4,enableProdMode:()=>U2,enclosingPowerOfTwo:()=>g0,engine:()=>Ln,env:()=>Q,equal:()=>xa,erf:()=>Gf,exp:()=>Wn,expandDims:()=>vn,expm1:()=>qf,eye:()=>Xf,fft:()=>Bu,fill:()=>Fu,findBackend:()=>G2,findBackendFactory:()=>L4,floor:()=>jo,floorDiv:()=>Xh,forceHalfFloat:()=>I0,fused:()=>va,gather:()=>Us,gatherND:()=>A0,gather_util:()=>Tf,getBackend:()=>qh,getGradient:()=>If,getKernel:()=>Uh,getKernelsForBackend:()=>bu,gpgpu_util:()=>v0,grad:()=>H4,grads:()=>j4,greater:()=>tr,greaterEqual:()=>_a,ifft:()=>Zo,imag:()=>nd,image:()=>St,inTopKAsync:()=>h8,initializers:()=>C0,input:()=>O0,io:()=>dn,irfft:()=>yd,isFinite:()=>n0,isInf:()=>r0,isNaN:()=>a0,keep:()=>Bt,kernel_impls:()=>Rr,layers:()=>R0,leakyRelu:()=>Mu,less:()=>rd,lessEqual:()=>Hs,linalg:()=>x0,linspace:()=>s0,loadGraphModel:()=>Yn,loadLayersModel:()=>x8,localResponseNormalization:()=>Kf,log:()=>kn,log1p:()=>ad,logSigmoid:()=>o0,logSoftmax:()=>sd,logSumExp:()=>Zf,logicalAnd:()=>nr,logicalNot:()=>$u,logicalOr:()=>id,logicalXor:()=>l0,losses:()=>f8,matMul:()=>qe,math:()=>W2,max:()=>Bn,maxPool:()=>Du,maxPool3d:()=>Jf,maxPoolWithArgmax:()=>u0,maximum:()=>Tr,mean:()=>bt,memory:()=>Gh,metrics:()=>z0,min:()=>qo,minimum:()=>Xo,mirrorPad:()=>Yf,mod:()=>Qf,model:()=>y8,models:()=>P0,moments:()=>od,movingAverage:()=>c8,mul:()=>W,multiRNNCell:()=>X4,multinomial:()=>c0,neg:()=>_t,nextFrame:()=>Td,norm:()=>_d,notEqual:()=>js,oneHot:()=>Wo,ones:()=>Er,onesLike:()=>In,op:()=>L,outerProduct:()=>K4,pad:()=>Jr,pad1d:()=>Z4,pad2d:()=>J4,pad3d:()=>Y4,pad4d:()=>Q4,pool:()=>h0,pow:()=>Yr,prelu:()=>zu,print:()=>L2,prod:()=>ld,profile:()=>Bo,rand:()=>e8,randomGamma:()=>t8,randomNormal:()=>d0,randomUniform:()=>Ko,range:()=>ud,ready:()=>j2,real:()=>Pu,reciprocal:()=>em,registerBackend:()=>Iu,registerCallbackConstructor:()=>w8,registerGradient:()=>z2,registerKernel:()=>Lo,registerOp:()=>b8,regularizers:()=>L0,relu:()=>Cr,relu6:()=>cd,removeBackend:()=>P4,reshape:()=>q,reverse:()=>Nn,reverse1d:()=>n8,reverse2d:()=>r8,reverse3d:()=>a8,reverse4d:()=>s8,rfft:()=>Vu,round:()=>tm,rsqrt:()=>hd,scalar:()=>Se,scatterND:()=>m0,scatter_util:()=>Ef,selu:()=>dd,separableConv2d:()=>nm,sequential:()=>g8,serialization:()=>re,setBackend:()=>H2,setPlatform:()=>W4,setWasmPath:()=>A8,setWasmPaths:()=>S0,setWebGLContext:()=>pm,setdiff1dAsync:()=>p0,shared:()=>dm,sigmoid:()=>er,sign:()=>rm,signal:()=>p8,sin:()=>pd,sinh:()=>fd,slice:()=>Me,slice1d:()=>md,slice2d:()=>am,slice3d:()=>Ad,slice4d:()=>Lu,slice_util:()=>rn,softmax:()=>Wu,softplus:()=>Go,spaceToBatchND:()=>Ou,sparseToDense:()=>cm,spectral:()=>d8,split:()=>an,sqrt:()=>Xt,square:()=>ot,squaredDifference:()=>gd,squeeze:()=>ba,stack:()=>Sn,step:()=>Jo,stridedSlice:()=>sm,sub:()=>we,sum:()=>Te,sumOutType:()=>Hh,tan:()=>im,tanh:()=>Vo,tensor:()=>pr,tensor1d:()=>Qt,tensor2d:()=>fr,tensor3d:()=>Sf,tensor4d:()=>i8,tensor5d:()=>o8,tensor6d:()=>l8,tensor_util:()=>dr,test_util:()=>B2,tidy:()=>U,tile:()=>wa,time:()=>z4,topk:()=>om,train:()=>Gs,transpose:()=>at,truncatedNormal:()=>xd,unique:()=>wd,unregisterGradient:()=>F4,unregisterKernel:()=>R4,unsortedSegmentSum:()=>lm,unstack:()=>rr,upcastType:()=>Qn,util:()=>v,valueAndGrad:()=>G4,valueAndGrads:()=>q4,variable:()=>f0,variableGrads:()=>i0,version:()=>I8,version_converter:()=>k8,version_core:()=>V2,version_cpu:()=>_0,version_layers:()=>Am,version_wasm:()=>T0,version_webgl:()=>k0,webgl:()=>m8,webgl_util:()=>b0,where:()=>fn,whereAsync:()=>um,zeros:()=>Ct,zerosLike:()=>He});var N8=Object.create,Ed=Object.defineProperty,S8=Object.getPrototypeOf,T8=Object.prototype.hasOwnProperty,E8=Object.getOwnPropertyNames,C8=Object.getOwnPropertyDescriptor,R8=e=>Ed(e,"__esModule",{value:!0}),nt=(e,t)=>()=>(t||(t={exports:{}},e(t.exports,t)),t.exports),ze=(e,t)=>{for(var n in t)Ed(e,n,{get:t[n],enumerable:!0})},F8=(e,t,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of E8(t))!T8.call(e,r)&&r!=="default"&&Ed(e,r,{get:()=>t[r],enumerable:!(n=C8(t,r))||n.enumerable});return e},Qo=e=>e&&e.__esModule?e:F8(R8(Ed(e!=null?N8(S8(e)):{},"default",{value:e,enumerable:!0})),e),M8=nt(()=>{}),$8=nt((e,t)=>{(function(n,r,a){function s(c){var u=this,h=l();u.next=function(){var d=2091639*u.s0+u.c*23283064365386963e-26;return u.s0=u.s1,u.s1=u.s2,u.s2=d-(u.c=d|0)},u.c=1,u.s0=h(" "),u.s1=h(" "),u.s2=h(" "),u.s0-=h(c),u.s0<0&&(u.s0+=1),u.s1-=h(c),u.s1<0&&(u.s1+=1),u.s2-=h(c),u.s2<0&&(u.s2+=1),h=null}function i(c,u){return u.c=c.c,u.s0=c.s0,u.s1=c.s1,u.s2=c.s2,u}function o(c,u){var h=new s(c),d=u&&u.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 c=4022871197,u=function(h){h=h.toString();for(var d=0;d<h.length;d++){c+=h.charCodeAt(d);var p=.02519603282416938*c;c=p>>>0,p-=c,p*=c,c=p>>>0,p-=c,c+=p*4294967296}return(c>>>0)*23283064365386963e-26};return u}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)}),D8=nt((e,t)=>{(function(n,r,a){function s(l){var c=this,u="";c.x=0,c.y=0,c.z=0,c.w=0,c.next=function(){var d=c.x^c.x<<11;return c.x=c.y,c.y=c.z,c.z=c.w,c.w^=c.w>>>19^d^d>>>8},l===(l|0)?c.x=l:u+=l;for(var h=0;h<u.length+64;h++)c.x^=u.charCodeAt(h)|0,c.next()}function i(l,c){return c.x=l.x,c.y=l.y,c.z=l.z,c.w=l.w,c}function o(l,c){var u=new s(l),h=c&&c.state,d=function(){return(u.next()>>>0)/4294967296};return d.double=function(){do var p=u.next()>>>11,f=(u.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=u.next,d.quick=d,h&&(typeof h=="object"&&i(h,u),d.state=function(){return i(u,{})}),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)}),O8=nt((e,t)=>{(function(n,r,a){function s(l){var c=this,u="";c.next=function(){var d=c.x^c.x>>>2;return c.x=c.y,c.y=c.z,c.z=c.w,c.w=c.v,(c.d=c.d+362437|0)+(c.v=c.v^c.v<<4^(d^d<<1))|0},c.x=0,c.y=0,c.z=0,c.w=0,c.v=0,l===(l|0)?c.x=l:u+=l;for(var h=0;h<u.length+64;h++)c.x^=u.charCodeAt(h)|0,h==u.length&&(c.d=c.x<<10^c.x>>>4),c.next()}function i(l,c){return c.x=l.x,c.y=l.y,c.z=l.z,c.w=l.w,c.v=l.v,c.d=l.d,c}function o(l,c){var u=new s(l),h=c&&c.state,d=function(){return(u.next()>>>0)/4294967296};return d.double=function(){do var p=u.next()>>>11,f=(u.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=u.next,d.quick=d,h&&(typeof h=="object"&&i(h,u),d.state=function(){return i(u,{})}),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)}),z8=nt((e,t)=>{(function(n,r,a){function s(l){var c=this;c.next=function(){var h=c.x,d=c.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,c.i=d+1&7,f};function u(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()}u(c,l)}function i(l,c){return c.x=l.x.slice(),c.i=l.i,c}function o(l,c){l==null&&(l=+new Date);var u=new s(l),h=c&&c.state,d=function(){return(u.next()>>>0)/4294967296};return d.double=function(){do var p=u.next()>>>11,f=(u.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=u.next,d.quick=d,h&&(h.x&&i(h,u),d.state=function(){return i(u,{})}),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)}),P8=nt((e,t)=>{(function(n,r,a){function s(l){var c=this;c.next=function(){var h=c.w,d=c.X,p=c.i,f,m;return c.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,c.i=p,m+(h^h>>>16)|0};function u(h,d){var p,f,m,A,y,g=[],w=128;for(d===(d|0)?(f=d,d=null):(d=d+"\0",f=0,w=Math.max(w,d.length)),m=0,A=-32;A<w;++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}u(c,l)}function i(l,c){return c.i=l.i,c.w=l.w,c.X=l.X.slice(),c}function o(l,c){l==null&&(l=+new Date);var u=new s(l),h=c&&c.state,d=function(){return(u.next()>>>0)/4294967296};return d.double=function(){do var p=u.next()>>>11,f=(u.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=u.next,d.quick=d,h&&(h.X&&i(h,u),d.state=function(){return i(u,{})}),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)}),L8=nt((e,t)=>{(function(n,r,a){function s(l){var c=this,u="";c.next=function(){var d=c.b,p=c.c,f=c.d,m=c.a;return d=d<<25^d>>>7^p,p=p-f|0,f=f<<24^f>>>8^m,m=m-d|0,c.b=d=d<<20^d>>>12^p,c.c=p=p-f|0,c.d=f<<16^p>>>16^m,c.a=m-d|0},c.a=0,c.b=0,c.c=2654435769|0,c.d=1367130551,l===Math.floor(l)?(c.a=l/4294967296|0,c.b=l|0):u+=l;for(var h=0;h<u.length+20;h++)c.b^=u.charCodeAt(h)|0,c.next()}function i(l,c){return c.a=l.a,c.b=l.b,c.c=l.c,c.d=l.d,c}function o(l,c){var u=new s(l),h=c&&c.state,d=function(){return(u.next()>>>0)/4294967296};return d.double=function(){do var p=u.next()>>>11,f=(u.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=u.next,d.quick=d,h&&(typeof h=="object"&&i(h,u),d.state=function(){return i(u,{})}),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)}),ym=nt(()=>{}),W8=nt((e,t)=>{(function(n,r){var a=this,s=256,i=6,o=52,l="random",c=r.pow(s,i),u=r.pow(2,o),h=u*2,d=s-1,p;function f(_,I,T){var E=[];I=I==!0?{entropy:!0}:I||{};var N=g(y(I.entropy?[_,x(n)]:_==null?w():_,3),E),F=new m(E),$=function(){for(var D=F.g(i),P=c,H=0;D<u;)D=(D+H)*s,P*=s,H=F.g(1);for(;D>=h;)D/=2,P/=2,H>>>=1;return(D+H)/P};return $.int32=function(){return F.g(4)|0},$.quick=function(){return F.g(4)/4294967296},$.double=$,g(x(F.S),n),(I.pass||T||function(D,P,H,V){return V&&(V.S&&A(V,F),D.state=function(){return A(F,{})}),H?(r[l]=D,P):D})($,N,"global"in I?I.global:this==r,I.state)}r["seed"+l]=f;function m(_){var I,T=_.length,E=this,N=0,F=E.i=E.j=0,$=E.S=[];for(T||(_=[T++]);N<s;)$[N]=N++;for(N=0;N<s;N++)$[N]=$[F=d&F+_[N%T]+(I=$[N])],$[F]=I;(E.g=function(D){for(var P,H=0,V=E.i,K=E.j,X=E.S;D--;)P=X[V=d&V+1],H=H*s+X[d&(X[V]=X[K=d&K+P])+(X[K]=P)];return E.i=V,E.j=K,H})(s)}function A(_,I){return I.i=_.i,I.j=_.j,I.S=_.S.slice(),I}function y(_,I){var T=[],E=typeof _,N;if(I&&E=="object")for(N in _)try{T.push(y(_[N],I-1))}catch(F){}return T.length?T:E=="string"?_:_+"\0"}function g(_,I){for(var T=_+"",E,N=0;N<T.length;)I[d&N]=d&(E^=I[d&N]*19)+T.charCodeAt(N++);return x(I)}function w(){try{var _;return p&&(_=p.randomBytes)?_=_(s):(_=new Uint8Array(s),(a.crypto||a.msCrypto).getRandomValues(_)),x(_)}catch(E){var I=a.navigator,T=I&&I.plugins;return[+new Date,a,T,a.screen,x(n)]}}function x(_){return String.fromCharCode.apply(0,_)}if(g(r.random(),n),typeof t=="object"&&t.exports){t.exports=f;try{p=ym()}catch(_){}}else typeof define=="function"&&define.amd&&define(function(){return f})})([],Math)}),B8=nt((e,t)=>{var n=$8(),r=D8(),a=O8(),s=z8(),i=P8(),o=L8(),l=W8();l.alea=n,l.xor128=r,l.xorwow=a,l.xorshift7=s,l.xor4096=i,l.tychei=o,t.exports=l}),V8=nt((e,t)=>{(function(n,r,a){function s(c){var u=this,h=l();u.next=function(){var d=2091639*u.s0+u.c*23283064365386963e-26;return u.s0=u.s1,u.s1=u.s2,u.s2=d-(u.c=d|0)},u.c=1,u.s0=h(" "),u.s1=h(" "),u.s2=h(" "),u.s0-=h(c),u.s0<0&&(u.s0+=1),u.s1-=h(c),u.s1<0&&(u.s1+=1),u.s2-=h(c),u.s2<0&&(u.s2+=1),h=null}function i(c,u){return u.c=c.c,u.s0=c.s0,u.s1=c.s1,u.s2=c.s2,u}function o(c,u){var h=new s(c),d=u&&u.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 c=4022871197,u=function(h){h=h.toString();for(var d=0;d<h.length;d++){c+=h.charCodeAt(d);var p=.02519603282416938*c;c=p>>>0,p-=c,p*=c,c=p>>>0,p-=c,c+=p*4294967296}return(c>>>0)*23283064365386963e-26};return u}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)}),U8=nt((e,t)=>{(function(n,r,a){function s(l){var c=this,u="";c.x=0,c.y=0,c.z=0,c.w=0,c.next=function(){var d=c.x^c.x<<11;return c.x=c.y,c.y=c.z,c.z=c.w,c.w^=c.w>>>19^d^d>>>8},l===(l|0)?c.x=l:u+=l;for(var h=0;h<u.length+64;h++)c.x^=u.charCodeAt(h)|0,c.next()}function i(l,c){return c.x=l.x,c.y=l.y,c.z=l.z,c.w=l.w,c}function o(l,c){var u=new s(l),h=c&&c.state,d=function(){return(u.next()>>>0)/4294967296};return d.double=function(){do var p=u.next()>>>11,f=(u.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=u.next,d.quick=d,h&&(typeof h=="object"&&i(h,u),d.state=function(){return i(u,{})}),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)}),H8=nt((e,t)=>{(function(n,r,a){function s(l){var c=this,u="";c.next=function(){var d=c.x^c.x>>>2;return c.x=c.y,c.y=c.z,c.z=c.w,c.w=c.v,(c.d=c.d+362437|0)+(c.v=c.v^c.v<<4^(d^d<<1))|0},c.x=0,c.y=0,c.z=0,c.w=0,c.v=0,l===(l|0)?c.x=l:u+=l;for(var h=0;h<u.length+64;h++)c.x^=u.charCodeAt(h)|0,h==u.length&&(c.d=c.x<<10^c.x>>>4),c.next()}function i(l,c){return c.x=l.x,c.y=l.y,c.z=l.z,c.w=l.w,c.v=l.v,c.d=l.d,c}function o(l,c){var u=new s(l),h=c&&c.state,d=function(){return(u.next()>>>0)/4294967296};return d.double=function(){do var p=u.next()>>>11,f=(u.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=u.next,d.quick=d,h&&(typeof h=="object"&&i(h,u),d.state=function(){return i(u,{})}),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)}),j8=nt((e,t)=>{(function(n,r,a){function s(l){var c=this;c.next=function(){var h=c.x,d=c.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,c.i=d+1&7,f};function u(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()}u(c,l)}function i(l,c){return c.x=l.x.slice(),c.i=l.i,c}function o(l,c){l==null&&(l=+new Date);var u=new s(l),h=c&&c.state,d=function(){return(u.next()>>>0)/4294967296};return d.double=function(){do var p=u.next()>>>11,f=(u.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=u.next,d.quick=d,h&&(h.x&&i(h,u),d.state=function(){return i(u,{})}),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)}),G8=nt((e,t)=>{(function(n,r,a){function s(l){var c=this;c.next=function(){var h=c.w,d=c.X,p=c.i,f,m;return c.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,c.i=p,m+(h^h>>>16)|0};function u(h,d){var p,f,m,A,y,g=[],w=128;for(d===(d|0)?(f=d,d=null):(d=d+"\0",f=0,w=Math.max(w,d.length)),m=0,A=-32;A<w;++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}u(c,l)}function i(l,c){return c.i=l.i,c.w=l.w,c.X=l.X.slice(),c}function o(l,c){l==null&&(l=+new Date);var u=new s(l),h=c&&c.state,d=function(){return(u.next()>>>0)/4294967296};return d.double=function(){do var p=u.next()>>>11,f=(u.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=u.next,d.quick=d,h&&(h.X&&i(h,u),d.state=function(){return i(u,{})}),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)}),q8=nt((e,t)=>{(function(n,r,a){function s(l){var c=this,u="";c.next=function(){var d=c.b,p=c.c,f=c.d,m=c.a;return d=d<<25^d>>>7^p,p=p-f|0,f=f<<24^f>>>8^m,m=m-d|0,c.b=d=d<<20^d>>>12^p,c.c=p=p-f|0,c.d=f<<16^p>>>16^m,c.a=m-d|0},c.a=0,c.b=0,c.c=2654435769|0,c.d=1367130551,l===Math.floor(l)?(c.a=l/4294967296|0,c.b=l|0):u+=l;for(var h=0;h<u.length+20;h++)c.b^=u.charCodeAt(h)|0,c.next()}function i(l,c){return c.a=l.a,c.b=l.b,c.c=l.c,c.d=l.d,c}function o(l,c){var u=new s(l),h=c&&c.state,d=function(){return(u.next()>>>0)/4294967296};return d.double=function(){do var p=u.next()>>>11,f=(u.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=u.next,d.quick=d,h&&(typeof h=="object"&&i(h,u),d.state=function(){return i(u,{})}),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)}),X8=nt((e,t)=>{(function(n,r){var a=this,s=256,i=6,o=52,l="random",c=r.pow(s,i),u=r.pow(2,o),h=u*2,d=s-1,p;function f(_,I,T){var E=[];I=I==!0?{entropy:!0}:I||{};var N=g(y(I.entropy?[_,x(n)]:_==null?w():_,3),E),F=new m(E),$=function(){for(var D=F.g(i),P=c,H=0;D<u;)D=(D+H)*s,P*=s,H=F.g(1);for(;D>=h;)D/=2,P/=2,H>>>=1;return(D+H)/P};return $.int32=function(){return F.g(4)|0},$.quick=function(){return F.g(4)/4294967296},$.double=$,g(x(F.S),n),(I.pass||T||function(D,P,H,V){return V&&(V.S&&A(V,F),D.state=function(){return A(F,{})}),H?(r[l]=D,P):D})($,N,"global"in I?I.global:this==r,I.state)}r["seed"+l]=f;function m(_){var I,T=_.length,E=this,N=0,F=E.i=E.j=0,$=E.S=[];for(T||(_=[T++]);N<s;)$[N]=N++;for(N=0;N<s;N++)$[N]=$[F=d&F+_[N%T]+(I=$[N])],$[F]=I;(E.g=function(D){for(var P,H=0,V=E.i,K=E.j,X=E.S;D--;)P=X[V=d&V+1],H=H*s+X[d&(X[V]=X[K=d&K+P])+(X[K]=P)];return E.i=V,E.j=K,H})(s)}function A(_,I){return I.i=_.i,I.j=_.j,I.S=_.S.slice(),I}function y(_,I){var T=[],E=typeof _,N;if(I&&E=="object")for(N in _)try{T.push(y(_[N],I-1))}catch(F){}return T.length?T:E=="string"?_:_+"\0"}function g(_,I){for(var T=_+"",E,N=0;N<T.length;)I[d&N]=d&(E^=I[d&N]*19)+T.charCodeAt(N++);return x(I)}function w(){try{var _;return p&&(_=p.randomBytes)?_=_(s):(_=new Uint8Array(s),(a.crypto||a.msCrypto).getRandomValues(_)),x(_)}catch(E){var I=a.navigator,T=I&&I.plugins;return[+new Date,a,T,a.screen,x(n)]}}function x(_){return String.fromCharCode.apply(0,_)}if(g(r.random(),n),typeof t=="object"&&t.exports){t.exports=f;try{p=ym()}catch(_){}}else typeof define=="function"&&define.amd&&define(function(){return f})})([],Math)}),K8=nt((e,t)=>{var n=V8(),r=U8(),a=H8(),s=j8(),i=G8(),o=q8(),l=X8();l.alea=n,l.xor128=r,l.xorwow=a,l.xorshift7=s,l.xor4096=i,l.tychei=o,t.exports=l}),Hu=nt(()=>{}),Z8=nt(()=>{}),J8=nt(()=>{}),Y8=nt((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 Y.buffer!=Ye&&_n(Y.buffer),xn}function i(){return Y.buffer!=Ye&&_n(Y.buffer),qt}function o(){return Y.buffer!=Ye&&_n(Y.buffer),hn}function l(){return Y.buffer!=Ye&&_n(Y.buffer),nn}function c(){return Y.buffer!=Ye&&_n(Y.buffer),kr}var u=typeof a!="undefined"?a:{},h={},d;for(d in u)u.hasOwnProperty(d)&&(h[d]=u[d]);var p=[],f="./this.program",m=function(b,S){throw S},A=!1,y=!1,g=!1,w=!1;A=typeof window=="object",y=typeof importScripts=="function",g=typeof process=="object"&&typeof process.versions=="object"&&typeof process.versions.node=="string",w=!A&&!g&&!y;var x=u.ENVIRONMENT_IS_PTHREAD||!1;x&&(Ye=u.buffer,Kn=u.DYNAMIC_BASE,hr=u.DYNAMICTOP_PTR);var _="";function I(b){return u.locateFile?u.locateFile(b,_):_+b}var T,E,N,F,$,D;if(g){y?_=Hu().dirname(_)+"/":_=__dirname+"/",T=function(b,S){return $||($=require("fs")),D||(D=Hu()),b=D.normalize(b),$.readFileSync(b,S?null:"utf8")},N=function(b){var S=T(b,!0);return S.buffer||(S=new Uint8Array(S)),ke(S.buffer),S},process.argv.length>1&&(f=process.argv[1].replace(/\\/g,"/")),p=process.argv.slice(2),process.on("uncaughtException",function(b){if(!(b instanceof R2))throw b}),process.on("unhandledRejection",Gr),m=function(b){process.exit(b)},u.inspect=function(){return"[Emscripten Module object]"};var P;try{P=Z8()}catch(b){throw console.error('The "worker_threads" module is not supported in this node.js build - perhaps a newer version is needed?'),b}Worker=P.Worker}else w?(typeof read!="undefined"&&(T=function(b){return read(b)}),N=function(b){var S;return typeof readbuffer=="function"?new Uint8Array(readbuffer(b)):(S=read(b,"binary"),ke(typeof S=="object"),S)},typeof scriptArgs!="undefined"?p=scriptArgs:typeof arguments!="undefined"&&(p=arguments),typeof quit=="function"&&(m=function(b){quit(b)}),typeof print!="undefined"&&(typeof console=="undefined"&&(console={}),console.log=print,console.warn=console.error=typeof printErr!="undefined"?printErr:print)):(A||y)&&(y?_=self.location.href:document.currentScript&&(_=document.currentScript.src),typeof r!="undefined"&&r&&(_=r),_.indexOf("blob:")!==0?_=_.substr(0,_.lastIndexOf("/")+1):_="",g?(T=function(b,S){return $||($=require("fs")),D||(D=Hu()),b=D.normalize(b),$.readFileSync(b,S?null:"utf8")},N=function(b){var S=T(b,!0);return S.buffer||(S=new Uint8Array(S)),ke(S.buffer),S}):(T=function(b){var S=new XMLHttpRequest;return S.open("GET",b,!1),S.send(null),S.responseText},y&&(N=function(b){var S=new XMLHttpRequest;return S.open("GET",b,!1),S.responseType="arraybuffer",S.send(null),new Uint8Array(S.response)}),E=function(b,S,O){var G=new XMLHttpRequest;G.open("GET",b,!0),G.responseType="arraybuffer",G.onload=function(){if(G.status==200||G.status==0&&G.response){S(G.response);return}O()},G.onerror=O,G.send(null)}),F=function(b){document.title=b});g&&typeof performance=="undefined"&&(performance=J8().performance);var H=u.print||console.log.bind(console),V=u.printErr||console.warn.bind(console);for(d in h)h.hasOwnProperty(d)&&(u[d]=h[d]);h=null,u.arguments&&(p=u.arguments),u.thisProgram&&(f=u.thisProgram),u.quit&&(m=u.quit);var K=Atomics.load,X=Atomics.store,ee=Atomics.compareExchange,J;u.wasmBinary&&(J=u.wasmBinary);var ae;u.noExitRuntime&&(ae=u.noExitRuntime),typeof WebAssembly!="object"&&V("no native wasm support detected");var Y,ue=new WebAssembly.Table({initial:169,maximum:169+0,element:"anyfunc"}),ne,de=0,he=0,me=!1,Ae=0;function ke(b,S){b||Gr("Assertion failed: "+S)}function Ee(b){var S=u["_"+b];return ke(S,"Cannot call unknown function "+b+", make sure it is exported"),S}function Re(b,S,O,G,pe){var ce={string:function(Pn){var da=0;if(Pn!=null&&Pn!==0){var nu=(Pn.length<<2)+1;da=Mi(nu),it(Pn,da,nu)}return da},array:function(Pn){var da=Mi(Pn.length);return lt(Pn,da),da}};function le(Pn){return S==="string"?Ve(Pn):S==="boolean"?Boolean(Pn):Pn}var be=Ee(b),et=[],Ft=0;if(G)for(var Yt=0;Yt<G.length;Yt++){var Di=ce[O[Yt]];Di?(Ft===0&&(Ft=Ql()),et[Yt]=Di(G[Yt])):et[Yt]=G[Yt]}var tu=be.apply(null,et);return tu=le(tu),Ft!==0&&$i(Ft),tu}function Oe(b,S,O,G){O=O||[];var pe=O.every(function(le){return le==="number"}),ce=S!=="string";return ce&&pe&&!G?Ee(b):function(){return Re(b,S,O,arguments,G)}}function Ke(b,S,O){for(var G=S+O,pe="";!(S>=G);){var ce=b[S++];if(!ce)return pe;if(!(ce&128)){pe+=String.fromCharCode(ce);continue}var le=b[S++]&63;if((ce&224)==192){pe+=String.fromCharCode((ce&31)<<6|le);continue}var be=b[S++]&63;if((ce&240)==224?ce=(ce&15)<<12|le<<6|be:ce=(ce&7)<<18|le<<12|be<<6|b[S++]&63,ce<65536)pe+=String.fromCharCode(ce);else{var et=ce-65536;pe+=String.fromCharCode(55296|et>>10,56320|et&1023)}}return pe}function Ve(b,S){return b?Ke(i(),b,S):""}function rt(b,S,O,G){if(!(G>0))return 0;for(var pe=O,ce=O+G-1,le=0;le<b.length;++le){var be=b.charCodeAt(le);if(be>=55296&&be<=57343){var et=b.charCodeAt(++le);be=65536+((be&1023)<<10)|et&1023}if(be<=127){if(O>=ce)break;S[O++]=be}else if(be<=2047){if(O+1>=ce)break;S[O++]=192|be>>6,S[O++]=128|be&63}else if(be<=65535){if(O+2>=ce)break;S[O++]=224|be>>12,S[O++]=128|be>>6&63,S[O++]=128|be&63}else{if(O+3>=ce)break;S[O++]=240|be>>18,S[O++]=128|be>>12&63,S[O++]=128|be>>6&63,S[O++]=128|be&63}}return S[O]=0,O-pe}function it(b,S,O){return rt(b,i(),S,O)}function je(b){for(var S=0,O=0;O<b.length;++O){var G=b.charCodeAt(O);G>=55296&&G<=57343&&(G=65536+((G&1023)<<10)|b.charCodeAt(++O)&1023),G<=127?++S:G<=2047?S+=2:G<=65535?S+=3:S+=4}return S}function lt(b,S){s().set(b,S)}var ut=65536;function On(b,S){return b%S>0&&(b+=S-b%S),b}var Ye,xn,qt,wn,qn,hn,nn,Xn,kr;function _n(b){Ye=b,u.HEAP8=xn=new Int8Array(b),u.HEAP16=wn=new Int16Array(b),u.HEAP32=hn=new Int32Array(b),u.HEAPU8=qt=new Uint8Array(b),u.HEAPU16=qn=new Uint16Array(b),u.HEAPU32=nn=new Uint32Array(b),u.HEAPF32=Xn=new Float32Array(b),u.HEAPF64=kr=new Float64Array(b)}var ki=5256480,Pl=ki,cr=13600,Kn=5256480,hr=12672,Ii=u.INITIAL_MEMORY||16777216;if(x)Y=u.wasmMemory,Ye=u.buffer;else if(u.wasmMemory)Y=u.wasmMemory;else if(Y=new WebAssembly.Memory({initial:Ii/ut,maximum:2147483648/ut,shared:!0}),!(Y.buffer instanceof SharedArrayBuffer))throw V("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"),g&&console.log("(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)"),Error("bad memory");Y&&(Ye=Y.buffer),Ii=Ye.byteLength,_n(Ye),x||(o()[hr>>2]=Kn);function Ni(b){for(;b.length>0;){var S=b.shift();if(typeof S=="function"){S(u);continue}var O=S.func;typeof O=="number"?S.arg===void 0?u.dynCall_v(O):u.dynCall_vi(O,S.arg):O(S.arg===void 0?null:S.arg)}}var Va=[],Ll=[],d1=[],Wl=[],Uc=[],Bl=!1;x&&(Bl=!0);function Zn(){if(!x){if(u.preRun)for(typeof u.preRun=="function"&&(u.preRun=[u.preRun]);u.preRun.length;)m1(u.preRun.shift());Ni(Va)}}function Hc(){Bl=!0,Ni(Ll)}function p1(){x||Ni(d1)}function f1(){if(!x){if(u.postRun)for(typeof u.postRun=="function"&&(u.postRun=[u.postRun]);u.postRun.length;)Ua(u.postRun.shift());Ni(Uc)}}function m1(b){Va.unshift(b)}function Ua(b){Uc.unshift(b)}var Si=Math.ceil,A1=Math.floor,jr=0,Vl=null,Ha=null;function y1(b){ke(!x,"addRunDependency cannot be used in a pthread worker"),jr++,u.monitorRunDependencies&&u.monitorRunDependencies(jr)}function g1(b){if(jr--,u.monitorRunDependencies&&u.monitorRunDependencies(jr),jr==0&&(Vl!==null&&(clearInterval(Vl),Vl=null),Ha)){var S=Ha;Ha=null,S()}}u.preloadedImages={},u.preloadedAudios={};function Gr(b){throw u.onAbort&&u.onAbort(b),x&&console.error("Pthread aborting at "+new Error().stack),b+="",H(b),V(b),me=!0,Ae=1,b="abort("+b+"). Build with -s ASSERTIONS=1 for more info.",new WebAssembly.RuntimeError(b)}function Ul(b,S){return String.prototype.startsWith?b.startsWith(S):b.indexOf(S)===0}var x1="data:application/octet-stream;base64,";function jc(b){return Ul(b,x1)}var w1="file://";function Gc(b){return Ul(b,w1)}var Jn="tfjs-backend-wasm-threaded-simd.wasm";jc(Jn)||(Jn=I(Jn));function qc(){try{if(J)return new Uint8Array(J);if(N)return N(Jn);throw"both async and sync fetching of the wasm failed"}catch(b){Gr(b)}}function _1(){return!J&&(A||y)&&typeof fetch=="function"&&!Gc(Jn)?fetch(Jn,{credentials:"same-origin"}).then(function(b){if(!b.ok)throw"failed to load wasm binary file at '"+Jn+"'";return b.arrayBuffer()}).catch(function(){return qc()}):new Promise(function(b,S){b(qc())})}function b1(){var b={a:ff};function S(le,be){var et=le.exports;if(u.asm=et,ne=be,!x){var Ft=fe.unusedWorkers.length;fe.unusedWorkers.forEach(function(Yt){fe.loadWasmModuleToWorker(Yt,function(){--Ft||g1("wasm-instantiate")})})}}x||y1("wasm-instantiate");function O(le){S(le.instance,le.module)}function G(le){return _1().then(function(be){return WebAssembly.instantiate(be,b)}).then(le,function(be){V("failed to asynchronously prepare wasm: "+be),Gr(be)})}function pe(){if(!J&&typeof WebAssembly.instantiateStreaming=="function"&&!jc(Jn)&&!Gc(Jn)&&typeof fetch=="function")fetch(Jn,{credentials:"same-origin"}).then(function(le){var be=WebAssembly.instantiateStreaming(le,b);return be.then(O,function(et){V("wasm streaming compile failed: "+et),V("falling back to ArrayBuffer instantiation"),G(O)})});else return G(O)}if(u.instantiateWasm)try{var ce=u.instantiateWasm(b,S);return ce}catch(le){return V("Module.instantiateWasm callback failed with error: "+le),!1}return pe(),{}}var v1={};function k1(){fe.initRuntime()}x||Ll.push({func:function(){Gl()}});var Xc=0,Kc=0,Zc=0;function Ti(b,S,O){b=b|0,S=S|0,O=O|0,Xc=b,Zc=S,Kc=O}u.__register_pthread_ptr=Ti;var Hl={EPERM:63,ENOENT:44,ESRCH:71,EINTR:27,EIO:29,ENXIO:60,E2BIG:1,ENOEXEC:45,EBADF:8,ECHILD:12,EAGAIN:6,EWOULDBLOCK:6,ENOMEM:48,EACCES:2,EFAULT:21,ENOTBLK:105,EBUSY:10,EEXIST:20,EXDEV:75,ENODEV:43,ENOTDIR:54,EISDIR:31,EINVAL:28,ENFILE:41,EMFILE:33,ENOTTY:59,ETXTBSY:74,EFBIG:22,ENOSPC:51,ESPIPE:70,EROFS:69,EMLINK:34,EPIPE:64,EDOM:18,ERANGE:68,ENOMSG:49,EIDRM:24,ECHRNG:106,EL2NSYNC:156,EL3HLT:107,EL3RST:108,ELNRNG:109,EUNATCH:110,ENOCSI:111,EL2HLT:112,EDEADLK:16,ENOLCK:46,EBADE:113,EBADR:114,EXFULL:115,ENOANO:104,EBADRQC:103,EBADSLT:102,EDEADLOCK:16,EBFONT:101,ENOSTR:100,ENODATA:116,ETIME:117,ENOSR:118,ENONET:119,ENOPKG:120,EREMOTE:121,ENOLINK:47,EADV:122,ESRMNT:123,ECOMM:124,EPROTO:65,EMULTIHOP:36,EDOTDOT:125,EBADMSG:9,ENOTUNIQ:126,EBADFD:127,EREMCHG:128,ELIBACC:129,ELIBBAD:130,ELIBSCN:131,ELIBMAX:132,ELIBEXEC:133,ENOSYS:52,ENOTEMPTY:55,ENAMETOOLONG:37,ELOOP:32,EOPNOTSUPP:138,EPFNOSUPPORT:139,ECONNRESET:15,ENOBUFS:42,EAFNOSUPPORT:5,EPROTOTYPE:67,ENOTSOCK:57,ENOPROTOOPT:50,ESHUTDOWN:140,ECONNREFUSED:14,EADDRINUSE:3,ECONNABORTED:13,ENETUNREACH:40,ENETDOWN:38,ETIMEDOUT:73,EHOSTDOWN:142,EHOSTUNREACH:23,EINPROGRESS:26,EALREADY:7,EDESTADDRREQ:17,EMSGSIZE:35,EPROTONOSUPPORT:66,ESOCKTNOSUPPORT:137,EADDRNOTAVAIL:4,ENETRESET:39,EISCONN:30,ENOTCONN:53,ETOOMANYREFS:141,EUSERS:136,EDQUOT:19,ESTALE:72,ENOTSUP:138,ENOMEDIUM:148,EILSEQ:25,EOVERFLOW:61,ECANCELED:11,ENOTRECOVERABLE:56,EOWNERDEAD:62,ESTRPIPE:135},Ei=13584;function Ci(b,S){if(b<=0||b>s().length||b&!0||S<0)return-28;if(S==0)return 0;S>=2147483647&&(S=Infinity);var O=Atomics.load(o(),Ei>>2),G=0;if(O==b){var pe=Atomics.compareExchange(o(),Ei>>2,O,0);if(pe==O&&(--S,G=1,S<=0))return 1}var ce=Atomics.notify(o(),b>>2,S);if(ce>=0)return ce+G;throw"Atomics.notify returned an unexpected value "+ce}u._emscripten_futex_wake=Ci;function I1(b){if(x)throw"Internal Error! _kill_thread() can only ever be called from main application thread!";if(!b)throw"Internal Error! Null pthread_ptr in _kill_thread!";o()[b+12>>2]=0;var S=fe.pthreads[b];S.worker.terminate(),fe.freeThreadData(S),fe.runningWorkers.splice(fe.runningWorkers.indexOf(S.worker),1),S.worker.pthread=void 0}function N1(b){if(x)throw"Internal Error! _cancel_thread() can only ever be called from main application thread!";if(!b)throw"Internal Error! Null pthread_ptr in _cancel_thread!";var S=fe.pthreads[b];S.worker.postMessage({cmd:"cancel"})}function S1(b){if(x)throw"Internal Error! _cleanup_thread() can only ever be called from main application thread!";if(!b)throw"Internal Error! Null pthread_ptr in _cleanup_thread!";o()[b+12>>2]=0;var S=fe.pthreads[b];if(S){var O=S.worker;fe.returnWorkerToPool(O)}}var fe={MAIN_THREAD_ID:1,mainThreadInfo:{schedPolicy:0,schedPrio:0},unusedWorkers:[],runningWorkers:[],initRuntime:function(){Ti(fe.mainThreadBlock,!y,1),S2(fe.mainThreadBlock)},initMainThreadBlock:function(){for(var b=8,S=0;S<b;++S)fe.allocateUnusedWorker();fe.mainThreadBlock=12832;for(var S=0;S<232/4;++S)l()[fe.mainThreadBlock/4+S]=0;o()[fe.mainThreadBlock+12>>2]=fe.mainThreadBlock;var O=fe.mainThreadBlock+156;o()[O>>2]=O;for(var G=13072,S=0;S<128;++S)l()[G/4+S]=0;Atomics.store(l(),fe.mainThreadBlock+104>>2,G),Atomics.store(l(),fe.mainThreadBlock+40>>2,fe.mainThreadBlock),Atomics.store(l(),fe.mainThreadBlock+44>>2,42)},initWorker:function(){},pthreads:{},exitHandlers:null,setThreadStatus:function(){},runExitHandlers:function(){if(fe.exitHandlers!==null){for(;fe.exitHandlers.length>0;)fe.exitHandlers.pop()();fe.exitHandlers=null}x&&de&&N2()},threadExit:function(b){var S=Ir();S&&(Atomics.store(l(),S+4>>2,b),Atomics.store(l(),S+0>>2,1),Atomics.store(l(),S+60>>2,1),Atomics.store(l(),S+64>>2,0),fe.runExitHandlers(),Ci(S+0,2147483647),Ti(0,0,0),de=0,x&&postMessage({cmd:"exit"}))},threadCancel:function(){fe.runExitHandlers(),Atomics.store(l(),de+4>>2,-1),Atomics.store(l(),de+0>>2,1),Ci(de+0,2147483647),de=he=0,Ti(0,0,0),postMessage({cmd:"cancelDone"})},terminateAllThreads:function(){for(var b in fe.pthreads){var S=fe.pthreads[b];S&&S.worker&&fe.returnWorkerToPool(S.worker)}fe.pthreads={};for(var O=0;O<fe.unusedWorkers.length;++O){var G=fe.unusedWorkers[O];G.terminate()}fe.unusedWorkers=[];for(var O=0;O<fe.runningWorkers.length;++O){var G=fe.runningWorkers[O],S=G.pthread;fe.freeThreadData(S),G.terminate()}fe.runningWorkers=[]},freeThreadData:function(b){if(b){if(b.threadInfoStruct){var S=o()[b.threadInfoStruct+104>>2];o()[b.threadInfoStruct+104>>2]=0,Yl(S),Yl(b.threadInfoStruct)}b.threadInfoStruct=0,b.allocatedOwnStack&&b.stackBase&&Yl(b.stackBase),b.stackBase=0,b.worker&&(b.worker.pthread=null)}},returnWorkerToPool:function(b){delete fe.pthreads[b.pthread.thread],fe.unusedWorkers.push(b),fe.runningWorkers.splice(fe.runningWorkers.indexOf(b),1),fe.freeThreadData(b.pthread),b.pthread=void 0},receiveObjectTransfer:function(b){},loadWasmModuleToWorker:function(b,S){b.onmessage=function(O){var G=O.data,pe=G.cmd;if(b.pthread&&(fe.currentProxiedOperationCallerThread=b.pthread.threadInfoStruct),G.targetThread&&G.targetThread!=Ir()){var ce=fe.pthreads[G.targetThread];ce?ce.worker.postMessage(O.data,G.transferList):console.error('Internal error! Worker sent a message "'+pe+'" to target pthread '+G.targetThread+", but that thread no longer exists!"),fe.currentProxiedOperationCallerThread=void 0;return}if(pe==="processQueuedMainThreadWork")yf();else if(pe==="spawnThread")nh(O.data);else if(pe==="cleanupThread")S1(G.thread);else if(pe==="killThread")I1(G.thread);else if(pe==="cancelThread")N1(G.thread);else if(pe==="loaded")b.loaded=!0,S&&S(b),b.runPthread&&(b.runPthread(),delete b.runPthread);else if(pe==="print")H("Thread "+G.threadId+": "+G.text);else if(pe==="printErr")V("Thread "+G.threadId+": "+G.text);else if(pe==="alert")alert("Thread "+G.threadId+": "+G.text);else if(pe==="exit"){var le=b.pthread&&Atomics.load(l(),b.pthread.thread+68>>2);le&&fe.returnWorkerToPool(b)}else pe==="cancelDone"?fe.returnWorkerToPool(b):pe==="objectTransfer"?fe.receiveObjectTransfer(O.data):O.data.target==="setimmediate"?b.postMessage(O.data):V("worker sent an unknown command "+pe);fe.currentProxiedOperationCallerThread=void 0},b.onerror=function(O){V("pthread sent an error! "+O.filename+":"+O.lineno+": "+O.message)},g&&(b.on("message",function(O){b.onmessage({data:O})}),b.on("error",function(O){b.onerror(O)}),b.on("exit",function(O){console.log("worker exited - TODO: update the worker queue?")})),b.postMessage({cmd:"load",urlOrBlob:u.mainScriptUrlOrBlob||r,wasmMemory:Y,wasmModule:ne,DYNAMIC_BASE:Kn,DYNAMICTOP_PTR:hr})},allocateUnusedWorker:function(){var b=I("tfjs-backend-wasm-threaded-simd.worker.js");fe.unusedWorkers.push(new Worker(b))},getNewWorker:function(){return fe.unusedWorkers.length==0&&(fe.allocateUnusedWorker(),fe.loadWasmModuleToWorker(fe.unusedWorkers[0])),fe.unusedWorkers.length>0?fe.unusedWorkers.pop():null},busySpinWait:function(b){for(var S=performance.now()+b;performance.now()<S;);}};function T1(b,S){ki=Pl=b,cr=S,$i(b)}u.establishStackSpace=T1;function E1(){return ae}u.getNoExitRuntime=E1;function C1(b,S,O,G){Gr("Assertion failed: "+Ve(b)+", at: "+[S?Ve(S):"unknown filename",O,G?Ve(G):"unknown function"])}function R1(b,S){var O=_main(b,S)}var ja;g?ja=function(){var b=process.hrtime();return b[0]*1e3+b[1]/1e6}:x?ja=function(){return performance.now()-u.__performance_now_clock_drift}:typeof dateNow!="undefined"?ja=dateNow:ja=function(){return performance.now()};function F1(b){return o()[v2()>>2]=b,b}function M1(b,S){if(x)return ua(1,1,b,S);Wl.unshift({func:b,arg:S})}function $1(b,S){if(b==S)postMessage({cmd:"processQueuedMainThreadWork"});else if(x)postMessage({targetThread:b,cmd:"processThreadQueue"});else{var O=fe.pthreads[b],G=O&&O.worker;if(!G)return;G.postMessage({cmd:"processThreadQueue"})}return 1}function D1(){Gr()}function O1(b,S){b=b|0,S=S|0}function z1(b,S,O){if(b<=0||b>s().length||b&!0)return-28;if(y){var G=Atomics.wait(o(),b>>2,S,O);if(G==="timed-out")return-73;if(G==="not-equal")return-6;if(G==="ok")return 0;throw"Atomics.wait returned an unexpected value "+G}else{var pe=Atomics.load(o(),b>>2);if(S!=pe)return-6;var ce=performance.now(),le=ce+O;Atomics.store(o(),Ei>>2,b);for(var be=b;b==be;){if(ce=performance.now(),ce>le)return-73;yf(),b=Atomics.load(o(),Ei>>2)}return 0}}function P1(){return Zc|0}function L1(){return Kc|0}function W1(b,S,O){i().copyWithin(b,S,S+O)}function B1(){return navigator.hardwareConcurrency}function ua(b,S){for(var O=arguments.length-2,G=Ql(),pe=Mi(O*8),ce=pe>>3,le=0;le<O;le++)c()[ce+le]=arguments[2+le];var be=E2(b,O,pe,S);return $i(G),be}var Ga=[];function Ri(b,S){Ri.array||(Ri.array=[]);var O=Ri.array;O.length=0;for(var G;G=i()[b++];)G===100||G===102?(S=S+7&~7,O.push(c()[S>>3]),S+=8):(S=S+3&~3,O.push(o()[S>>2]),S+=4);return O}function V1(b,S,O){Ga.length=S;for(var G=O>>3,pe=0;pe<S;pe++)Ga[pe]=c()[G+pe];var ce=b<0,le=ce?v1[-b-1]:pf[b];if(ce){var be=Ga[1],et=Ga[2],Ft=Ri(be,et);return le.apply(null,Ft)}return le.apply(null,Ga)}function U1(){return i().length}function H1(b){try{return Y.grow(b-Ye.byteLength+65535>>>16),_n(Y.buffer),1}catch(S){}}function j1(b){b=b>>>0;var S=U1();if(b<=S)return!1;var O=65536,G=2147483648;if(b>G)return!1;for(var pe=16777216,ce=1;ce<=4;ce*=2){var le=S*(1+.2/ce);le=Math.min(le,b+100663296);var be=Math.min(G,On(Math.max(pe,b,le),O)),et=H1(be);if(et)return!0}return!1}var Le={keyEvent:0,mouseEvent:0,wheelEvent:0,uiEvent:0,focusEvent:0,deviceOrientationEvent:0,deviceMotionEvent:0,fullscreenChangeEvent:0,pointerlockChangeEvent:0,visibilityChangeEvent:0,touchEvent:0,previousFullscreenElement:null,previousScreenX:null,previousScreenY:null,removeEventListenersRegistered:!1,removeAllEventListeners:function(){for(var b=Le.eventHandlers.length-1;b>=0;--b)Le._removeHandler(b);Le.eventHandlers=[],Le.deferredCalls=[]},registerRemoveEventListeners:function(){Le.removeEventListenersRegistered||(Wl.push(Le.removeAllEventListeners),Le.removeEventListenersRegistered=!0)},deferredCalls:[],deferCall:function(b,S,O){function G(le,be){if(le.length!=be.length)return!1;for(var et in le)if(le[et]!=be[et])return!1;return!0}for(var pe in Le.deferredCalls){var ce=Le.deferredCalls[pe];if(ce.targetFunction==b&&G(ce.argsList,O))return}Le.deferredCalls.push({targetFunction:b,precedence:S,argsList:O}),Le.deferredCalls.sort(function(le,be){return le.precedence<be.precedence})},removeDeferredCalls:function(b){for(var S=0;S<Le.deferredCalls.length;++S)Le.deferredCalls[S].targetFunction==b&&(Le.deferredCalls.splice(S,1),--S)},canPerformEventHandlerRequests:function(){return Le.inEventHandler&&Le.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(Le.canPerformEventHandlerRequests())for(var b=0;b<Le.deferredCalls.length;++b){var S=Le.deferredCalls[b];Le.deferredCalls.splice(b,1),--b,S.targetFunction.apply(null,S.argsList)}},inEventHandler:0,currentEventHandler:null,eventHandlers:[],removeAllHandlersOnTarget:function(b,S){for(var O=0;O<Le.eventHandlers.length;++O)Le.eventHandlers[O].target==b&&(!S||S==Le.eventHandlers[O].eventTypeString)&&Le._removeHandler(O--)},_removeHandler:function(b){var S=Le.eventHandlers[b];S.target.removeEventListener(S.eventTypeString,S.eventListenerFunc,S.useCapture),Le.eventHandlers.splice(b,1)},registerOrRemoveHandler:function(b){var S=function(G){++Le.inEventHandler,Le.currentEventHandler=b,Le.runDeferredCalls(),b.handlerFunc(G),Le.runDeferredCalls(),--Le.inEventHandler};if(b.callbackfunc)b.eventListenerFunc=S,b.target.addEventListener(b.eventTypeString,S,b.useCapture),Le.eventHandlers.push(b),Le.registerRemoveEventListeners();else for(var O=0;O<Le.eventHandlers.length;++O)Le.eventHandlers[O].target==b.target&&Le.eventHandlers[O].eventTypeString==b.eventTypeString&&Le._removeHandler(O--)},queueEventHandlerOnThread_iiii:function(b,S,O,G,pe){var ce=Ql(),le=Mi(12);o()[le>>2]=O,o()[le+4>>2]=G,o()[le+8>>2]=pe,gf(b,637534208,S,G,le),$i(ce)},getTargetThreadForEventCallback:function(b){switch(b){case 1:return 0;case 2:return fe.currentProxiedOperationCallerThread;default:return b}},getNodeNameForTarget:function(b){return b?b==window?"#window":b==screen?"#screen":b&&b.nodeName?b.nodeName:"":""},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function G1(b){var S=je(b)+1,O=Jl(S);return it(b,O,S),O}function q1(b,S,O,G){var pe=Ql(),ce=Mi(12),le=0;S&&(le=G1(S)),o()[ce>>2]=le,o()[ce+4>>2]=O,o()[ce+8>>2]=G,gf(b,657457152,0,le,ce),$i(pe)}function X1(b,S,O,G){S=S?Ve(S):"",q1(b,S,O,G)}function K1(b){return b>2?Ve(b):b}var Z1=[0,typeof document!="undefined"?document:0,typeof window!="undefined"?window:0];function J1(b){b=K1(b);var S=Z1[b]||(typeof document!="undefined"?document.querySelector(b):void 0);return S}function jl(b){return J1(b)}function Jc(b,S,O){var G=jl(b);if(!G)return-4;if(G.canvasSharedPtr&&(o()[G.canvasSharedPtr>>2]=S,o()[G.canvasSharedPtr+4>>2]=O),G.offscreenCanvas||!G.controlTransferredOffscreen){G.offscreenCanvas&&(G=G.offscreenCanvas);var pe=!1;if(G.GLctxObject&&G.GLctxObject.GLctx){var ce=G.GLctxObject.GLctx.getParameter(2978);pe=ce[0]===0&&ce[1]===0&&ce[2]===G.width&&ce[3]===G.height}G.width=S,G.height=O,pe&&G.GLctxObject.GLctx.viewport(0,0,S,O)}else if(G.canvasSharedPtr){var le=o()[G.canvasSharedPtr+8>>2];return X1(le,b,S,O),1}else return-4;return 0}function Yc(b,S,O){return x?ua(2,1,b,S,O):Jc(b,S,O)}function Y1(b,S,O){var G=jl(b);return G?Jc(b,S,O):Yc(b,S,O)}function Q1(b){b=b|0}function ef(b,S){b=b|0,S=S|0}function tf(b){var S=b.getExtension("ANGLE_instanced_arrays");if(S)return b.vertexAttribDivisor=function(O,G){S.vertexAttribDivisorANGLE(O,G)},b.drawArraysInstanced=function(O,G,pe,ce){S.drawArraysInstancedANGLE(O,G,pe,ce)},b.drawElementsInstanced=function(O,G,pe,ce,le){S.drawElementsInstancedANGLE(O,G,pe,ce,le)},1}function nf(b){var S=b.getExtension("OES_vertex_array_object");if(S)return b.createVertexArray=function(){return S.createVertexArrayOES()},b.deleteVertexArray=function(O){S.deleteVertexArrayOES(O)},b.bindVertexArray=function(O){S.bindVertexArrayOES(O)},b.isVertexArray=function(O){return S.isVertexArrayOES(O)},1}function rf(b){var S=b.getExtension("WEBGL_draw_buffers");if(S)return b.drawBuffers=function(O,G){S.drawBuffersWEBGL(O,G)},1}var Be={counter:1,lastError:0,buffers:[],mappedBuffers:{},programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},currentContext:null,offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,init:function(){for(var b=new Float32Array(Be.MINI_TEMP_BUFFER_SIZE),S=0;S<Be.MINI_TEMP_BUFFER_SIZE;S++)Be.miniTempBufferFloatViews[S]=b.subarray(0,S+1);for(var O=new Int32Array(Be.MINI_TEMP_BUFFER_SIZE),S=0;S<Be.MINI_TEMP_BUFFER_SIZE;S++)Be.miniTempBufferIntViews[S]=O.subarray(0,S+1)},recordError:function(b){Be.lastError||(Be.lastError=b)},getNewId:function(b){for(var S=Be.counter++,O=b.length;O<S;O++)b[O]=null;return S},MINI_TEMP_BUFFER_SIZE:256,miniTempBufferFloatViews:[0],miniTempBufferIntViews:[0],getSource:function(b,S,O,G){for(var pe="",ce=0;ce<S;++ce){var le=G?o()[G+ce*4>>2]:-1;pe+=Ve(o()[O+ce*4>>2],le<0?void 0:le)}return pe},createContext:function(b,S){var O=b.getContext("webgl",S);if(!O)return 0;var G=Be.registerContext(O,S);return G},registerContext:function(b,S){var O=Jl(8);o()[O+4>>2]=Ir();var G={handle:O,attributes:S,version:S.majorVersion,GLctx:b};return b.canvas&&(b.canvas.GLctxObject=G),Be.contexts[O]=G,(typeof S.enableExtensionsByDefault=="undefined"||S.enableExtensionsByDefault)&&Be.initExtensions(G),O},makeContextCurrent:function(b){return Be.currentContext=Be.contexts[b],u.ctx=ca=Be.currentContext&&Be.currentContext.GLctx,!(b&&!ca)},getContext:function(b){return Be.contexts[b]},deleteContext:function(b){Be.currentContext===Be.contexts[b]&&(Be.currentContext=null),typeof Le=="object"&&Le.removeAllHandlersOnTarget(Be.contexts[b].GLctx.canvas),Be.contexts[b]&&Be.contexts[b].GLctx.canvas&&(Be.contexts[b].GLctx.canvas.GLctxObject=void 0),Yl(Be.contexts[b].handle),Be.contexts[b]=null},initExtensions:function(b){if(b||(b=Be.currentContext),!b.initExtensionsDone){b.initExtensionsDone=!0;var S=b.GLctx;tf(S),nf(S),rf(S),S.disjointTimerQueryExt=S.getExtension("EXT_disjoint_timer_query");var O=["OES_texture_float","OES_texture_half_float","OES_standard_derivatives","OES_vertex_array_object","WEBGL_compressed_texture_s3tc","WEBGL_depth_texture","OES_element_index_uint","EXT_texture_filter_anisotropic","EXT_frag_depth","WEBGL_draw_buffers","ANGLE_instanced_arrays","OES_texture_float_linear","OES_texture_half_float_linear","EXT_blend_minmax","EXT_shader_texture_lod","EXT_texture_norm16","WEBGL_compressed_texture_pvrtc","EXT_color_buffer_half_float","WEBGL_color_buffer_float","EXT_sRGB","WEBGL_compressed_texture_etc1","EXT_disjoint_timer_query","WEBGL_compressed_texture_etc","WEBGL_compressed_texture_astc","EXT_color_buffer_float","WEBGL_compressed_texture_s3tc_srgb","EXT_disjoint_timer_query_webgl2","WEBKIT_WEBGL_compressed_texture_pvrtc"],G=S.getSupportedExtensions()||[];G.forEach(function(pe){O.indexOf(pe)!=-1&&S.getExtension(pe)})}},populateUniformTable:function(b){for(var S=Be.programs[b],O=Be.programInfos[b]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1},G=O.uniforms,pe=ca.getProgramParameter(S,35718),ce=0;ce<pe;++ce){var le=ca.getActiveUniform(S,ce),be=le.name;O.maxUniformLength=Math.max(O.maxUniformLength,be.length+1),be.slice(-1)=="]"&&(be=be.slice(0,be.lastIndexOf("[")));var et=ca.getUniformLocation(S,be);if(et){var Ft=Be.getNewId(Be.uniforms);G[be]=[le.size,Ft],Be.uniforms[Ft]=et;for(var Yt=1;Yt<le.size;++Yt){var Di=be+"["+Yt+"]";et=ca.getUniformLocation(S,Di),Ft=Be.getNewId(Be.uniforms),Be.uniforms[Ft]=et}}}}},af=["default","low-power","high-performance"];function sf(b,S){var O={},G=S>>2;O.alpha=!!o()[G+(0>>2)],O.depth=!!o()[G+(4>>2)],O.stencil=!!o()[G+(8>>2)],O.antialias=!!o()[G+(12>>2)],O.premultipliedAlpha=!!o()[G+(16>>2)],O.preserveDrawingBuffer=!!o()[G+(20>>2)];var pe=o()[G+(24>>2)];O.powerPreference=af[pe],O.failIfMajorPerformanceCaveat=!!o()[G+(28>>2)],O.majorVersion=o()[G+(32>>2)],O.minorVersion=o()[G+(36>>2)],O.enableExtensionsByDefault=o()[G+(40>>2)],O.explicitSwapControl=o()[G+(44>>2)],O.proxyContextToMainThread=o()[G+(48>>2)],O.renderViaOffscreenBackBuffer=o()[G+(52>>2)];var ce=jl(b);if(!ce)return-4;if(O.explicitSwapControl)return-1;var le=Be.createContext(ce,O);return le}function of(b,S){return sf(b,S)}var qa={splitPath:function(b){var S=/^(\/?|)([\s\S]*?)((?:\.{1,2}|[^\/]+?|)(\.[^.\/]*|))(?:[\/]*)$/;return S.exec(b).slice(1)},normalizeArray:function(b,S){for(var O=0,G=b.length-1;G>=0;G--){var pe=b[G];pe==="."?b.splice(G,1):pe===".."?(b.splice(G,1),O++):O&&(b.splice(G,1),O--)}if(S)for(;O;O--)b.unshift("..");return b},normalize:function(b){var S=b.charAt(0)==="/",O=b.substr(-1)==="/";return b=qa.normalizeArray(b.split("/").filter(function(G){return!!G}),!S).join("/"),!b&&!S&&(b="."),b&&O&&(b+="/"),(S?"/":"")+b},dirname:function(b){var S=qa.splitPath(b),O=S[0],G=S[1];return!O&&!G?".":(G&&(G=G.substr(0,G.length-1)),O+G)},basename:function(b){if(b==="/")return"/";var S=b.lastIndexOf("/");return S===-1?b:b.substr(S+1)},extname:function(b){return qa.splitPath(b)[3]},join:function(){var b=Array.prototype.slice.call(arguments,0);return qa.normalize(b.join("/"))},join2:function(b,S){return qa.normalize(b+"/"+S)}},Fi={mappings:{},buffers:[null,[],[]],printChar:function(b,S){var O=Fi.buffers[b];S===0||S===10?((b===1?H:V)(Ke(O,0)),O.length=0):O.push(S)},varargs:void 0,get:function(){Fi.varargs+=4;var b=o()[Fi.varargs-4>>2];return b},getStr:function(b){var S=Ve(b);return S},get64:function(b,S){return b}};function Qc(b){return x?ua(3,1,b):0}function eh(b,S,O,G,pe){if(x)return ua(4,1,b,S,O,G,pe)}function th(b,S,O,G){if(x)return ua(5,1,b,S,O,G);for(var pe=0,ce=0;ce<O;ce++){for(var le=o()[S+ce*8>>2],be=o()[S+(ce*8+4)>>2],et=0;et<be;et++)Fi.printChar(b,i()[le+et]);pe+=be}return o()[G>>2]=pe,0}function lf(b){var S=fe.exitHandlers.pop();b&&S()}function uf(b,S){fe.exitHandlers===null&&(fe.exitHandlers=[]),fe.exitHandlers.push(function(){C2(b,S)})}function nh(b){if(x)throw"Internal Error! _spawn_thread() can only ever be called from main application thread!";var S=fe.getNewWorker();if(S.pthread!==void 0)throw"Internal error!";if(!b.pthread_ptr)throw"Internal error, no pthread ptr!";fe.runningWorkers.push(S);for(var O=Jl(128*4),G=0;G<128;++G)o()[O+G*4>>2]=0;var pe=b.stackBase+b.stackSize,ce=fe.pthreads[b.pthread_ptr]={worker:S,stackBase:b.stackBase,stackSize:b.stackSize,allocatedOwnStack:b.allocatedOwnStack,thread:b.pthread_ptr,threadInfoStruct:b.pthread_ptr},le=ce.threadInfoStruct>>2;Atomics.store(l(),le+(0>>2),0),Atomics.store(l(),le+(4>>2),0),Atomics.store(l(),le+(8>>2),0),Atomics.store(l(),le+(68>>2),b.detached),Atomics.store(l(),le+(104>>2),O),Atomics.store(l(),le+(48>>2),0),Atomics.store(l(),le+(40>>2),ce.threadInfoStruct),Atomics.store(l(),le+(44>>2),42),Atomics.store(l(),le+(108>>2),b.stackSize),Atomics.store(l(),le+(84>>2),b.stackSize),Atomics.store(l(),le+(80>>2),pe),Atomics.store(l(),le+(108+8>>2),pe),Atomics.store(l(),le+(108+12>>2),b.detached),Atomics.store(l(),le+(108+20>>2),b.schedPolicy),Atomics.store(l(),le+(108+24>>2),b.schedPrio);var be=k2(),et=be+40;Atomics.store(l(),le+(176>>2),et),S.pthread=ce;var Ft={cmd:"run",start_routine:b.startRoutine,arg:b.arg,threadInfoStruct:b.pthread_ptr,selfThreadId:b.pthread_ptr,parentThreadId:b.parent_pthread_ptr,stackBase:b.stackBase,stackSize:b.stackSize};S.runPthread=function(){Ft.time=performance.now(),S.postMessage(Ft,b.transferList)},S.loaded&&(S.runPthread(),delete S.runPthread)}function cf(b,S,O){if(!S&&!O)return Hl.EINVAL;if(!b)return V("pthread_getschedparam called with a null thread pointer!"),Hl.ESRCH;var G=o()[b+12>>2];if(G!==b)return V("pthread_getschedparam attempted on thread "+b+", which does not point to a valid thread, or does not exist anymore!"),Hl.ESRCH;var pe=Atomics.load(l(),b+108+20>>2),ce=Atomics.load(l(),b+108+24>>2);return S&&(o()[S>>2]=pe),O&&(o()[O>>2]=ce),0}function Ir(){return Xc|0}u._pthread_self=Ir;function hf(b,S,O,G){if(typeof SharedArrayBuffer=="undefined")return V("Current environment does not support SharedArrayBuffer, pthreads are not available!"),6;if(!b)return V("pthread_create called with a null thread pointer!"),28;var pe=[],ce=0;if(x&&(pe.length===0||ce))return T2(687865856,b,S,O,G);if(ce)return ce;var le=0,be=0,et=0,Ft=0,Yt=0;if(S){le=o()[S>>2],le+=81920,be=o()[S+8>>2],et=o()[S+12>>2]!==0;var Di=o()[S+16>>2]===0;if(Di){var tu=o()[S+20>>2],Pn=o()[S+24>>2],da=fe.currentProxiedOperationCallerThread?fe.currentProxiedOperationCallerThread:Ir();cf(da,S+20,S+24),Ft=o()[S+20>>2],Yt=o()[S+24>>2],o()[S+20>>2]=tu,o()[S+24>>2]=Pn}else Ft=o()[S+20>>2],Yt=o()[S+24>>2]}else le=2097152;var nu=be==0;nu?be=I2(16,le):(be-=le,ke(be>0));for(var Oi=Jl(232),wf=0;wf<232>>2;++wf)l()[(Oi>>2)+wf]=0;o()[b>>2]=Oi,o()[Oi+12>>2]=Oi;var F2=Oi+156;o()[F2>>2]=F2;var _f={stackBase:be,stackSize:le,allocatedOwnStack:nu,schedPolicy:Ft,schedPrio:Yt,detached:et,startRoutine:O,pthread_ptr:Oi,parent_pthread_ptr:Ir(),arg:G,transferList:pe};return x?(_f.cmd="spawnThread",postMessage(_f,pe)):nh(_f),0}function df(b){return b=+b,b>=0?+A1(b+.5):+Si(b-.5)}function rh(b){if(x)return ua(6,1,b);switch(b){case 30:return 16384;case 85:var S=2147483648;return S/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 80:case 81:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:case 79: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: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?fe.initWorker():fe.initMainThreadBlock();var ca;Be.init();var pf=[null,M1,Yc,Qc,eh,th,rh],ff={e:C1,r:R1,w:$1,a:D1,l:O1,d:z1,c:Ci,h:ja,g:P1,x:L1,q:W1,B:B1,t:V1,A:j1,u:Y1,k:Q1,s:ef,v:of,m:Qc,o:eh,i:th,p:k1,memory:Y||u.wasmMemory,y:lf,z:uf,j:hf,b:Ir,f:df,n:rh,table:ue},ah=b1();u.asm=ah;var Gl=u.___wasm_call_ctors=function(){return(Gl=u.___wasm_call_ctors=u.asm.C).apply(null,arguments)},ql=u._init=function(){return(ql=u._init=u.asm.D).apply(null,arguments)},sh=u._register_tensor=function(){return(sh=u._register_tensor=u.asm.E).apply(null,arguments)},Xa=u._dispose_data=function(){return(Xa=u._dispose_data=u.asm.F).apply(null,arguments)},Xl=u._dispose=function(){return(Xl=u._dispose=u.asm.G).apply(null,arguments)},mf=u._Abs=function(){return(mf=u._Abs=u.asm.H).apply(null,arguments)},Af=u._Add=function(){return(Af=u._Add=u.asm.I).apply(null,arguments)},Kl=u._AddN=function(){return(Kl=u._AddN=u.asm.J).apply(null,arguments)},ih=u._ArgMax=function(){return(ih=u._ArgMax=u.asm.K).apply(null,arguments)},oh=u._AvgPool=function(){return(oh=u._AvgPool=u.asm.L).apply(null,arguments)},j=u._BatchMatMul=function(){return(j=u._BatchMatMul=u.asm.M).apply(null,arguments)},te=u._ClipByValue=function(){return(te=u._ClipByValue=u.asm.N).apply(null,arguments)},Ie=u._Conv2D=function(){return(Ie=u._Conv2D=u.asm.O).apply(null,arguments)},Fe=u._Conv2DBackpropInput=function(){return(Fe=u._Conv2DBackpropInput=u.asm.P).apply(null,arguments)},tt=u._Cos=function(){return(tt=u._Cos=u.asm.Q).apply(null,arguments)},It=u._CropAndResize=function(){return(It=u._CropAndResize=u.asm.R).apply(null,arguments)},Ze=u._Cumsum=function(){return(Ze=u._Cumsum=u.asm.S).apply(null,arguments)},Ge=u._DepthToSpace=function(){return(Ge=u._DepthToSpace=u.asm.T).apply(null,arguments)},Wt=u._DepthwiseConv2dNative=function(){return(Wt=u._DepthwiseConv2dNative=u.asm.U).apply(null,arguments)},qr=u._Equal=function(){return(qr=u._Equal=u.asm.V).apply(null,arguments)},Xr=u._Exp=function(){return(Xr=u._Exp=u.asm.W).apply(null,arguments)},lh=u._FlipLeftRight=function(){return(lh=u._FlipLeftRight=u.asm.X).apply(null,arguments)},Zl=u._Floor=function(){return(Zl=u._Floor=u.asm.Y).apply(null,arguments)},zn=u._FloorDiv=function(){return(zn=u._FloorDiv=u.asm.Z).apply(null,arguments)},ha=u._FusedBatchNorm=function(){return(ha=u._FusedBatchNorm=u.asm._).apply(null,arguments)},uh=u._FusedConv2D=function(){return(uh=u._FusedConv2D=u.asm.$).apply(null,arguments)},sv=u._FusedDepthwiseConv2D=function(){return(sv=u._FusedDepthwiseConv2D=u.asm.aa).apply(null,arguments)},iv=u._Gather=function(){return(iv=u._Gather=u.asm.ba).apply(null,arguments)},ov=u._GatherNd=function(){return(ov=u._GatherNd=u.asm.ca).apply(null,arguments)},lv=u._Greater=function(){return(lv=u._Greater=u.asm.da).apply(null,arguments)},uv=u._GreaterEqual=function(){return(uv=u._GreaterEqual=u.asm.ea).apply(null,arguments)},cv=u._LeakyRelu=function(){return(cv=u._LeakyRelu=u.asm.fa).apply(null,arguments)},hv=u._Less=function(){return(hv=u._Less=u.asm.ga).apply(null,arguments)},dv=u._LessEqual=function(){return(dv=u._LessEqual=u.asm.ha).apply(null,arguments)},pv=u._Log=function(){return(pv=u._Log=u.asm.ia).apply(null,arguments)},fv=u._LogicalAnd=function(){return(fv=u._LogicalAnd=u.asm.ja).apply(null,arguments)},mv=u._Max=function(){return(mv=u._Max=u.asm.ka).apply(null,arguments)},Av=u._MaxPool=function(){return(Av=u._MaxPool=u.asm.la).apply(null,arguments)},yv=u._Maximum=function(){return(yv=u._Maximum=u.asm.ma).apply(null,arguments)},gv=u._Mean=function(){return(gv=u._Mean=u.asm.na).apply(null,arguments)},xv=u._Min=function(){return(xv=u._Min=u.asm.oa).apply(null,arguments)},wv=u._Minimum=function(){return(wv=u._Minimum=u.asm.pa).apply(null,arguments)},_v=u._Multiply=function(){return(_v=u._Multiply=u.asm.qa).apply(null,arguments)},bv=u._Neg=function(){return(bv=u._Neg=u.asm.ra).apply(null,arguments)},vv=u._NonMaxSuppressionV3=function(){return(vv=u._NonMaxSuppressionV3=u.asm.sa).apply(null,arguments)},kv=u._NonMaxSuppressionV4=function(){return(kv=u._NonMaxSuppressionV4=u.asm.ta).apply(null,arguments)},Iv=u._NonMaxSuppressionV5=function(){return(Iv=u._NonMaxSuppressionV5=u.asm.ua).apply(null,arguments)},Nv=u._NotEqual=function(){return(Nv=u._NotEqual=u.asm.va).apply(null,arguments)},Sv=u._OneHot=function(){return(Sv=u._OneHot=u.asm.wa).apply(null,arguments)},Tv=u._PadV2=function(){return(Tv=u._PadV2=u.asm.xa).apply(null,arguments)},Ev=u._Pow=function(){return(Ev=u._Pow=u.asm.ya).apply(null,arguments)},Cv=u._Prelu=function(){return(Cv=u._Prelu=u.asm.za).apply(null,arguments)},Rv=u._Prod=function(){return(Rv=u._Prod=u.asm.Aa).apply(null,arguments)},Fv=u._RealDiv=function(){return(Fv=u._RealDiv=u.asm.Ba).apply(null,arguments)},Mv=u._Relu=function(){return(Mv=u._Relu=u.asm.Ca).apply(null,arguments)},$v=u._Relu6=function(){return($v=u._Relu6=u.asm.Da).apply(null,arguments)},Dv=u._ResizeBilinear=function(){return(Dv=u._ResizeBilinear=u.asm.Ea).apply(null,arguments)},Ov=u._Reverse=function(){return(Ov=u._Reverse=u.asm.Fa).apply(null,arguments)},zv=u._RotateWithOffset=function(){return(zv=u._RotateWithOffset=u.asm.Ga).apply(null,arguments)},Pv=u._Round=function(){return(Pv=u._Round=u.asm.Ha).apply(null,arguments)},Lv=u._Rsqrt=function(){return(Lv=u._Rsqrt=u.asm.Ia).apply(null,arguments)},Wv=u._ScatterNd=function(){return(Wv=u._ScatterNd=u.asm.Ja).apply(null,arguments)},Bv=u._SelectV2=function(){return(Bv=u._SelectV2=u.asm.Ka).apply(null,arguments)},Vv=u._Sigmoid=function(){return(Vv=u._Sigmoid=u.asm.La).apply(null,arguments)},Uv=u._Sin=function(){return(Uv=u._Sin=u.asm.Ma).apply(null,arguments)},Hv=u._Softmax=function(){return(Hv=u._Softmax=u.asm.Na).apply(null,arguments)},jv=u._Sqrt=function(){return(jv=u._Sqrt=u.asm.Oa).apply(null,arguments)},Gv=u._Square=function(){return(Gv=u._Square=u.asm.Pa).apply(null,arguments)},qv=u._SquaredDifference=function(){return(qv=u._SquaredDifference=u.asm.Qa).apply(null,arguments)},Xv=u._Step=function(){return(Xv=u._Step=u.asm.Ra).apply(null,arguments)},Kv=u._StridedSlice=function(){return(Kv=u._StridedSlice=u.asm.Sa).apply(null,arguments)},Zv=u._Sub=function(){return(Zv=u._Sub=u.asm.Ta).apply(null,arguments)},Jv=u._Sum=function(){return(Jv=u._Sum=u.asm.Ua).apply(null,arguments)},Yv=u._Tanh=function(){return(Yv=u._Tanh=u.asm.Va).apply(null,arguments)},Qv=u._Tile=function(){return(Qv=u._Tile=u.asm.Wa).apply(null,arguments)},e4=u._TopK=function(){return(e4=u._TopK=u.asm.Xa).apply(null,arguments)},t4=u._Transpose=function(){return(t4=u._Transpose=u.asm.Ya).apply(null,arguments)},n4=u.__FusedMatMul=function(){return(n4=u.__FusedMatMul=u.asm.Za).apply(null,arguments)},Jl=u._malloc=function(){return(Jl=u._malloc=u.asm._a).apply(null,arguments)},Yl=u._free=function(){return(Yl=u._free=u.asm.$a).apply(null,arguments)},r4=u.___em_js__initPthreadsJS=function(){return(r4=u.___em_js__initPthreadsJS=u.asm.ab).apply(null,arguments)},v2=u.___errno_location=function(){return(v2=u.___errno_location=u.asm.bb).apply(null,arguments)},k2=u._emscripten_get_global_libc=function(){return(k2=u._emscripten_get_global_libc=u.asm.cb).apply(null,arguments)},I2=u._memalign=function(){return(I2=u._memalign=u.asm.db).apply(null,arguments)},N2=u.___pthread_tsd_run_dtors=function(){return(N2=u.___pthread_tsd_run_dtors=u.asm.eb).apply(null,arguments)},yf=u._emscripten_main_thread_process_queued_calls=function(){return(yf=u._emscripten_main_thread_process_queued_calls=u.asm.fb).apply(null,arguments)},a4=u._emscripten_current_thread_process_queued_calls=function(){return(a4=u._emscripten_current_thread_process_queued_calls=u.asm.gb).apply(null,arguments)},S2=u._emscripten_register_main_browser_thread_id=function(){return(S2=u._emscripten_register_main_browser_thread_id=u.asm.hb).apply(null,arguments)},s4=u._emscripten_main_browser_thread_id=function(){return(s4=u._emscripten_main_browser_thread_id=u.asm.ib).apply(null,arguments)},i4=u._emscripten_async_run_in_main_thread=function(){return(i4=u._emscripten_async_run_in_main_thread=u.asm.jb).apply(null,arguments)},o4=u._emscripten_sync_run_in_main_thread=function(){return(o4=u._emscripten_sync_run_in_main_thread=u.asm.kb).apply(null,arguments)},l4=u._emscripten_sync_run_in_main_thread_0=function(){return(l4=u._emscripten_sync_run_in_main_thread_0=u.asm.lb).apply(null,arguments)},u4=u._emscripten_sync_run_in_main_thread_1=function(){return(u4=u._emscripten_sync_run_in_main_thread_1=u.asm.mb).apply(null,arguments)},c4=u._emscripten_sync_run_in_main_thread_2=function(){return(c4=u._emscripten_sync_run_in_main_thread_2=u.asm.nb).apply(null,arguments)},h4=u._emscripten_sync_run_in_main_thread_xprintf_varargs=function(){return(h4=u._emscripten_sync_run_in_main_thread_xprintf_varargs=u.asm.ob).apply(null,arguments)},d4=u._emscripten_sync_run_in_main_thread_3=function(){return(d4=u._emscripten_sync_run_in_main_thread_3=u.asm.pb).apply(null,arguments)},T2=u._emscripten_sync_run_in_main_thread_4=function(){return(T2=u._emscripten_sync_run_in_main_thread_4=u.asm.qb).apply(null,arguments)},p4=u._emscripten_sync_run_in_main_thread_5=function(){return(p4=u._emscripten_sync_run_in_main_thread_5=u.asm.rb).apply(null,arguments)},f4=u._emscripten_sync_run_in_main_thread_6=function(){return(f4=u._emscripten_sync_run_in_main_thread_6=u.asm.sb).apply(null,arguments)},m4=u._emscripten_sync_run_in_main_thread_7=function(){return(m4=u._emscripten_sync_run_in_main_thread_7=u.asm.tb).apply(null,arguments)},E2=u._emscripten_run_in_main_runtime_thread_js=function(){return(E2=u._emscripten_run_in_main_runtime_thread_js=u.asm.ub).apply(null,arguments)},gf=u._emscripten_async_queue_on_thread_=function(){return(gf=u._emscripten_async_queue_on_thread_=u.asm.vb).apply(null,arguments)},A4=u._emscripten_tls_init=function(){return(A4=u._emscripten_tls_init=u.asm.wb).apply(null,arguments)},Ql=u.stackSave=function(){return(Ql=u.stackSave=u.asm.xb).apply(null,arguments)},Mi=u.stackAlloc=function(){return(Mi=u.stackAlloc=u.asm.yb).apply(null,arguments)},$i=u.stackRestore=function(){return($i=u.stackRestore=u.asm.zb).apply(null,arguments)},C2=u.dynCall_vi=function(){return(C2=u.dynCall_vi=u.asm.Ab).apply(null,arguments)},y4=u.dynCall_v=function(){return(y4=u.dynCall_v=u.asm.Bb).apply(null,arguments)},g4=u.dynCall_ii=function(){return(g4=u.dynCall_ii=u.asm.Cb).apply(null,arguments)};u.asm=ah,u.cwrap=Oe,u.PThread=fe,u.PThread=fe,u._pthread_self=Ir,u.wasmMemory=Y,u.ExitStatus=R2;var eu;u.then=function(b){if(eu)b(u);else{var S=u.onRuntimeInitialized;u.onRuntimeInitialized=function(){S&&S(),b(u)}}return u};function R2(b){this.name="ExitStatus",this.message="Program terminated with exit("+b+")",this.status=b}Ha=function b(){eu||xf(),eu||(Ha=b)};function xf(b){if(b=b||p,jr>0||(Zn(),jr>0))return;function S(){eu||(eu=!0,u.calledRun=!0,!me&&(Hc(),p1(),u.onRuntimeInitialized&&u.onRuntimeInitialized(),f1()))}u.setStatus?(u.setStatus("Running..."),setTimeout(function(){setTimeout(function(){u.setStatus("")},1),S()},1)):S()}if(u.run=xf,u.preInit)for(typeof u.preInit=="function"&&(u.preInit=[u.preInit]);u.preInit.length>0;)u.preInit.pop()();return x||(ae=!0),x||xf(),a}}();typeof e=="object"&&typeof t=="object"?t.exports=n:typeof define=="function"&&define.amd?define([],function(){return n}):typeof e=="object"&&(e.WasmBackendModuleThreadedSimd=n)}),Q8=nt((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;for(o in s)s.hasOwnProperty(o)&&(i[o]=s[o]);var l=[],c="./this.program",u=function(j,te){throw te},h=!1,d=!1,p=!1,f=!1;h=typeof window=="object",d=typeof importScripts=="function",p=typeof process=="object"&&typeof process.versions=="object"&&typeof process.versions.node=="string",f=!h&&!p&&!d;var m="";function A(j){return s.locateFile?s.locateFile(j,m):m+j}var y,g,w,x,_,I;p?(d?m=Hu().dirname(m)+"/":m=__dirname+"/",y=function(j,te){return _||(_=require("fs")),I||(I=Hu()),j=I.normalize(j),_.readFileSync(j,te?null:"utf8")},w=function(j){var te=y(j,!0);return te.buffer||(te=new Uint8Array(te)),V(te.buffer),te},process.argv.length>1&&(c=process.argv[1].replace(/\\/g,"/")),l=process.argv.slice(2),process.on("uncaughtException",function(j){if(!(j instanceof Xl))throw j}),process.on("unhandledRejection",Va),u=function(j){process.exit(j)},s.inspect=function(){return"[Emscripten Module object]"}):f?(typeof read!="undefined"&&(y=function(j){return read(j)}),w=function(j){var te;return typeof readbuffer=="function"?new Uint8Array(readbuffer(j)):(te=read(j,"binary"),V(typeof te=="object"),te)},typeof scriptArgs!="undefined"?l=scriptArgs:typeof arguments!="undefined"&&(l=arguments),typeof quit=="function"&&(u=function(j){quit(j)}),typeof print!="undefined"&&(typeof console=="undefined"&&(console={}),console.log=print,console.warn=console.error=typeof printErr!="undefined"?printErr:print)):(h||d)&&(d?m=self.location.href:document.currentScript&&(m=document.currentScript.src),r&&(m=r),m.indexOf("blob:")!==0?m=m.substr(0,m.lastIndexOf("/")+1):m="",y=function(j){var te=new XMLHttpRequest;return te.open("GET",j,!1),te.send(null),te.responseText},d&&(w=function(j){var te=new XMLHttpRequest;return te.open("GET",j,!1),te.responseType="arraybuffer",te.send(null),new Uint8Array(te.response)}),g=function(j,te,Ie){var Fe=new XMLHttpRequest;Fe.open("GET",j,!0),Fe.responseType="arraybuffer",Fe.onload=function(){if(Fe.status==200||Fe.status==0&&Fe.response){te(Fe.response);return}Ie()},Fe.onerror=Ie,Fe.send(null)},x=function(j){document.title=j});var T=s.print||console.log.bind(console),E=s.printErr||console.warn.bind(console);for(o in i)i.hasOwnProperty(o)&&(s[o]=i[o]);i=null,s.arguments&&(l=s.arguments),s.thisProgram&&(c=s.thisProgram),s.quit&&(u=s.quit);var N;s.wasmBinary&&(N=s.wasmBinary);var F;s.noExitRuntime&&(F=s.noExitRuntime),typeof WebAssembly!="object"&&E("no native wasm support detected");var $,D=new WebAssembly.Table({initial:151,maximum:151+0,element:"anyfunc"}),P=!1,H=0;function V(j,te){j||Va("Assertion failed: "+te)}function K(j){var te=s["_"+j];return V(te,"Cannot call unknown function "+j+", make sure it is exported"),te}function X(j,te,Ie,Fe,tt){var It={string:function(zn){var ha=0;if(zn!=null&&zn!==0){var uh=(zn.length<<2)+1;ha=ql(uh),ne(zn,ha,uh)}return ha},array:function(zn){var ha=ql(zn.length);return de(zn,ha),ha}};function Ze(zn){return te==="string"?Y(zn):te==="boolean"?Boolean(zn):zn}var Ge=K(j),Wt=[],qr=0;if(Fe)for(var Xr=0;Xr<Fe.length;Xr++){var lh=It[Ie[Xr]];lh?(qr===0&&(qr=Gl()),Wt[Xr]=lh(Fe[Xr])):Wt[Xr]=Fe[Xr]}var Zl=Ge.apply(null,Wt);return Zl=Ze(Zl),qr!==0&&sh(qr),Zl}function ee(j,te,Ie,Fe){Ie=Ie||[];var tt=Ie.every(function(Ze){return Ze==="number"}),It=te!=="string";return It&&tt&&!Fe?K(j):function(){return X(j,te,Ie,arguments,Fe)}}var J=typeof TextDecoder!="undefined"?new TextDecoder("utf8"):void 0;function ae(j,te,Ie){for(var Fe=te+Ie,tt=te;j[tt]&&!(tt>=Fe);)++tt;if(tt-te>16&&j.subarray&&J)return J.decode(j.subarray(te,tt));for(var It="";te<tt;){var Ze=j[te++];if(!(Ze&128)){It+=String.fromCharCode(Ze);continue}var Ge=j[te++]&63;if((Ze&224)==192){It+=String.fromCharCode((Ze&31)<<6|Ge);continue}var Wt=j[te++]&63;if((Ze&240)==224?Ze=(Ze&15)<<12|Ge<<6|Wt:Ze=(Ze&7)<<18|Ge<<12|Wt<<6|j[te++]&63,Ze<65536)It+=String.fromCharCode(Ze);else{var qr=Ze-65536;It+=String.fromCharCode(55296|qr>>10,56320|qr&1023)}}return It}function Y(j,te){return j?ae(Ae,j,te):""}function ue(j,te,Ie,Fe){if(!(Fe>0))return 0;for(var tt=Ie,It=Ie+Fe-1,Ze=0;Ze<j.length;++Ze){var Ge=j.charCodeAt(Ze);if(Ge>=55296&&Ge<=57343){var Wt=j.charCodeAt(++Ze);Ge=65536+((Ge&1023)<<10)|Wt&1023}if(Ge<=127){if(Ie>=It)break;te[Ie++]=Ge}else if(Ge<=2047){if(Ie+1>=It)break;te[Ie++]=192|Ge>>6,te[Ie++]=128|Ge&63}else if(Ge<=65535){if(Ie+2>=It)break;te[Ie++]=224|Ge>>12,te[Ie++]=128|Ge>>6&63,te[Ie++]=128|Ge&63}else{if(Ie+3>=It)break;te[Ie++]=240|Ge>>18,te[Ie++]=128|Ge>>12&63,te[Ie++]=128|Ge>>6&63,te[Ie++]=128|Ge&63}}return te[Ie]=0,Ie-tt}function ne(j,te,Ie){return ue(j,Ae,te,Ie)}function de(j,te){me.set(j,te)}var he,me,Ae,ke,Ee,Re,Oe,Ke,Ve;function rt(j){he=j,s.HEAP8=me=new Int8Array(j),s.HEAP16=ke=new Int16Array(j),s.HEAP32=Re=new Int32Array(j),s.HEAPU8=Ae=new Uint8Array(j),s.HEAPU16=Ee=new Uint16Array(j),s.HEAPU32=Oe=new Uint32Array(j),s.HEAPF32=Ke=new Float32Array(j),s.HEAPF64=Ve=new Float64Array(j)}var it=s.INITIAL_MEMORY||16777216;function je(j){for(;j.length>0;){var te=j.shift();if(typeof te=="function"){te(s);continue}var Ie=te.func;typeof Ie=="number"?te.arg===void 0?s.dynCall_v(Ie):s.dynCall_vi(Ie,te.arg):Ie(te.arg===void 0?null:te.arg)}}var lt=[],ut=[],On=[],Ye=[],xn=!1,qt=!1;function wn(){if(s.preRun)for(typeof s.preRun=="function"&&(s.preRun=[s.preRun]);s.preRun.length;)kr(s.preRun.shift());je(lt)}function qn(){xn=!0,je(ut)}function hn(){je(On)}function nn(){qt=!0}function Xn(){if(s.postRun)for(typeof s.postRun=="function"&&(s.postRun=[s.postRun]);s.postRun.length;)_n(s.postRun.shift());je(Ye)}function kr(j){lt.unshift(j)}function _n(j){Ye.unshift(j)}var ki=Math.ceil,Pl=Math.floor,cr=0,Kn=null,hr=null;function Ii(j){cr++,s.monitorRunDependencies&&s.monitorRunDependencies(cr)}function Ni(j){if(cr--,s.monitorRunDependencies&&s.monitorRunDependencies(cr),cr==0&&(Kn!==null&&(clearInterval(Kn),Kn=null),hr)){var te=hr;hr=null,te()}}s.preloadedImages={},s.preloadedAudios={};function Va(j){throw s.onAbort&&s.onAbort(j),j+="",T(j),E(j),P=!0,H=1,j="abort("+j+"). Build with -s ASSERTIONS=1 for more info.",new WebAssembly.RuntimeError(j)}function Ll(j,te){return String.prototype.startsWith?j.startsWith(te):j.indexOf(te)===0}var d1="data:application/octet-stream;base64,";function Wl(j){return Ll(j,d1)}var Uc="file://";function Bl(j){return Ll(j,Uc)}var Zn="tfjs-backend-wasm.wasm";Wl(Zn)||(Zn=A(Zn));function Hc(){try{if(N)return new Uint8Array(N);if(w)return w(Zn);throw"both async and sync fetching of the wasm failed"}catch(j){Va(j)}}function p1(){return!N&&(h||d)&&typeof fetch=="function"&&!Bl(Zn)?fetch(Zn,{credentials:"same-origin"}).then(function(j){if(!j.ok)throw"failed to load wasm binary file at '"+Zn+"'";return j.arrayBuffer()}).catch(function(){return Hc()}):new Promise(function(j,te){j(Hc())})}function f1(){var j={env:Gr,wasi_snapshot_preview1:Gr};function te(Ze,Ge){var Wt=Ze.exports;s.asm=Wt,$=Wt.memory,rt($.buffer),Ni("wasm-instantiate")}Ii("wasm-instantiate");function Ie(Ze){te(Ze.instance)}function Fe(Ze){return p1().then(function(Ge){return WebAssembly.instantiate(Ge,j)}).then(Ze,function(Ge){E("failed to asynchronously prepare wasm: "+Ge),Va(Ge)})}function tt(){if(!N&&typeof WebAssembly.instantiateStreaming=="function"&&!Wl(Zn)&&!Bl(Zn)&&typeof fetch=="function")fetch(Zn,{credentials:"same-origin"}).then(function(Ze){var Ge=WebAssembly.instantiateStreaming(Ze,j);return Ge.then(Ie,function(Wt){E("wasm streaming compile failed: "+Wt),E("falling back to ArrayBuffer instantiation"),Fe(Ie)})});else return Fe(Ie)}if(s.instantiateWasm)try{var It=s.instantiateWasm(j,te);return It}catch(Ze){return E("Module.instantiateWasm callback failed with error: "+Ze),!1}return tt(),{}}ut.push();function m1(j){rt($.buffer)}var Ua={splitPath:function(j){var te=/^(\/?|)([\s\S]*?)((?:\.{1,2}|[^\/]+?|)(\.[^.\/]*|))(?:[\/]*)$/;return te.exec(j).slice(1)},normalizeArray:function(j,te){for(var Ie=0,Fe=j.length-1;Fe>=0;Fe--){var tt=j[Fe];tt==="."?j.splice(Fe,1):tt===".."?(j.splice(Fe,1),Ie++):Ie&&(j.splice(Fe,1),Ie--)}if(te)for(;Ie;Ie--)j.unshift("..");return j},normalize:function(j){var te=j.charAt(0)==="/",Ie=j.substr(-1)==="/";return j=Ua.normalizeArray(j.split("/").filter(function(Fe){return!!Fe}),!te).join("/"),!j&&!te&&(j="."),j&&Ie&&(j+="/"),(te?"/":"")+j},dirname:function(j){var te=Ua.splitPath(j),Ie=te[0],Fe=te[1];return!Ie&&!Fe?".":(Fe&&(Fe=Fe.substr(0,Fe.length-1)),Ie+Fe)},basename:function(j){if(j==="/")return"/";var te=j.lastIndexOf("/");return te===-1?j:j.substr(te+1)},extname:function(j){return Ua.splitPath(j)[3]},join:function(){var j=Array.prototype.slice.call(arguments,0);return Ua.normalize(j.join("/"))},join2:function(j,te){return Ua.normalize(j+"/"+te)}},Si={mappings:{},buffers:[null,[],[]],printChar:function(j,te){var Ie=Si.buffers[j];te===0||te===10?((j===1?T:E)(ae(Ie,0)),Ie.length=0):Ie.push(te)},varargs:void 0,get:function(){Si.varargs+=4;var j=Re[Si.varargs-4>>2];return j},getStr:function(j){var te=Y(j);return te},get64:function(j,te){return j}};function A1(j){return 0}function jr(j,te,Ie,Fe,tt){}function Vl(j,te,Ie,Fe){for(var tt=0,It=0;It<Ie;It++){for(var Ze=Re[te+It*8>>2],Ge=Re[te+(It*8+4)>>2],Wt=0;Wt<Ge;Wt++)Si.printChar(j,Ae[Ze+Wt]);tt+=Ge}return Re[Fe>>2]=tt,0}function Ha(j){ih(j)}function y1(j){Ha(j)}function g1(j){return j=+j,j>=0?+Pl(j+.5):+ki(j-.5)}var Gr={emscripten_notify_memory_growth:m1,fd_close:A1,fd_seek:jr,fd_write:Vl,proc_exit:y1,roundf:g1},Ul=f1();s.asm=Ul;var x1=s._init=function(){return(x1=s._init=s.asm.init).apply(null,arguments)},jc=s._register_tensor=function(){return(jc=s._register_tensor=s.asm.register_tensor).apply(null,arguments)},w1=s._dispose_data=function(){return(w1=s._dispose_data=s.asm.dispose_data).apply(null,arguments)},Gc=s._dispose=function(){return(Gc=s._dispose=s.asm.dispose).apply(null,arguments)},Jn=s._Abs=function(){return(Jn=s._Abs=s.asm.Abs).apply(null,arguments)},qc=s._Add=function(){return(qc=s._Add=s.asm.Add).apply(null,arguments)},_1=s._AddN=function(){return(_1=s._AddN=s.asm.AddN).apply(null,arguments)},b1=s._ArgMax=function(){return(b1=s._ArgMax=s.asm.ArgMax).apply(null,arguments)},v1=s._AvgPool=function(){return(v1=s._AvgPool=s.asm.AvgPool).apply(null,arguments)},k1=s._BatchMatMul=function(){return(k1=s._BatchMatMul=s.asm.BatchMatMul).apply(null,arguments)},Xc=s._ClipByValue=function(){return(Xc=s._ClipByValue=s.asm.ClipByValue).apply(null,arguments)},Kc=s._Conv2D=function(){return(Kc=s._Conv2D=s.asm.Conv2D).apply(null,arguments)},Zc=s._Conv2DBackpropInput=function(){return(Zc=s._Conv2DBackpropInput=s.asm.Conv2DBackpropInput).apply(null,arguments)},Ti=s._Cos=function(){return(Ti=s._Cos=s.asm.Cos).apply(null,arguments)},Hl=s._CropAndResize=function(){return(Hl=s._CropAndResize=s.asm.CropAndResize).apply(null,arguments)},Ei=s._Cumsum=function(){return(Ei=s._Cumsum=s.asm.Cumsum).apply(null,arguments)},Ci=s._DepthToSpace=function(){return(Ci=s._DepthToSpace=s.asm.DepthToSpace).apply(null,arguments)},I1=s._DepthwiseConv2dNative=function(){return(I1=s._DepthwiseConv2dNative=s.asm.DepthwiseConv2dNative).apply(null,arguments)},N1=s._Equal=function(){return(N1=s._Equal=s.asm.Equal).apply(null,arguments)},S1=s._Exp=function(){return(S1=s._Exp=s.asm.Exp).apply(null,arguments)},fe=s._FlipLeftRight=function(){return(fe=s._FlipLeftRight=s.asm.FlipLeftRight).apply(null,arguments)},T1=s._Floor=function(){return(T1=s._Floor=s.asm.Floor).apply(null,arguments)},E1=s._FloorDiv=function(){return(E1=s._FloorDiv=s.asm.FloorDiv).apply(null,arguments)},C1=s._FusedBatchNorm=function(){return(C1=s._FusedBatchNorm=s.asm.FusedBatchNorm).apply(null,arguments)},R1=s._FusedConv2D=function(){return(R1=s._FusedConv2D=s.asm.FusedConv2D).apply(null,arguments)},ja=s._FusedDepthwiseConv2D=function(){return(ja=s._FusedDepthwiseConv2D=s.asm.FusedDepthwiseConv2D).apply(null,arguments)},F1=s._Gather=function(){return(F1=s._Gather=s.asm.Gather).apply(null,arguments)},M1=s._GatherNd=function(){return(M1=s._GatherNd=s.asm.GatherNd).apply(null,arguments)},$1=s._Greater=function(){return($1=s._Greater=s.asm.Greater).apply(null,arguments)},D1=s._GreaterEqual=function(){return(D1=s._GreaterEqual=s.asm.GreaterEqual).apply(null,arguments)},O1=s._LeakyRelu=function(){return(O1=s._LeakyRelu=s.asm.LeakyRelu).apply(null,arguments)},z1=s._Less=function(){return(z1=s._Less=s.asm.Less).apply(null,arguments)},P1=s._LessEqual=function(){return(P1=s._LessEqual=s.asm.LessEqual).apply(null,arguments)},L1=s._Log=function(){return(L1=s._Log=s.asm.Log).apply(null,arguments)},W1=s._LogicalAnd=function(){return(W1=s._LogicalAnd=s.asm.LogicalAnd).apply(null,arguments)},B1=s._Max=function(){return(B1=s._Max=s.asm.Max).apply(null,arguments)},ua=s._MaxPool=function(){return(ua=s._MaxPool=s.asm.MaxPool).apply(null,arguments)},Ga=s._Maximum=function(){return(Ga=s._Maximum=s.asm.Maximum).apply(null,arguments)},Ri=s._Mean=function(){return(Ri=s._Mean=s.asm.Mean).apply(null,arguments)},V1=s._Min=function(){return(V1=s._Min=s.asm.Min).apply(null,arguments)},U1=s._Minimum=function(){return(U1=s._Minimum=s.asm.Minimum).apply(null,arguments)},H1=s._Multiply=function(){return(H1=s._Multiply=s.asm.Multiply).apply(null,arguments)},j1=s._Neg=function(){return(j1=s._Neg=s.asm.Neg).apply(null,arguments)},Le=s._NonMaxSuppressionV3=function(){return(Le=s._NonMaxSuppressionV3=s.asm.NonMaxSuppressionV3).apply(null,arguments)},G1=s._NonMaxSuppressionV4=function(){return(G1=s._NonMaxSuppressionV4=s.asm.NonMaxSuppressionV4).apply(null,arguments)},q1=s._NonMaxSuppressionV5=function(){return(q1=s._NonMaxSuppressionV5=s.asm.NonMaxSuppressionV5).apply(null,arguments)},X1=s._NotEqual=function(){return(X1=s._NotEqual=s.asm.NotEqual).apply(null,arguments)},K1=s._OneHot=function(){return(K1=s._OneHot=s.asm.OneHot).apply(null,arguments)},Z1=s._PadV2=function(){return(Z1=s._PadV2=s.asm.PadV2).apply(null,arguments)},J1=s._Pow=function(){return(J1=s._Pow=s.asm.Pow).apply(null,arguments)},jl=s._Prelu=function(){return(jl=s._Prelu=s.asm.Prelu).apply(null,arguments)},Jc=s._Prod=function(){return(Jc=s._Prod=s.asm.Prod).apply(null,arguments)},Yc=s._RealDiv=function(){return(Yc=s._RealDiv=s.asm.RealDiv).apply(null,arguments)},Y1=s._Relu=function(){return(Y1=s._Relu=s.asm.Relu).apply(null,arguments)},Q1=s._Relu6=function(){return(Q1=s._Relu6=s.asm.Relu6).apply(null,arguments)},ef=s._ResizeBilinear=function(){return(ef=s._ResizeBilinear=s.asm.ResizeBilinear).apply(null,arguments)},tf=s._Reverse=function(){return(tf=s._Reverse=s.asm.Reverse).apply(null,arguments)},nf=s._RotateWithOffset=function(){return(nf=s._RotateWithOffset=s.asm.RotateWithOffset).apply(null,arguments)},rf=s._Round=function(){return(rf=s._Round=s.asm.Round).apply(null,arguments)},Be=s._Rsqrt=function(){return(Be=s._Rsqrt=s.asm.Rsqrt).apply(null,arguments)},af=s._ScatterNd=function(){return(af=s._ScatterNd=s.asm.ScatterNd).apply(null,arguments)},sf=s._SelectV2=function(){return(sf=s._SelectV2=s.asm.SelectV2).apply(null,arguments)},of=s._Sigmoid=function(){return(of=s._Sigmoid=s.asm.Sigmoid).apply(null,arguments)},qa=s._Sin=function(){return(qa=s._Sin=s.asm.Sin).apply(null,arguments)},Fi=s._Softmax=function(){return(Fi=s._Softmax=s.asm.Softmax).apply(null,arguments)},Qc=s._Sqrt=function(){return(Qc=s._Sqrt=s.asm.Sqrt).apply(null,arguments)},eh=s._Square=function(){return(eh=s._Square=s.asm.Square).apply(null,arguments)},th=s._SquaredDifference=function(){return(th=s._SquaredDifference=s.asm.SquaredDifference).apply(null,arguments)},lf=s._Step=function(){return(lf=s._Step=s.asm.Step).apply(null,arguments)},uf=s._StridedSlice=function(){return(uf=s._StridedSlice=s.asm.StridedSlice).apply(null,arguments)},nh=s._Sub=function(){return(nh=s._Sub=s.asm.Sub).apply(null,arguments)},cf=s._Sum=function(){return(cf=s._Sum=s.asm.Sum).apply(null,arguments)},Ir=s._Tanh=function(){return(Ir=s._Tanh=s.asm.Tanh).apply(null,arguments)},hf=s._Tile=function(){return(hf=s._Tile=s.asm.Tile).apply(null,arguments)},df=s._TopK=function(){return(df=s._TopK=s.asm.TopK).apply(null,arguments)},rh=s._Transpose=function(){return(rh=s._Transpose=s.asm.Transpose).apply(null,arguments)},ca=s.__FusedMatMul=function(){return(ca=s.__FusedMatMul=s.asm._FusedMatMul).apply(null,arguments)},pf=s._malloc=function(){return(pf=s._malloc=s.asm.malloc).apply(null,arguments)},ff=s._free=function(){return(ff=s._free=s.asm.free).apply(null,arguments)},ah=s.__start=function(){return(ah=s.__start=s.asm._start).apply(null,arguments)},Gl=s.stackSave=function(){return(Gl=s.stackSave=s.asm.stackSave).apply(null,arguments)},ql=s.stackAlloc=function(){return(ql=s.stackAlloc=s.asm.stackAlloc).apply(null,arguments)},sh=s.stackRestore=function(){return(sh=s.stackRestore=s.asm.stackRestore).apply(null,arguments)};s.asm=Ul,s.cwrap=ee;var Xa;s.then=function(j){if(Xa)j(s);else{var te=s.onRuntimeInitialized;s.onRuntimeInitialized=function(){te&&te(),j(s)}}return s};function Xl(j){this.name="ExitStatus",this.message="Program terminated with exit("+j+")",this.status=j}var mf=!1;hr=function j(){Xa||Kl(),Xa||(hr=j)};function Af(j){var te=s.__start;try{te();var Ie=0;ih(Ie,!0)}catch(tt){if(tt instanceof Xl)return;if(tt=="unwind"){F=!0;return}else{var Fe=tt;tt&&typeof tt=="object"&&tt.stack&&(Fe=[tt,tt.stack]),E("exception thrown: "+Fe),u(1,tt)}}finally{mf=!0}}function Kl(j){if(j=j||l,cr>0||(wn(),cr>0))return;function te(){Xa||(Xa=!0,s.calledRun=!0,!P&&(qn(),hn(),s.onRuntimeInitialized&&s.onRuntimeInitialized(),oh&&Af(j),Xn()))}s.setStatus?(s.setStatus("Running..."),setTimeout(function(){setTimeout(function(){s.setStatus("")},1),te()},1)):te()}s.run=Kl;function ih(j,te){te&&F&&j===0||(F||(P=!0,H=j,nn(),s.onExit&&s.onExit(j)),u(j,new Xl(j)))}if(s.preInit)for(typeof s.preInit=="function"&&(s.preInit=[s.preInit]);s.preInit.length>0;)s.preInit.pop()();var oh=!0;return s.noInitialRun&&(oh=!1),F=!0,Kl(),a}}();typeof e=="object"&&typeof t=="object"?t.exports=n:typeof define=="function"&&define.amd?define([],function(){return n}):typeof e=="object"&&(e.WasmBackendModule=n)}),ek=nt((e,t)=>{(function(n,r,a){function s(c){var u=this,h=l();u.next=function(){var d=2091639*u.s0+u.c*23283064365386963e-26;return u.s0=u.s1,u.s1=u.s2,u.s2=d-(u.c=d|0)},u.c=1,u.s0=h(" "),u.s1=h(" "),u.s2=h(" "),u.s0-=h(c),u.s0<0&&(u.s0+=1),u.s1-=h(c),u.s1<0&&(u.s1+=1),u.s2-=h(c),u.s2<0&&(u.s2+=1),h=null}function i(c,u){return u.c=c.c,u.s0=c.s0,u.s1=c.s1,u.s2=c.s2,u}function o(c,u){var h=new s(c),d=u&&u.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 c=4022871197,u=function(h){h=String(h);for(var d=0;d<h.length;d++){c+=h.charCodeAt(d);var p=.02519603282416938*c;c=p>>>0,p-=c,p*=c,c=p>>>0,p-=c,c+=p*4294967296}return(c>>>0)*23283064365386963e-26};return u}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)}),tk=nt((e,t)=>{(function(n,r,a){function s(l){var c=this,u="";c.x=0,c.y=0,c.z=0,c.w=0,c.next=function(){var d=c.x^c.x<<11;return c.x=c.y,c.y=c.z,c.z=c.w,c.w^=c.w>>>19^d^d>>>8},l===(l|0)?c.x=l:u+=l;for(var h=0;h<u.length+64;h++)c.x^=u.charCodeAt(h)|0,c.next()}function i(l,c){return c.x=l.x,c.y=l.y,c.z=l.z,c.w=l.w,c}function o(l,c){var u=new s(l),h=c&&c.state,d=function(){return(u.next()>>>0)/4294967296};return d.double=function(){do var p=u.next()>>>11,f=(u.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=u.next,d.quick=d,h&&(typeof h=="object"&&i(h,u),d.state=function(){return i(u,{})}),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)}),nk=nt((e,t)=>{(function(n,r,a){function s(l){var c=this,u="";c.next=function(){var d=c.x^c.x>>>2;return c.x=c.y,c.y=c.z,c.z=c.w,c.w=c.v,(c.d=c.d+362437|0)+(c.v=c.v^c.v<<4^(d^d<<1))|0},c.x=0,c.y=0,c.z=0,c.w=0,c.v=0,l===(l|0)?c.x=l:u+=l;for(var h=0;h<u.length+64;h++)c.x^=u.charCodeAt(h)|0,h==u.length&&(c.d=c.x<<10^c.x>>>4),c.next()}function i(l,c){return c.x=l.x,c.y=l.y,c.z=l.z,c.w=l.w,c.v=l.v,c.d=l.d,c}function o(l,c){var u=new s(l),h=c&&c.state,d=function(){return(u.next()>>>0)/4294967296};return d.double=function(){do var p=u.next()>>>11,f=(u.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=u.next,d.quick=d,h&&(typeof h=="object"&&i(h,u),d.state=function(){return i(u,{})}),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)}),rk=nt((e,t)=>{(function(n,r,a){function s(l){var c=this;c.next=function(){var h=c.x,d=c.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,c.i=d+1&7,f};function u(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()}u(c,l)}function i(l,c){return c.x=l.x.slice(),c.i=l.i,c}function o(l,c){l==null&&(l=+new Date);var u=new s(l),h=c&&c.state,d=function(){return(u.next()>>>0)/4294967296};return d.double=function(){do var p=u.next()>>>11,f=(u.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=u.next,d.quick=d,h&&(h.x&&i(h,u),d.state=function(){return i(u,{})}),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)}),ak=nt((e,t)=>{(function(n,r,a){function s(l){var c=this;c.next=function(){var h=c.w,d=c.X,p=c.i,f,m;return c.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,c.i=p,m+(h^h>>>16)|0};function u(h,d){var p,f,m,A,y,g=[],w=128;for(d===(d|0)?(f=d,d=null):(d=d+"\0",f=0,w=Math.max(w,d.length)),m=0,A=-32;A<w;++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}u(c,l)}function i(l,c){return c.i=l.i,c.w=l.w,c.X=l.X.slice(),c}function o(l,c){l==null&&(l=+new Date);var u=new s(l),h=c&&c.state,d=function(){return(u.next()>>>0)/4294967296};return d.double=function(){do var p=u.next()>>>11,f=(u.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=u.next,d.quick=d,h&&(h.X&&i(h,u),d.state=function(){return i(u,{})}),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)}),sk=nt((e,t)=>{(function(n,r,a){function s(l){var c=this,u="";c.next=function(){var d=c.b,p=c.c,f=c.d,m=c.a;return d=d<<25^d>>>7^p,p=p-f|0,f=f<<24^f>>>8^m,m=m-d|0,c.b=d=d<<20^d>>>12^p,c.c=p=p-f|0,c.d=f<<16^p>>>16^m,c.a=m-d|0},c.a=0,c.b=0,c.c=2654435769|0,c.d=1367130551,l===Math.floor(l)?(c.a=l/4294967296|0,c.b=l|0):u+=l;for(var h=0;h<u.length+20;h++)c.b^=u.charCodeAt(h)|0,c.next()}function i(l,c){return c.a=l.a,c.b=l.b,c.c=l.c,c.d=l.d,c}function o(l,c){var u=new s(l),h=c&&c.state,d=function(){return(u.next()>>>0)/4294967296};return d.double=function(){do var p=u.next()>>>11,f=(u.next()>>>0)/4294967296,m=(p+f)/(1<<21);while(m===0);return m},d.int32=u.next,d.quick=d,h&&(typeof h=="object"&&i(h,u),d.state=function(){return i(u,{})}),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)}),ik=nt((e,t)=>{(function(n,r,a){var s=256,i=6,o=52,l="random",c=a.pow(s,i),u=a.pow(2,o),h=u*2,d=s-1,p;function f(_,I,T){var E=[];I=I==!0?{entropy:!0}:I||{};var N=g(y(I.entropy?[_,x(r)]:_==null?w():_,3),E),F=new m(E),$=function(){for(var D=F.g(i),P=c,H=0;D<u;)D=(D+H)*s,P*=s,H=F.g(1);for(;D>=h;)D/=2,P/=2,H>>>=1;return(D+H)/P};return $.int32=function(){return F.g(4)|0},$.quick=function(){return F.g(4)/4294967296},$.double=$,g(x(F.S),r),(I.pass||T||function(D,P,H,V){return V&&(V.S&&A(V,F),D.state=function(){return A(F,{})}),H?(a[l]=D,P):D})($,N,"global"in I?I.global:this==a,I.state)}function m(_){var I,T=_.length,E=this,N=0,F=E.i=E.j=0,$=E.S=[];for(T||(_=[T++]);N<s;)$[N]=N++;for(N=0;N<s;N++)$[N]=$[F=d&F+_[N%T]+(I=$[N])],$[F]=I;(E.g=function(D){for(var P,H=0,V=E.i,K=E.j,X=E.S;D--;)P=X[V=d&V+1],H=H*s+X[d&(X[V]=X[K=d&K+P])+(X[K]=P)];return E.i=V,E.j=K,H})(s)}function A(_,I){return I.i=_.i,I.j=_.j,I.S=_.S.slice(),I}function y(_,I){var T=[],E=typeof _,N;if(I&&E=="object")for(N in _)try{T.push(y(_[N],I-1))}catch(F){}return T.length?T:E=="string"?_:_+"\0"}function g(_,I){for(var T=_+"",E,N=0;N<T.length;)I[d&N]=d&(E^=I[d&N]*19)+T.charCodeAt(N++);return x(I)}function w(){try{var _;return p&&(_=p.randomBytes)?_=_(s):(_=new Uint8Array(s),(n.crypto||n.msCrypto).getRandomValues(_)),x(_)}catch(E){var I=n.navigator,T=I&&I.plugins;return[+new Date,n,T,n.screen,x(r)]}}function x(_){return String.fromCharCode.apply(0,_)}if(g(a.random(),r),typeof t=="object"&&t.exports){t.exports=f;try{p=ym()}catch(_){}}else typeof define=="function"&&define.amd?define(function(){return f}):a["seed"+l]=f})(typeof self!="undefined"?self:e,[],Math)}),H0=nt((e,t)=>{var n=ek(),r=tk(),a=nk(),s=rk(),i=ak(),o=sk(),l=ik();l.alea=n,l.xor128=r,l.xorwow=a,l.xorshift7=s,l.xor4096=i,l.tychei=o,t.exports=l}),ok=nt(()=>{}),lk="3.0.0",uk="3.0.0",ck="3.0.0",hk="3.0.0",dk="3.0.0",pk=1e-7,fk=1e-4,hh=class{constructor(e,t){this.backend=e,this.dataMover=t,this.data=new WeakMap,this.dataIdsCount=0}get(e){return this.data.has(e)||this.dataMover.moveData(this.backend,e),this.data.get(e)}set(e,t){this.dataIdsCount++,this.data.set(e,t)}has(e){return this.data.has(e)}delete(e){return this.dataIdsCount--,this.data.delete(e)}numDataIds(){return this.dataIdsCount}},au=class{decComplexRef(e){}time(e){return Mr("time")}read(e){return Mr("read")}readSync(e){return Mr("readSync")}numDataIds(){return Mr("numDataIds")}disposeData(e){return Mr("disposeData")}write(e,t,n){return Mr("write")}move(e,t,n,r){return Mr("move")}memory(){return Mr("memory")}floatPrecision(){return Mr("floatPrecision")}epsilon(){return this.floatPrecision()===32?pk:fk}dispose(){return Mr("dispose")}};function Mr(e){throw new Error(`'${e}' not yet implemented or not found in the registry. This kernel may not be supported by the tfjs backend you have chosen`)}function j0(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 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 ju(e,t,n){return Math.max(e,Math.min(t,n))}function Ak(e){return e%2==0?e:e+1}function yk(e){let t=0;for(let n=0;n<e.length;n++)t+=e[n];return t}function gk(e,t){let n=Math.random();return t*n+(1-n)*e}function xk(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 M(e,t){if(!e)throw new Error(typeof t=="string"?t:t())}function en(e,t,n=""){M(ta(e,t),()=>n+` Shapes ${e} and ${t} must match`)}function qs(e){M(e!=null,()=>"The input to the tensor constructor must be a non-null value.")}function Xs(e,t=[],n=!1){if(t==null&&(t=[]),Array.isArray(e)||tn(e)&&!n)for(let r=0;r<e.length;++r)Xs(e[r],t,n);else t.push(e);return t}function Dt(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 wk(e){return e.length===0}function ta(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 Ut(e){return e%1==0}function _k(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 bk(e){let t=Math.ceil(Math.sqrt(e));return[t,Math.ceil(e/t)]}function vk(e){let t=new Uint32Array(e);for(let n=0;n<e;++n)t[n]=n;return j0(t),t}function Gu(e,t){return t<=e.length?e:e+" ".repeat(t-e.length)}function kk(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 Ik(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} / ${n}`);let a=e.slice();return a[r]=t/n,a}function ar(e,t){let n=t.length;return e=e==null?t.map((r,a)=>a):[].concat(e),M(e.every(r=>r>=-n&&r<n),()=>`All values in axis param must be in range [-${n}, ${n}) but got axis ${e}`),M(e.every(r=>Ut(r)),()=>`All values in axis param must be integers but got axis ${e}`),e.map(r=>r<0?n+r:r)}function G0(e,t){let n=[],r=[],a=t!=null&&Array.isArray(t)&&t.length===0,s=t==null||a?null:ar(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 q0(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 X0(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 K0(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 Z0(e){return e==="bool"||e==="complex64"||e==="float32"||e==="int32"||e==="string"}function Nk(e,t){return!(t==="complex64"||t==="float32"&&e!=="complex64"||t==="int32"&&e!=="float32"&&e!=="complex64"||t==="bool"&&e==="bool")}function tn(e){return e instanceof Float32Array||e instanceof Int32Array||e instanceof Uint8Array}function J0(e){if(e==="float32"||e==="int32")return 4;if(e==="complex64")return 8;if(e==="bool")return 1;throw new Error(`Unknown dtype ${e}`)}function Y0(e){if(e==null)return 0;let t=0;return e.forEach(n=>t+=n.length),t}function ka(e){return typeof e=="string"||e instanceof String}function Q0(e){return typeof e=="boolean"}function e5(e){return typeof e=="number"}function Cd(e){return Array.isArray(e)?Cd(e[0]):e instanceof Float32Array?"float32":e instanceof Int32Array||e instanceof Uint8Array?"int32":e5(e)?"float32":ka(e)?"string":Q0(e)?"bool":"float32"}function Ia(e){return!!(e&&e.constructor&&e.call&&e.apply)}function Rd(e,t){for(let n=t;n<e;++n)if(e%n==0)return n;return e}function el(e){let t=e.length;if(t<2)return[];let n=new Array(t-1);n[t-2]=e[t-1];for(let r=t-3;r>=0;--r)n[r]=n[r+1]*e[r+1];return n}function t5(e,t,n){let r=new Array;if(t.length===1){let a=t[0];for(let s=0;s<a;s++)r[s]=n[e+s]}else{let a=t[0],s=t.slice(1),i=s.reduce((o,l)=>o*l);for(let o=0;o<a;o++)r[o]=t5(e+o*i,s,n)}return r}function tl(e,t){if(e.length===0)return t[0];let n=e.reduce((r,a)=>r*a);if(n===0)return[];if(n!==t.length)throw new Error(`[${e}] does not match the input size ${t.length}.`);return t5(0,e,t)}function gm(e,t){let n=Fd(e,t);for(let r=0;r<n.length;r++)n[r]=1;return n}function Fd(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 Sk(e,t){let n=e.reduce((r,a)=>r*a,1);if(t==null||t==="float32")return tl(e,new Float32Array(n));if(t==="int32")return tl(e,new Int32Array(n));if(t==="bool")return tl(e,new Uint8Array(n));throw new Error(`Unknown data type ${t}`)}function xm(e){e.forEach(t=>{M(Number.isInteger(t)&&t>=0,()=>`Tensor must have a shape comprised of positive integers but got shape [${e}].`)})}function Tk(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 Ek(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 wm(e){return e&&e.then&&typeof e.then=="function"}var n5="tfjsflags",$2=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(wm(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=Ck(this.global.location.search);n5 in e&&e[n5].split(",").forEach(t=>{let[n,r]=t.split(":");this.urlFlags[n]=Rk(n,r)})}};function Ck(e){let t={};return e.replace(/[?&]([^=?&]+)(?:=([^&]*))?/g,(n,...r)=>(Fk(t,r[0],r[1]),r.join("="))),t}function Fk(e,t,n){e[decodeURIComponent(t)]=decodeURIComponent(n||"")}function Rk(e,t){if(t=t.toLowerCase(),t==="true"||t==="false")return t==="true";if(`${+t}`===t)return+t;throw new Error(`Could not parse value flag value ${t} for flag ${e}.`)}function Q(){return bn}var bn=null;function Mk(e){bn=e}var _m;function r5(){if(_m==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");_m=e}return _m}function $k(){let e=r5();return e._tfGlobals==null&&(e._tfGlobals=new Map),e._tfGlobals}function bm(e,t){let n=$k();if(n.has(e))return n.get(e);{let r=t();return n.set(e,r),n.get(e)}}var zi="Abs",Pi="Acos",Li="Acosh",fa="Add",Ka="AddN",dh="All",ph="Any",Za="ArgMax",su="ArgMin",Wi="Asin",Bi="Asinh",Vi="Atan",Ui="Atanh",Hi="Atan2",Ja="AvgPool",fh="AvgPoolGrad",iu="AvgPool3D",mh="AvgPool3DGrad",Ya="BatchMatMul",ou="BatchToSpaceND",Ah="Bincount",D2="BroadcastTo",Qa="Cast",ji="Ceil",ma="ClipByValue",yh="Complex",lu="ComplexAbs",Gi="Concat",es="Conv2D",gh="Conv2DBackpropFilter",ts="Conv2DBackpropInput",uu="Conv3D",xh="Conv3DBackpropFilterV2",wh="Conv3DBackpropInputV2",ns="Cos",qi="Cosh",rs="Cumsum",Xi="CropAndResize",_h="DenseBincount",Ki="DepthToSpace",as="DepthwiseConv2dNative",bh="DepthwiseConv2dNativeBackpropFilter",vh="DepthwiseConv2dNativeBackpropInput",kh="Diag",cu="Dilation2D",Ih="Dilation2DBackpropInput",Nh="Dilation2DBackpropFilter",ss="RealDiv",Zi="Elu",Sh="EluGrad",Ji="Erf",Yi="Equal",is="Exp",Qi="ExpandDims",eo="Expm1",Th="FFT",hu="Fill",to="FlipLeftRight",os="Floor",ls="FloorDiv",us="FusedBatchNorm",no="GatherV2",ro="GatherNd",ao="Greater",cs="GreaterEqual",so="Identity",Eh="IFFT",Ch="Imag",io="IsFinite",oo="IsInf",lo="IsNan",hs="LeakyRelu",uo="Less",co="LessEqual",Rh="LinSpace",ds="Log",ho="Log1p",po="LogicalAnd",du="LogicalNot",pu="LogicalOr",O2="LogSoftmax",fu="LRN",Fh="LRNGrad",ps="Max",fs="Maximum",ms="MaxPool",Mh="MaxPoolGrad",mu="MaxPool3D",$h="MaxPool3DGrad",Dh="MaxPoolWithArgmax",As="Mean",ys="Min",gs="Minimum",Au="MirrorPad",fo="Mod",Oh="Multinomial",xs="Multiply",mo="Neg",Ao="NotEqual",yo="NonMaxSuppressionV3",go="NonMaxSuppressionV4",xo="NonMaxSuppressionV5",wo="OnesLike",ws="OneHot",_o="Pack",_s="PadV2",C4="Pool",bs="Pow",vs="Prelu",bo="Prod",yu="Range",zh="Real",vo="Reciprocal",ks="Relu",ko="Reshape",gu="ResizeNearestNeighbor",Ph="ResizeNearestNeighborGrad",Is="ResizeBilinear",Lh="ResizeBilinearGrad",Ns="Relu6",Ss="Reverse",Ts="Round",Es="Rsqrt",Io="ScatterNd",No="Select",So="Selu",To="Slice",Cs="Sin",Eo="Sinh",Co="Sign",Rs="Sigmoid",Ro="Softplus",Fs="Sqrt",Ms="Sum",xu="SpaceToBatchND",Fo="SplitV",$s="Softmax",Ds="SquaredDifference",wu="Square",Os="Sub",Wh="SparseToDense",Mo="StridedSlice",$o="Tan",zs="Tanh",Aa="Tile",Do="TopK",Ps="Transpose",Bh="Unique",Oo="Unpack",_u="UnsortedSegmentSum",zo="ZerosLike",ya="Step",Vh="FromPixels",Po="RotateWithOffset",Ls="_FusedMatMul",Ws="FusedConv2D",Bs="FusedDepthwiseConv2D",nl=bm("kernelRegistry",()=>new Map),qu=bm("gradRegistry",()=>new Map);function Uh(e,t){let n=vm(e,t);return nl.get(n)}function If(e){return qu.get(e)}function bu(e){let t=nl.entries(),n=[];for(;;){let{done:r,value:a}=t.next();if(r)break;let[s,i]=a,[o]=s.split("_");o===e&&n.push(i)}return n}function Lo(e){let{kernelName:t,backendName:n}=e,r=vm(t,n);nl.has(r)&&console.warn(`The kernel '${t}' for backend '${n}' is already registered`),nl.set(r,e)}function z2(e){let{kernelName:t}=e;qu.has(t)&&Q().getBool("DEBUG")&&console.warn(`Overriding the gradient for '${t}'`),qu.set(t,e)}function R4(e,t){let n=vm(e,t);if(!nl.has(n))throw new Error(`The kernel '${e}' for backend '${t}' is not registered`);nl.delete(n)}function F4(e){if(!qu.has(e))throw new Error(`The gradient '${e}' for backend is not registered`);qu.delete(e)}function M4(e,t){bu(e).forEach(n=>{let r=Object.assign({},n,{backendName:t});Lo(r)})}function vm(e,t){return`${t}_${e}`}var v={};ze(v,{arraysEqual:()=>ta,assert:()=>M,assertNonNegativeIntegerDimensions:()=>xm,assertNonNull:()=>qs,assertShapesMatch:()=>en,bytesFromStringArray:()=>Y0,bytesPerElement:()=>J0,checkConversionForErrors:()=>K0,clamp:()=>ju,computeStrides:()=>el,createScalarValue:()=>Dk,createShuffledIndices:()=>vk,decodeString:()=>$d,distSquared:()=>xk,encodeString:()=>Xu,fetch:()=>Ok,flatten:()=>Xs,getArrayFromDType:()=>X0,getTypedArrayFromDType:()=>q0,hasEncodingLoss:()=>Nk,indexToLoc:()=>Ek,inferDtype:()=>Cd,inferFromImplicitShape:()=>Ik,isBoolean:()=>Q0,isFunction:()=>Ia,isInt:()=>Ut,isNumber:()=>e5,isPromise:()=>wm,isScalarShape:()=>wk,isString:()=>ka,isTypedArray:()=>tn,isValidDtype:()=>Z0,locToIndex:()=>Tk,makeOnesTypedArray:()=>gm,makeZerosNestedTypedArray:()=>Sk,makeZerosTypedArray:()=>Fd,nearestDivisor:()=>Rd,nearestLargerEven:()=>Ak,now:()=>km,parseAxisParam:()=>ar,randUniform:()=>gk,repeatedTry:()=>kk,rightPad:()=>Gu,shuffle:()=>j0,shuffleCombo:()=>mk,sizeFromShape:()=>Dt,sizeToSquarishShape:()=>bk,squeezeShape:()=>G0,sum:()=>yk,tanh:()=>_k,toNestedArray:()=>tl,toTypedArray:()=>Md});function Dk(e,t){return t==="string"?Xu(e):Md([e],t)}function zk(e,t){return e instanceof Float32Array&&t==="float32"||e instanceof Int32Array&&t==="int32"||e instanceof Uint8Array&&t==="bool"}function Md(e,t){if(t==="string")throw new Error("Cannot convert a string[] to a TypedArray");if(Array.isArray(e)&&(e=Xs(e)),Q().getBool("DEBUG")&&K0(e,t),zk(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 km(){return Q().platform.now()}function Ok(e,t){return Q().platform.fetch(e,t)}function Xu(e,t="utf-8"){return t=t||"utf-8",Q().platform.encode(e,t)}function $d(e,t="utf-8"){return t=t||"utf-8",Q().platform.decode(e,t)}var Wk=class{constructor(e,t){this.backendTimer=e,this.logger=t,t==null&&(this.logger=new Lk)}profileKernel(e,t,n){let r,a=()=>{r=n()},s=this.backendTimer.time(a);if(Q().getBool("CHECK_COMPUTATION_FOR_ERRORS"))for(let i=0;i<r.length;i++){let o=r[i];o.data().then(l=>{Pk(l,o.dtype,e)})}return{kernelName:e,outputs:r,inputs:t,timeMs:s.then(i=>i.kernelMs),extraInfo:s.then(i=>i.getExtraProfileInfo!=null?i.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 Pk(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 Lk=class{logKernelProfile(e,t,n,r,a,s){let i=typeof r=="number"?Gu(`${r}ms`,9):r.error,o=Gu(e,25),l=t.rank,c=t.size,u=Gu(t.shape.toString(),14),h="";for(let d in a){let p=a[d];if(p!=null){let f=p.shape||t.shape,m=f.length;h+=`${d}: ${m}D ${m>0?f:""} `}}console.log(`%c${o} %c${i} %c${l}D ${u} %c${c} %c${h} %c${s}`,"font-weight:bold","color:red","color:blue","color: orange","color: green","color: steelblue")}};function Bk(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 c=e[l],u=c.inputs;for(let h in u){let d=u[h],p=!1;for(let f=0;f<t.length;f++)if(r[d.id]){c.outputs.forEach(m=>r[m.id]=!0),p=!0,a[c.id]=!0;break}if(p)break}}let s={};s[n.id]=!0;let i={};for(let l=e.length-1;l>=0;l--){let c=e[l],u=c.inputs;for(let h=0;h<c.outputs.length;h++)if(s[c.outputs[h].id]){for(let d in u)s[u[d].id]=!0,i[c.id]=!0;break}}let o=[];for(let l=0;l<e.length;l++){let c=e[l];if(a[c.id]&&i[c.id]){let u={};for(let d in c.inputs){let p=c.inputs[d];r[p.id]&&(u[d]=p)}let h=Object.assign({},c);h.inputs=u,h.outputs=c.outputs,o.push(h)}}return o}function Vk(e,t,n,r){for(let a=t.length-1;a>=0;a--){let s=t[a],i=[];if(s.outputs.forEach(l=>{let c=e[l.id];c!=null?i.push(c):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 c=n(()=>o[l]());if(c.dtype!=="float32")throw new Error(`Error in gradient for op ${s.kernelName}. The gradient of input ${l} must have 'float32' dtype, but has '${c.dtype}'`);let u=s.inputs[l];if(!ta(c.shape,u.shape))throw new Error(`Error in gradient for op ${s.kernelName}. The gradient of input '${l}' has shape '${c.shape}', which does not match the shape of the input '${u.shape}'`);if(e[u.id]==null)e[u.id]=c;else{let h=e[u.id];e[u.id]=r(h,c),h.dispose()}}}}var a5=20,Ku=3,Im=7;function Hk(e,t,n,r){let a=el(t),s=Uk(e,t,n,a),i=t.length,o=Dd(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(c=>" "+c).join(`
`)),l.join(`
`)}function Uk(e,t,n,r){let a=Dt(t),s=r[r.length-1],i=new Array(s).fill(0),o=t.length,l=n==="complex64"?Ju(e):e;if(o>1)for(let c=0;c<a/s;c++){let u=c*s;for(let h=0;h<s;h++)i[h]=Math.max(i[h],Zu(l[u+h],0,n).length)}return i}function Zu(e,t,n){let r;return Array.isArray(e)?r=`${parseFloat(e[0].toFixed(Im))} + ${parseFloat(e[1].toFixed(Im))}j`:ka(e)?r=`'${e}'`:n==="bool"?r=s5(e):r=parseFloat(e.toFixed(Im)).toString(),Gu(r,t)}function s5(e){return e===0?"false":"true"}function Dd(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=Ju(e);return[Zu(m[0],0,n)]}return n==="bool"?[s5(e[0])]:[e[0].toString()]}if(l===1){if(o>a5){let A=Ku*i,y=Array.from(e.slice(0,A)),g=Array.from(e.slice((o-Ku)*i,o*i));return n==="complex64"&&(y=Ju(y),g=Ju(g)),["["+y.map((w,x)=>Zu(w,a[x],n)).join(", ")+", ..., "+g.map((w,x)=>Zu(w,a[o-Ku+x],n)).join(", ")+"]"]}let m=n==="complex64"?Ju(e):Array.from(e);return["["+m.map((A,y)=>Zu(A,a[y],n)).join(", ")+"]"]}let c=t.slice(1),u=r.slice(1),h=r[0]*i,d=[];if(o>a5){for(let m=0;m<Ku;m++){let A=m*h,y=A+h;d.push(...Dd(e.slice(A,y),c,n,u,a,!1))}d.push("...");for(let m=o-Ku;m<o;m++){let A=m*h,y=A+h;d.push(...Dd(e.slice(A,y),c,n,u,a,m===o-1))}}else for(let m=0;m<o;m++){let A=m*h,y=A+h;d.push(...Dd(e.slice(A,y),c,n,u,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 Ju(e){let t=[];for(let n=0;n<e.length;n+=2)t.push([e[n],e[n+1]]);return t}var Mt=class{constructor(e,t,n){if(this.dtype=t,this.shape=e.slice(),this.size=Dt(e),n!=null){let r=n.length;M(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||X0(t,this.size),this.strides=el(e)}set(e,...t){t.length===0&&(t=[0]),M(t.length===this.rank,()=>`The number of provided coordinates (${t.length}) must match the rank (${this.rank})`);let n=this.locToIndex(t);this.values[n]=e}get(...e){e.length===0&&(e=[0]);let t=0;for(let 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 $r().makeTensor(this.values,this.shape,this.dtype)}},$r=null,rl=null,jk=null;function Gk(e){$r=e}function qk(e){rl=e}function Xk(e){jk=e}var Qe=class{constructor(e,t,n,r){this.kept=!1,this.isDisposedInternal=!1,this.shape=e.slice(),this.dtype=t||"float32",this.size=Dt(e),this.strides=el(e),this.dataId=n,this.id=r,this.rankType=this.rank<5?this.rank.toString():"higher"}get rank(){return this.shape.length}async buffer(){let e=await this.data();return rl.buffer(this.shape,this.dtype,e)}bufferSync(){return rl.buffer(this.shape,this.dtype,this.dataSync())}async array(){let e=await this.data();return tl(this.shape,e)}arraySync(){return tl(this.shape,this.dataSync())}async data(){this.throwIfDisposed();let e=$r().read(this.dataId);if(this.dtype==="string"){let t=await e;try{return t.map(n=>$d(n))}catch(n){throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().")}}return e}dataSync(){this.throwIfDisposed();let e=$r().readSync(this.dataId);if(this.dtype==="string")try{return e.map(t=>$d(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 $r().read(this.dataId);return this.dtype==="string"?e:new Uint8Array(e.buffer)}dispose(){this.isDisposed||($r().disposeTensor(this),this.isDisposedInternal=!0)}get isDisposed(){return this.isDisposedInternal}throwIfDisposed(){if(this.isDisposed)throw new Error("Tensor is disposed.")}print(e=!1){return rl.print(this,e)}clone(){return this.throwIfDisposed(),rl.clone(this)}toString(e=!1){let t=this.dataSync();return Hk(t,this.shape,this.dtype,e)}cast(e){return this.throwIfDisposed(),rl.cast(this,e)}variable(e=!0,t,n){return this.throwIfDisposed(),$r().makeVariable(this,e,t,n)}};Object.defineProperty(Qe,Symbol.hasInstance,{value:e=>!!e&&e.data!=null&&e.dataSync!=null&&e.throwIfDisposed!=null});function Z(){return bm("Tensor",()=>Qe)}Z();var vu=class extends Qe{constructor(e,t,n,r){super(e.shape,e.dtype,e.dataId,r);this.trainable=t,this.name=n}assign(e){if(e.dtype!==this.dtype)throw new Error(`dtype of the new value (${e.dtype}) and previous value (${this.dtype}) must match`);if(!ta(e.shape,this.shape))throw new Error(`shape of the new value (${e.shape}) and previous value (${this.shape}) must match`);$r().disposeTensor(this),this.dataId=e.dataId,$r().incRef(this,null)}dispose(){$r().disposeVariable(this),this.isDisposedInternal=!0}};Object.defineProperty(vu,Symbol.hasInstance,{value:e=>e instanceof Qe&&e.assign!=null&&e.assign instanceof Function});var dr={};ze(dr,{assertTypesMatch:()=>i5,getTensorsInContainer:()=>Nm,isTensorInList:()=>Kk,makeTypesMatch:()=>vt});var Nf;(function(e){e.R0="R0",e.R1="R1",e.R2="R2",e.R3="R3",e.R4="R4",e.R5="R5",e.R6="R6"})(Nf||(Nf={}));var Sm;(function(e){e.float32="float32",e.int32="int32",e.bool="int32",e.complex64="complex64"})(Sm||(Sm={}));var Tm;(function(e){e.float32="float32",e.int32="int32",e.bool="bool",e.complex64="complex64"})(Tm||(Tm={}));var Em;(function(e){e.float32="float32",e.int32="float32",e.bool="float32",e.complex64="complex64"})(Em||(Em={}));var Cm;(function(e){e.float32="complex64",e.int32="complex64",e.bool="complex64",e.complex64="complex64"})(Cm||(Cm={}));var Zk={float32:Em,int32:Sm,bool:Tm,complex64:Cm};function Qn(e,t){if(e==="string"||t==="string"){if(e==="string"&&t==="string")return"string";throw new Error(`Can not upcast ${e} with ${t}`)}return Zk[e][t]}function Hh(e){return Qn(e,"int32")}function vt(e,t){if(e.dtype===t.dtype)return[e,t];let n=Qn(e.dtype,t.dtype);return[e.cast(n),t.cast(n)]}function i5(e,t){M(e.dtype===t.dtype,()=>`The dtypes of the first(${e.dtype}) and second(${t.dtype}) input must match`)}function Kk(e,t){return t.some(n=>n.id===e.id)}function Nm(e){let t=[],n=new Set;return o5(e,t,n),t}function o5(e,t,n){if(e==null)return;if(e instanceof Qe){t.push(e);return}if(!Jk(e))return;let r=e;for(let a in r){let s=r[a];n.has(s)||(n.add(s),o5(s,t,n))}}function Jk(e){return Array.isArray(e)||typeof e=="object"}function Rm(e){return e.kernelName!=null}var l5=class{constructor(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null,get kernelNames(){return Array.from(new Set(this.kernels.map(e=>e.name)))}}}dispose(){for(let e in this.registeredVariables)this.registeredVariables[e].dispose()}},Yu=class{constructor(e){this.ENV=e,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new l5}async ready(){if(this.pendingBackendInit!=null)return this.pendingBackendInit.then(()=>{});if(this.backendInstance!=null)return;let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let n=e[t];if(await this.initializeBackend(n).success){await this.setBackend(n);return}}throw new Error("Could not initialize any backends, all backend initializations failed.")}get backend(){if(this.pendingBackendInit!=null)throw new Error(`Backend '${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 Wk(this.backendInstance),!0}setupRegisteredKernels(){bu(this.backendName).forEach(e=>{e.setupFunc!=null&&e.setupFunc(this.backendInstance)})}disposeRegisteredKernels(e){bu(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 au)&&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);r.disposeData(t),n.backend=e,e.move(t,a,n.shape,n.dtype),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 Yu.nextTensorId++}nextVariableId(){return Yu.nextVariableId++}clone(e){let t=this.makeTensorFromDataId(e.dataId,e.shape,e.dtype),n={x:e},r=s=>({x:()=>{let i="float32",o={x:s},l={dtype:i};return z.runKernel(Qa,o,l)}}),a=[];return this.addTapeNode(this.state.activeScope.name,n,[t],r,a,{}),t}runKernel(e,t,n){if(Uh(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 '${e}'`)}runKernelFunc(e){let t,n=[],r=this.isTapeOn(),a=this.state.numBytes,s=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let i;this.backendName==null&&this.backend;let o,l=Rm(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(Rm(e)){let{kernelName:p,inputs:f,attrs:m}=e;this.backendName==null&&this.backend;let A=Uh(p,this.backendName);M(A!=null,()=>`Cannot find registered kernel '${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 w=g.map(x=>{if(x.rank!=null)return x;let{dataId:_,shape:I,dtype:T}=x;return this.makeTensorFromDataId(_,I,T)});if(r){let x=this.getTensorsForGradient(p,f,w);n=this.saveTensorsForBackwardMode(x)}return w}}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:c,attrs:u}=e,h=Rm(e)?null:e.backwardsFunc,d;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(d=this.profiler.profileKernel(l,c,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs)}),r&&this.addTapeNode(l,c,t,h,n,u),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(c).map(p=>c[p]!=null?c[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=If(e);if(r!=null){let a=r.inputsToSave||[],s=r.outputsToSave||[],i;r.saveAllInputs?(M(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,c)=>s[c]);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"&&ka(e[0])&&(a=e.map(o=>Xu(o)));let s=r.write(a,t,n),i=new Qe(t,n,s,this.nextTensorId());if(this.incRef(i,r),n==="string"){let o=this.state.tensorInfo.get(s),l=Y0(a);this.state.numBytes+=l-o.bytes,o.bytes=l}return i}makeTensorFromDataId(e,t,n,r){n=n||"float32";let a=new Qe(t,n,e,this.nextTensorId());return this.incRef(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 vu(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}incRef(e,t){let n=this.state.tensorInfo.has(e.dataId)?this.state.tensorInfo.get(e.dataId).refCount:0;if(this.state.numTensors++,e.dtype==="string"&&this.state.numStringTensors++,n===0){this.state.numDataBuffers++;let r=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(r=e.size*J0(e.dtype)),this.state.tensorInfo.set(e.dataId,{backend:t||this.backend,dtype:e.dtype,shape:e.shape,bytes:r,refCount:0}),this.state.numBytes+=r}this.state.tensorInfo.get(e.dataId).refCount++,e instanceof vu||this.track(e)}disposeTensor(e){if(!this.state.tensorInfo.has(e.dataId))return;this.state.numTensors--,e.dtype==="string"&&this.state.numStringTensors--;let t=this.state.tensorInfo.get(e.dataId);t.refCount<=1?(e.dtype!=="complex64"&&(this.state.numBytes-=t.bytes),this.state.numDataBuffers--,t.backend.disposeData(e.dataId),this.state.tensorInfo.delete(e.dataId)):(t.backend.decComplexRef(e.dataId),this.state.tensorInfo.get(e.dataId).refCount--)}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=If(e);o!=null&&(r=o.gradFunc),r!=null&&(i.gradient=l=>(l=l.map((c,u)=>{if(c==null){let h=n[u],d=Fd(h.size,h.dtype);return this.makeTensor(d,h.shape,h.dtype)}return c}),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=Nm(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(M(t.length>0,()=>"gradients() received an empty list of xs."),n!=null&&n.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);let a=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));M(a instanceof Qe,()=>"The result y returned by f() must be a tensor.");let s=Bk(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?Yk(a.shape):n,Vk(i,s,l=>this.tidy(l),Qk);let o=t.map(l=>i[l.id]);return this.state.gradientDepth===0&&(this.state.activeTape.forEach(l=>{for(let c of l.saved)c.dispose()}),this.state.activeTape=null),{value:a,grads:o}})}customGrad(e){return M(Ia(e),()=>"The f passed in customGrad(f) must be a function."),(...t)=>{M(t.every(i=>i instanceof Qe),()=>"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),M(n.value instanceof Qe,()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"),M(Ia(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),c=Array.isArray(l)?l:[l];M(c.length===t.length,()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...)."),M(c.every(h=>h instanceof Qe),()=>"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 u={};return c.forEach((h,d)=>{u[d]=()=>h}),u};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=km(),n=await this.backend.time(e);return n.wallMs=km()-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 l5;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}};Yu.nextTensorId=0;Yu.nextVariableId=0;function Yk(e){let t=gm(Dt(e),"float32");return z.makeTensor(t,e,"float32")}function u5(){let e=r5();if(e._tfengine==null){let t=new $2(e);e._tfengine=new Yu(t)}return Mk(e._tfengine.ENV),Gk(()=>e._tfengine),e._tfengine}var z=u5();function Qk(e,t){let n={a:e,b:t};return z.runKernel(fa,n)}var jh={};ze(jh,{isBrowser:()=>c5,isMobile:()=>e9});function t9(){return typeof navigator!="undefined"&&navigator!=null}function e9(){if(t9()){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 c5(){return typeof window!="undefined"&&window.document!=null||typeof WorkerGlobalScope!="undefined"}var Dr=Q();Dr.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.")});Dr.registerFlag("IS_BROWSER",()=>c5());Dr.registerFlag("IS_NODE",()=>typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined");Dr.registerFlag("IS_CHROME",()=>typeof navigator!="undefined"&&navigator!=null&&navigator.userAgent!=null&&/Chrome/.test(navigator.userAgent)&&/Google Inc/.test(navigator.vendor));Dr.registerFlag("PROD",()=>!1);Dr.registerFlag("TENSORLIKE_CHECK_SHAPE_CONSISTENCY",()=>Dr.getBool("DEBUG"));Dr.registerFlag("DEPRECATION_WARNINGS_ENABLED",()=>!0);Dr.registerFlag("IS_TEST",()=>!1);Dr.registerFlag("CHECK_COMPUTATION_FOR_ERRORS",()=>!0);function Or(e,t){let n=e;if(tn(e))return t==="string"?[]:[e.length];if(!Array.isArray(e))return[];let r=[];for(;Array.isArray(n)||tn(n)&&t!=="string";)r.push(n.length),n=n[0];return Array.isArray(e)&&Q().getBool("TENSORLIKE_CHECK_SHAPE_CONSISTENCY")&&h5(e,r,[]),r}function h5(e,t,n){if(n=n||[],!Array.isArray(e)&&!tn(e)){M(t.length===0,()=>`Element arr[${n.join("][")}] is a primitive, but should be an array/TypedArray of ${t[0]} elements`);return}M(t.length>0,()=>`Element arr[${n.join("][")}] should be a primitive, but is an array of ${e.length} elements`),M(e.length===t[0],()=>`Element arr[${n.join("][")}] should have ${t[0]} elements, but has ${e.length} elements`);let r=t.slice(1);for(let a=0;a<e.length;++a)h5(e[a],r,n.concat(a))}function d5(e,t,n,r){if(e!=="string_or_numeric"){if(e==null)throw new Error("Expected dtype cannot be null.");if(e!=="numeric"&&e!==t||e==="numeric"&&t==="string")throw new Error(`Argument '${n}' passed to '${r}' must be ${e} tensor, but got ${t} tensor`)}}function R(e,t,n,r="numeric"){if(e instanceof Qe)return d5(r,e.dtype,t,n),e;let a=Cd(e);if(a!=="string"&&["bool","int32","float32"].indexOf(r)>=0&&(a=r),d5(r,a,t,n),e==null||!tn(e)&&!Array.isArray(e)&&typeof e!="number"&&typeof e!="boolean"&&typeof e!="string"){let o=e==null?"null":e.constructor.name;throw new Error(`Argument '${t}' passed to '${n}' must be a Tensor or TensorLike, but got '${o}'`)}let s=Or(e,a);!tn(e)&&!Array.isArray(e)&&(e=[e]);let i=a!=="string"?Md(e,a):Xs(e,[],!0);return z.makeTensor(i,s,a)}function Qu(e,t,n,r="numeric"){if(!Array.isArray(e))throw new Error(`Argument ${t} passed to ${n} must be a \`Tensor[]\` or \`TensorLike[]\``);return e.map((a,s)=>R(a,`${t}[${s}]`,n,r))}var P2="__op";function L(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+P2;let a=(...s)=>{z.startScope(n);try{let i=r(...s);return wm(i)&&console.error("Cannot return a Promise inside of tidy."),z.endScope(i),i}catch(i){throw z.endScope(null),i}};return Object.defineProperty(a,"name",{value:n,configurable:!0}),a}function n9(e,t){let n=R(e,"real","complex"),r=R(t,"imag","complex");en(n.shape,r.shape,`real and imag shapes, ${n.shape} and ${r.shape}, must match in call to tf.complex().`);let a={real:n,imag:r};return z.runKernel(yh,a)}var ga=L({complex_:n9});function Na(e,t,n,r){if(r==null&&(r=Cd(e)),r==="complex64")throw new Error("Cannot construct a complex64 tensor directly. Please use tf.complex(real, imag).");if(!tn(e)&&!Array.isArray(e)&&typeof e!="number"&&typeof e!="boolean"&&typeof e!="string")throw new Error("values passed to tensor(values) must be a number/boolean/string or an array of numbers/booleans/strings, or a TypedArray");if(t!=null){xm(t);let a=Dt(t),s=Dt(n);M(a===s,()=>`Based on the provided shape, [${t}], the tensor should have ${a} values but has ${s}`);for(let i=0;i<n.length;++i){let o=n[i],l=i===n.length-1?o!==Dt(t.slice(i)):!0;M(n[i]===t[i]||!l,()=>`Error creating a new Tensor. Inferred shape (${n}) does not match the provided shape (${t}). `)}}return!tn(e)&&!Array.isArray(e)&&(e=[e]),t=t||n,e=r!=="string"?Md(e,r):Xs(e,[],!0),z.makeTensor(e,t,r)}function pr(e,t,n){let r=Or(e,n);return Na(e,t,r,n)}var Fm={float32:4,float16:2,int32:4,uint16:2,uint8:1,bool:1,complex64:8},Od=4;async function a9(e,t){let n=[],r=[],a=Array.isArray(e)?e.map(i=>i.name):Object.keys(e);for(let i=0;i<a.length;++i){let o=a[i],l=Array.isArray(e)?e[i].tensor:e[o];if(l.dtype!=="float32"&&l.dtype!=="int32"&&l.dtype!=="bool"&&l.dtype!=="string"&&l.dtype!=="complex64")throw new Error(`Unsupported dtype in weight '${o}': ${l.dtype}`);let c={name:o,shape:l.shape,dtype:l.dtype};if(l.dtype==="string"){let u=new Promise(async h=>{let d=await l.bytes(),p=d.reduce((A,y)=>A+y.length,0)+Od*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+=Od,f.set(y,m),m+=y.length}h(f)});r.push(u)}else r.push(l.data());t!=null&&(c.group=t),n.push(c)}let s=await Promise.all(r);return{data:r9(s),specs:n}}function p5(e,t){let n={},r,a=0;for(let s of t){let i=s.name,o=s.dtype,l=s.shape,c=Dt(l),u;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=Fm[h.dtype],p=e.slice(a,a+c*d),f=h.dtype==="uint8"?new Uint8Array(p):new Uint16Array(p);if(o==="float32")if(h.dtype==="uint8"||h.dtype==="uint16"){u=new Float32Array(f.length);for(let m=0;m<f.length;m++){let A=f[m];u[m]=A*h.scale+h.min}}else if(h.dtype==="float16")r===void 0&&(r=s9()),u=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 ${h.dtype} for weight type int32.`);u=new Int32Array(f.length);for(let m=0;m<f.length;m++){let A=f[m];u[m]=Math.round(A*h.scale+h.min)}}else throw new Error(`Unsupported dtype in weight '${i}': ${o}`);a+=c*d}else if(o==="string"){let h=Dt(s.shape);u=[];for(let d=0;d<h;d++){let p=new Uint32Array(e.slice(a,a+Od))[0];a+=Od;let f=new Uint8Array(e.slice(a,a+p));u.push(f),a+=p}}else{let h=Fm[o],d=e.slice(a,a+c*h);if(o==="float32")u=new Float32Array(d);else if(o==="int32")u=new Int32Array(d);else if(o==="bool")u=new Uint8Array(d);else if(o==="complex64"){u=new Float32Array(d);let p=new Float32Array(u.length/2),f=new Float32Array(u.length/2);for(let y=0;y<p.length;y++)p[y]=u[y*2],f[y]=u[y*2+1];let m=pr(p,l,"float32"),A=pr(f,l,"float32");n[i]=ga(m,A),m.dispose(),A.dispose()}else throw new Error(`Unsupported dtype in weight '${i}': ${o}`);a+=c*h}o!=="complex64"&&(n[i]=pr(u,l,o))}return n}function r9(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 Mm=typeof Buffer!="undefined"&&(typeof Blob=="undefined"||typeof atob=="undefined"||typeof btoa=="undefined");function f5(e){return Mm?Buffer.byteLength(e):new Blob([e]).size}function i9(e){if(Mm)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 o9(e){if(Mm){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 $m(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 m5(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 ec(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:f5(JSON.stringify(e.modelTopology)),weightSpecsBytes:e.weightSpecs==null?0:f5(JSON.stringify(e.weightSpecs)),weightDataBytes:e.weightData==null?0:e.weightData.byteLength}}function l9(){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 u9(){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 c9(){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=l9(),t=u9(),n=c9();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 Nt=class{constructor(){this.saveRouters=[],this.loadRouters=[]}static getInstance(){return Nt.instance==null&&(Nt.instance=new Nt),Nt.instance}static registerSaveRouter(e){Nt.getInstance().saveRouters.push(e)}static registerLoadRouter(e){Nt.getInstance().loadRouters.push(e)}static getSaveHandlers(e){return Nt.getHandlers(e,"save")}static getLoadHandlers(e,t){return Nt.getHandlers(e,"load",t)}static getHandlers(e,t,n){let r=[];return(t==="load"?Nt.getInstance().loadRouters:Nt.getInstance().saveRouters).forEach(a=>{let s=a(e,n);s!==null&&r.push(s)}),r}},h9=e=>Nt.registerSaveRouter(e),d9=e=>Nt.registerLoadRouter(e),p9=e=>Nt.getSaveHandlers(e),f9=(e,t)=>Nt.getLoadHandlers(e,t),Dm="tensorflowjs",Om=1,Ks="models_store",Sa="model_info_store";function A5(){if(!Q().getBool("IS_BROWSER"))throw new Error("Failed to obtain IndexedDB factory because the current environmentis not a web browser.");let e=typeof window=="undefined"?self:window,t=e.indexedDB||e.mozIndexedDB||e.webkitIndexedDB||e.msIndexedDB||e.shimIndexedDB;if(t==null)throw new Error("The current browser does not appear to support IndexedDB.");return t}function zm(e){let t=e.result;t.createObjectStore(Ks,{keyPath:"modelPath"}),t.createObjectStore(Sa,{keyPath:"modelPath"})}var Zs=class{constructor(e){if(this.indexedDB=A5(),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(Dm,Om);a.onupgradeneeded=()=>zm(a),a.onsuccess=()=>{let s=a.result;if(t==null){let i=s.transaction(Ks,"readonly"),o=i.objectStore(Ks).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=ec(t),o=s.transaction(Sa,"readwrite"),l=o.objectStore(Sa),c=l.put({modelPath:this.modelPath,modelArtifactsInfo:i}),u;c.onsuccess=()=>{u=s.transaction(Ks,"readwrite");let h=u.objectStore(Ks).put({modelPath:this.modelPath,modelArtifacts:t,modelArtifactsInfo:i});h.onsuccess=()=>n({modelArtifactsInfo:i}),h.onerror=d=>{l=o.objectStore(Sa);let p=l.delete(this.modelPath);p.onsuccess=()=>(s.close(),r(h.error)),p.onerror=f=>(s.close(),r(h.error))}},c.onerror=h=>(s.close(),r(c.error)),o.oncomplete=()=>{u==null?s.close():u.oncomplete=()=>s.close()}}},a.onerror=s=>r(a.error)})}};Zs.URL_SCHEME="indexeddb://";var y5=e=>Q().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(Zs.URL_SCHEME)?m9(e.slice(Zs.URL_SCHEME.length)):null;Nt.registerSaveRouter(y5);Nt.registerLoadRouter(y5);function m9(e){return new Zs(e)}function A9(e){return e.startsWith(Zs.URL_SCHEME)?e.slice(Zs.URL_SCHEME.length):e}var y9=class{constructor(){this.indexedDB=A5()}async listModels(){return new Promise((e,t)=>{let n=this.indexedDB.open(Dm,Om);n.onupgradeneeded=()=>zm(n),n.onsuccess=()=>{let r=n.result,a=r.transaction(Sa,"readonly"),s=a.objectStore(Sa).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=A9(e),new Promise((t,n)=>{let r=this.indexedDB.open(Dm,Om);r.onupgradeneeded=()=>zm(r),r.onsuccess=()=>{let a=r.result,s=a.transaction(Sa,"readwrite"),i=s.objectStore(Sa),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 c=i.delete(e),u=()=>{l=a.transaction(Ks,"readwrite");let h=l.objectStore(Ks).delete(e);h.onsuccess=()=>t(o.result.modelArtifactsInfo),h.onerror=d=>n(o.error)};c.onsuccess=u,c.onerror=h=>(u(),a.close(),n(o.error))}},o.onerror=c=>(a.close(),n(o.error)),s.oncomplete=()=>{l==null?a.close():l.oncomplete=()=>a.close()}},r.onerror=a=>n(r.error)})}},na="/",al="tensorflowjs_models",g5="info",g9="model_topology",x9="weight_specs",w9="weight_data",_9="model_metadata";function x5(e){return{info:[al,e,g5].join(na),topology:[al,e,g9].join(na),weightSpecs:[al,e,x9].join(na),weightData:[al,e,w9].join(na),modelMetadata:[al,e,_9].join(na)}}function b9(e){let t=e.split(na);if(t.length<3)throw new Error(`Invalid key format: ${e}`);return t.slice(1,t.length-1).join(na)}function v9(e){return e.startsWith(Js.URL_SCHEME)?e.slice(Js.URL_SCHEME.length):e}var Js=class{constructor(e){if(!Q().getBool("IS_BROWSER")||typeof window=="undefined"||typeof window.localStorage=="undefined")throw new Error("The current environment does not support local storage.");if(this.LS=window.localStorage,e==null||!e)throw new Error("For local storage, modelPath must not be null, undefined or empty.");this.modelPath=e,this.keys=x5(this.modelPath)}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");{let t=JSON.stringify(e.modelTopology),n=JSON.stringify(e.weightSpecs),r=ec(e);try{this.LS.setItem(this.keys.info,JSON.stringify(r)),this.LS.setItem(this.keys.topology,t),this.LS.setItem(this.keys.weightSpecs,n),this.LS.setItem(this.keys.weightData,i9(e.weightData));let a={format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy};return e.signature!=null&&(a.signature=e.signature),e.userDefinedMetadata!=null&&(a.userDefinedMetadata=e.userDefinedMetadata),e.modelInitializer!=null&&(a.modelInitializer=e.modelInitializer),this.LS.setItem(this.keys.modelMetadata,JSON.stringify(a)),{modelArtifactsInfo:r}}catch(a){throw this.LS.removeItem(this.keys.info),this.LS.removeItem(this.keys.topology),this.LS.removeItem(this.keys.weightSpecs),this.LS.removeItem(this.keys.weightData),this.LS.removeItem(this.keys.modelMetadata),new Error(`Failed to save model '${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 '${this.modelPath}' are missing.`);return t.weightData=o9(s),t}};Js.URL_SCHEME="localstorage://";var w5=e=>Q().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(Js.URL_SCHEME)?k9(e.slice(Js.URL_SCHEME.length)):null;Nt.registerSaveRouter(w5);Nt.registerLoadRouter(w5);function k9(e){return new Js(e)}var I9=class{constructor(){M(Q().getBool("IS_BROWSER"),()=>"Current environment is not a web browser"),M(typeof window=="undefined"||typeof window.localStorage!="undefined",()=>"Current browser does not appear to support localStorage"),this.LS=window.localStorage}async listModels(){let e={},t=al+na,n=na+g5;for(let r=0;r<this.LS.length;++r){let a=this.LS.key(r);if(a.startsWith(t)&&a.endsWith(n)){let s=b9(a);e[s]=JSON.parse(this.LS.getItem(a))}}return e}async removeModel(e){e=v9(e);let t=x5(e);if(this.LS.getItem(t.info)==null)throw new Error(`Cannot find model at path '${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}},sl="://",Vn=class{constructor(){this.managers={}}static getInstance(){return Vn.instance==null&&(Vn.instance=new Vn),Vn.instance}static registerManager(e,t){M(e!=null,()=>"scheme must not be undefined or null."),e.endsWith(sl)&&(e=e.slice(0,e.indexOf(sl))),M(e.length>0,()=>"scheme must not be an empty string.");let n=Vn.getInstance();M(n.managers[e]==null,()=>`A model store manager is already registered for scheme '${e}'.`),n.managers[e]=t}static getManager(e){let t=this.getInstance().managers[e];if(t==null)throw new Error(`Cannot find model manager for scheme '${e}'`);return t}static getSchemes(){return Object.keys(this.getInstance().managers)}};function zd(e){if(e.indexOf(sl)===-1)throw new Error(`The url string provided does not contain a scheme. Supported schemes are: ${Vn.getSchemes().join(",")}`);return{scheme:e.split(sl)[0],path:e.split(sl)[1]}}async function _5(e,t,n=!1){M(e!==t,()=>`Old path and new path are the same: '${e}'`);let r=Nt.getLoadHandlers(e);M(r.length>0,()=>`Copying failed because no load handler is found for source URL ${e}.`),M(r.length<2,()=>`Copying failed because more than one (${r.length}) load handlers for source URL ${e}.`);let a=r[0],s=Nt.getSaveHandlers(t);M(s.length>0,()=>`Copying failed because no save handler is found for destination URL ${t}.`),M(s.length<2,()=>`Copying failed because more than one (${r.length}) save handlers for destination URL ${t}.`);let i=s[0],o=zd(e).scheme,l=zd(e).path,c=o===zd(e).scheme,u=await a.load();n&&c&&await Vn.getManager(o).removeModel(l);let h=await i.save(u);return n&&!c&&await Vn.getManager(o).removeModel(l),h.modelArtifactsInfo}async function N9(){let e=Vn.getSchemes(),t={};for(let n of e){let r=await Vn.getManager(n).listModels();for(let a in r){let s=n+sl+a;t[s]=r[a]}}return t}async function S9(e){let t=zd(e);return Vn.getManager(t.scheme).removeModel(t.path)}async function T9(e,t){return _5(e,t,!1)}async function E9(e,t){return _5(e,t,!0)}var C9=class{fetch(e,t){return fetch(e,t)}now(){return performance.now()}encode(e,t){if(t!=="utf-8"&&t!=="utf8")throw new Error(`Browser's encoder only supports utf-8, but got ${t}`);return this.textEncoder==null&&(this.textEncoder=new TextEncoder),this.textEncoder.encode(e)}decode(e,t){return new TextDecoder(t).decode(e)}};if(Q().get("IS_BROWSER")){Q().setPlatform("browser",new C9);try{Vn.registerManager(Js.URL_SCHEME,new I9)}catch(e){}try{Vn.registerManager(Zs.URL_SCHEME,new y9)}catch(e){}}var R9={importFetch:()=>M8()},Pm,F9=class{constructor(){this.util=require("util"),this.textEncoder=new this.util.TextEncoder}fetch(e,t){return Q().global.fetch!=null?Q().global.fetch(e,t):(Pm==null&&(Pm=R9.importFetch()),Pm(e,t))}now(){let e=process.hrtime();return e[0]*1e3+e[1]/1e6}encode(e,t){if(t!=="utf-8"&&t!=="utf8")throw new Error(`Node built-in encoder only supports utf-8, but got ${t}`);return this.textEncoder.encode(e)}decode(e,t){return e.length===0?"":new this.util.TextDecoder(t).decode(e)}};Q().get("IS_NODE")&&Q().setPlatform("node",new F9);function We(e,t="float32",n){return t=t||"float32",xm(e),new Mt(e,t,n)}function M9(e,t){let n=R(e,"x","cast");if(!Z0(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 z.runKernel(Qa,r,a)}var ye=L({cast_:M9});function $9(e){let t={x:R(e,"x","clone","string_or_numeric")};return z.runKernel(so,t)}var Nr=L({clone_:$9});function L2(e,t=!1){console.log(e.toString(t))}u5();var D9={buffer:We,cast:ye,clone:Nr,print:L2};qk(D9);var dn={};ze(dn,{browserFiles:()=>O9,browserHTTPRequest:()=>P9,concatenateArrayBuffers:()=>$m,copyModel:()=>T9,decodeWeights:()=>p5,encodeWeights:()=>a9,fromMemory:()=>L9,getLoadHandlers:()=>f9,getModelArtifactsInfoForJSON:()=>ec,getSaveHandlers:()=>p9,http:()=>Wm,isHTTPScheme:()=>Lm,listModels:()=>N9,loadWeights:()=>z9,moveModel:()=>E9,registerLoadRouter:()=>d9,registerSaveRouter:()=>h9,removeModel:()=>S9,weightsLoaderFactory:()=>b5,withSaveHandler:()=>W9});var B9="model",V9=".json",U9=".weights.bin";function v5(e){return new Promise(t=>setTimeout(t)).then(e)}var il=class{constructor(e){if(!Q().getBool("IS_BROWSER"))throw new Error("browserDownloads() cannot proceed because the current environment is not a browser.");e.startsWith(il.URL_SCHEME)&&(e=e.slice(il.URL_SCHEME.length)),(e==null||e.length===0)&&(e=B9),this.modelTopologyFileName=e+V9,this.weightDataFileName=e+U9}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 v5(()=>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 v5(()=>i.dispatchEvent(new MouseEvent("click")))}return{modelArtifactsInfo:ec(e)}}}};il.URL_SCHEME="downloads://";var H9=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 ${e.name}`));return}let c;try{c=this.checkManifestAndWeightFiles(l,t)}catch(p){r(p);return}let u=[],h=[],d=[];l.forEach(p=>{p.paths.forEach(f=>{h.push(f),d.push(null)}),u.push(...p.weights)}),l.forEach(p=>{p.paths.forEach(f=>{let m=new FileReader;m.onload=A=>{let y=A.target.result,g=h.indexOf(f);if(d[g]=y,d.indexOf(null)===-1){let w={modelTopology:o,weightSpecs:u,weightData:$m(d),format:i.format,generatedBy:i.generatedBy,convertedBy:i.convertedBy};i.signature!=null&&(w.signature=i.signature),i.userDefinedMetadata!=null&&(w.userDefinedMetadata=i.userDefinedMetadata),i.modelInitializer!=null&&(w.modelInitializer=i.modelInitializer),n(w)}},m.onerror=A=>r(`Failed to weights data from file of path '${f}'.`),m.readAsArrayBuffer(c[f])})})},a.onerror=s=>r(`Failed to read model topology and weights manifest JSON from file '${e.name}'. BrowserFiles supports loading Keras-style tf.Model artifacts only.`),a.readAsText(e)})}checkManifestAndWeightFiles(e,t){let n=[],r=t.map(s=>m5(s.name)),a={};for(let s of e)s.paths.forEach(i=>{let o=m5(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}},G9=e=>Q().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(il.URL_SCHEME)?j9(e.slice(il.URL_SCHEME.length)):null;Nt.registerSaveRouter(G9);function j9(e="model"){return new il(e)}function O9(e){return new H9(e)}function k5(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(c=>{let u=n+ ++a/e.length*(r-n);return t(u),c}),l);function i(l){M(l!=null&&Array.isArray(l)&&l.length>0,()=>"promises must be a none empty array")}function o(l,c){M(l>=0&&l<=1,()=>`Progress fraction must be in range [0, 1], but got startFraction ${l}`),M(c>=0&&c<=1,()=>`Progress fraction must be in range [0, 1], but got endFraction ${c}`),M(c>=l,()=>`startFraction must be no more than endFraction, but got startFraction ${l} and endFraction ${c}`)}return Promise.all(e.map(s))}async function I5(e,t){t==null&&(t={});let n=t.fetchFunc==null?Q().platform.fetch:t.fetchFunc,r=e.map(c=>n(c,t.requestInit,{isBinary:!0})),a=0,s=.5,i=(t.onProgress==null?await Promise.all(r):await k5(r,t.onProgress,a,s)).map(c=>c.arrayBuffer()),o=.5,l=1;return t.onProgress==null?await Promise.all(i):await k5(i,t.onProgress,o,l)}async function z9(e,t="",n,r){return b5(a=>I5(a,{requestInit:r}))(e,t,n)}function b5(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=Fm[y]*Dt(A.shape),w=()=>{a[f]=!0,s[f]==null&&(s[f]=[]),s[f].push({manifestEntry:A,groupOffset:m,sizeBytes:g})};r!=null?r.forEach((x,_)=>{x===A.name&&(w(),i[_]=!0)}):w(),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),[]),c=[];l.forEach(p=>{t[p].paths.forEach(f=>{let m=n+(n.endsWith("/")?"":"/")+f;c.push(m)})});let u=await e(c),h={},d=0;return l.forEach(p=>{let f=t[p].paths.length,m=0;for(let w=0;w<f;w++)m+=u[d+w].byteLength;let A=new ArrayBuffer(m),y=new Uint8Array(A),g=0;for(let w=0;w<f;w++){let x=new Uint8Array(u[d+w]);y.set(x,g),g+=x.byteLength}s[p].forEach(w=>{let x=A.slice(w.groupOffset,w.groupOffset+w.sizeBytes),_=p5(x,[w.manifestEntry]);for(let I in _)h[I]=_[I]}),d+=f}),h}}var q9="application/octet-stream",X9="application/json",Bm=class{constructor(e,t){if(this.DEFAULT_METHOD="POST",t==null&&(t={}),this.weightPathPrefix=t.weightPathPrefix,this.onProgress=t.onProgress,this.weightUrlConverter=t.weightUrlConverter,t.fetchFunc!=null?(M(typeof t.fetchFunc=="function",()=>"Must pass a function that matches the signature of `fetch` (see https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)"),this.fetch=t.fetchFunc):this.fetch=Q().platform.fetch,M(e!=null&&e.length>0,()=>"URL path for http must not be null, undefined or empty."),Array.isArray(e)&&M(e.length===2,()=>`URL paths for http must have a length of 2, (actual length is ${e.length}).`),this.path=e,t.requestInit!=null&&t.requestInit.body!=null)throw new Error("requestInit is expected to have no pre-existing body, but has one.");this.requestInit=t.requestInit||{}}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserHTTPRequest.save() does not support saving model topology in binary formats yet.");let t=Object.assign({method:this.DEFAULT_METHOD},this.requestInit);t.body=new FormData;let n=[{paths:["./model.weights.bin"],weights:e.weightSpecs}],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:X9}),"model.json"),e.weightData!=null&&t.body.append("model.weights.bin",new Blob([e.weightData],{type:q9}),"model.weights.bin");let a=await this.fetch(this.path,t);if(a.ok)return{modelArtifactsInfo:ec(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 ${this.path} contains neither model topology or manifest for weights.`);let c,u;r!=null&&([c,u]=await this.loadWeights(r));let h={modelTopology:n,weightSpecs:c,weightData:u,generatedBy:a,convertedBy:s,format:i};o!=null&&(h.signature=o),l!=null&&(h.userDefinedMetadata=l);let d=t.modelInitializer;return d&&(h.modelInitializer=d),h}async loadWeights(e){let t=Array.isArray(this.path)?this.path[1]:this.path,[n,r]=K9(t),a=this.weightPathPrefix||n,s=[];for(let c of e)s.push(...c.weights);let i=[],o=[];for(let c of e)for(let u of c.paths)this.weightUrlConverter!=null?o.push(this.weightUrlConverter(u)):i.push(a+u+r);this.weightUrlConverter&&i.push(...await Promise.all(o));let l=await I5(i,{requestInit:this.requestInit,fetchFunc:this.fetch,onProgress:this.onProgress});return[s,$m(l)]}};Bm.URL_SCHEME_REGEX=/^https?:\/\//;function K9(e){let t=e.lastIndexOf("/"),n=e.lastIndexOf("?"),r=e.substring(0,t),a=n>t?e.substring(n):"";return[r+"/",a]}function Lm(e){return e.match(Bm.URL_SCHEME_REGEX)!=null}var N5=(e,t)=>{if(typeof fetch=="undefined"&&(t==null||t.fetchFunc==null))return null;{let n=!0;if(Array.isArray(e)?n=e.every(r=>Lm(r)):n=Lm(e),n)return Wm(e,t)}return null};Nt.registerSaveRouter(N5);Nt.registerLoadRouter(N5);function Wm(e,t){return new Bm(e,t)}function P9(e,t){return Wm(e,t)}var Vm=class{constructor(e){this.modelArtifacts=e}async load(){return this.modelArtifacts}},Z9=class{constructor(e){this.saveHandler=e}async save(e){return this.saveHandler(e)}};function L9(e,t,n,r){return arguments.length===1?e.modelTopology!=null||e.weightSpecs!=null?new Vm(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 Vm({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 Vm({modelTopology:e,weightSpecs:t,weightData:n,trainingConfig:r}))}function W9(e){return new Z9(e)}var W2={};ze(W2,{confusionMatrix:()=>J9});function Y9(e,t,n=!1,r=!1){let a=R(e,"a","matMul"),s=R(t,"b","matMul");[a,s]=vt(a,s);let i={a,b:s},o={transposeA:n,transposeB:r};return z.runKernel(Ya,i,o)}var qe=L({matMul_:Y9});function Q9(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:R(e,"indices","oneHot","int32")},s={depth:t,onValue:n,offValue:r};return z.runKernel(ws,a,s)}var Wo=L({oneHot_:Q9});function eI(e,t){let n=R(e,"x","transpose");if(t==null&&(t=n.shape.map((s,i)=>i).reverse()),M(n.rank===t.length,()=>`Error in transpose: rank of input ${n.rank} must match length of perm ${t}.`),t.forEach(s=>{M(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 z.runKernel(Ps,r,a)}var at=L({transpose_:eI});function tI(e,t,n){let r=R(e,"labels","confusionMatrix"),a=R(t,"predictions","confusionMatrix");M(n==null||n>0&&Number.isInteger(n),()=>`If provided, numClasses must be a positive integer, but got ${n}`),M(r.rank===1,()=>`Expected the rank of labels to be 1, but got ${r.rank}`),M(a.rank===1,()=>`Expected the rank of predictions to be 1, but got ${a.rank}`),M(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.`),M(n>0&&Number.isInteger(n),()=>`numClasses is required to be a positive integer, but got ${n}`);let s=Wo(ye(r,"int32"),n),i=Wo(ye(a,"int32"),n),o=at(s),l=qe(o,i);return ye(l,"int32")}var J9=L({confusionMatrix_:tI}),ku={};ze(ku,{fromPixels:()=>rI,toPixels:()=>nI});function Sf(e,t,n){if(qs(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 Na(e,t,r,n)}var ol;function aI(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(Uh(Vh,z.backendName)!=null){let d={pixels:e},p={numChannels:t};return z.runKernel(Vh,d,p)}let[l,c]=a?[e.videoWidth,e.videoHeight]:[e.width,e.height],u;i?u=e.getContext("2d").getImageData(0,0,l,c).data:r||n?u=e.data:(s||a||o)&&(ol==null&&(ol=document.createElement("canvas").getContext("2d")),ol.canvas.width=l,ol.canvas.height=c,ol.drawImage(e,0,0,l,c),u=ol.getImageData(0,0,l,c).data);let h;if(t===4)h=new Int32Array(u);else{let d=l*c;h=new Int32Array(d*t);for(let p=0;p<d;p++)for(let f=0;f<t;++f)h[p*t+f]=u[p*4+f]}return Sf(h,[c,l,t],"int32")}async function nI(e,t){let n=R(e,"img","toPixels");if(!(e instanceof Qe)){let c=n;n=ye(c,"int32"),c.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 c=0;c<r*a;++c){let u=[0,0,0,255];for(let d=0;d<s;d++){let p=i[c*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?(u[0]=p*o,u[1]=p*o,u[2]=p*o):u[d]=p*o}let h=c*4;l[h+0]=Math.round(u[0]),l[h+1]=Math.round(u[1]),l[h+2]=Math.round(u[2]),l[h+3]=Math.round(u[3])}if(t!=null){t.width=a,t.height=r;let c=t.getContext("2d"),u=new ImageData(l,a,r);c.putImageData(u,0,0)}return n!==e&&n.dispose(),l}var rI=L({fromPixels_:aI}),Tf={};ze(Tf,{prepareAndValidate:()=>S5});function S5(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(Dt(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 c=1;for(let h=s;h<n;++h)c*=o[h],l.push(o[h]);let u=[...el(e.shape).map(h=>h/c),1].slice(0,s);return[l,i,c,u]}var Ef={};ze(Ef,{calculateShapes:()=>T5,validateInput:()=>Hm,validateUpdateShape:()=>Um});function Um(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 Hm(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}`)}Um(n,t,e)}function T5(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=Dt(t.shape)/o,c=[...el(n.slice(0,a)),1],u=Dt(n);return{sliceRank:a,numUpdates:l,sliceSize:i,strides:c,outputSize:u}}var rn={};ze(rn,{assertParamsValid:()=>sI,computeFlatOffset:()=>oI,computeOutShape:()=>E5,getNormalizedAxes:()=>R5,isSliceContinous:()=>iI,maskToAxes:()=>Pd,parseSliceParams:()=>z5,sliceInfo:()=>lI,startForAxis:()=>D5,startIndicesWithElidedDims:()=>F5,stopForAxis:()=>O5,stopIndicesWithElidedDims:()=>M5,stridesForAxis:()=>$5,stridesWithElidedDims:()=>C5});function sI(e,t,n){let r=e.shape.length;M(r===t.length,()=>`Error in slice${r}D: Length of begin ${t} must match the rank of the array (${r}).`),M(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)M(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 Pd(e){let t=[],n=0;for(;e>0;)e&1&&t.push(n),e/=2,n++;return t}function E5(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 C5(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 P5(e,t,n){return n<=e?n:n-(t-1)}function L5(e,t){let n=[];for(let r=0;r<e;r++)n.push(t+r);return n}function R5(e,t,n,r,a,s,i,o,l){let c=e.length,u=new Array(c),h=new Array(c),d=new Array(c);if(t.length&&n>0){let p=t[0],f=n+1;u=F5(i,p,f,r,e),h=M5(o,p,f,a,e),d=C5(s,p,f,e)}else for(let p=0;p<c;p++)u[p]=D5(i,r,s,e,p,l),h[p]=O5(o,a,s,e,p,l),d[p]=$5(s,p,l);return{begin:u,end:h,strides:d}}function F5(e,t,n,r,a){let s=[...a],i=L5(n,t);for(let o=0;o<s.length;o++)if(i.indexOf(o)>-1)s[o]=0;else{let l=P5(t,n,o),c=r[l];e&1<<l&&(c=0),s[o]=c}return s}function M5(e,t,n,r,a){let s=[...a],i=L5(n,t);for(let o=0;o<s.length;o++)if(i.indexOf(o)>-1)s[o]=Number.MAX_SAFE_INTEGER;else{let l=P5(t,n,o),c=r[l];e&1<<l&&(c=Number.MAX_SAFE_INTEGER),s[o]=c}for(let o=0;o<s.length;o++){let l=a[o];s[o]<0&&(s[o]+=l),s[o]=ju(0,s[o],a[o])}return s}function $5(e,t,n){let r=e[t];return(n&1<<t||r==null)&&(r=1),r}function D5(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=ju(0,i,l-1),i}function O5(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=ju(0,i,l):i=ju(-1,i,l-1),i}function iI(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 oI(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=>{M(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:(M(i===-1,()=>`Negative size values should be exactly -1 but got ${i} for the slice() size at index ${o}.`),e.shape[o]-r[o])),[r,s]}function lI(e,t,n,r,a,s,i,o,l){let c=t.slice(),u=n.slice(),h=r;r==null&&(h=new Array(c.length));let d=Pd(i);if(d.length>1)throw new Error("Multiple ellipses in slice is not allowed.");if(i!==0&&o!==0)throw new Error("Using both ellipsisMask and newAxisMask is not yet supported.");if(i!==0&&l!==0)throw new Error("Using both ellipsisMask and shrinkAxisMask is not yet supported.");let p=e.length-c.length,f=Pd(o),m=e.slice();f.forEach(I=>{c[I]=0,u[I]=1,m.splice(I,0,1)});let{begin:A,end:y,strides:g}=R5(m,d,p,c,u,h,a,s,i);c=A,u=y,h=g;let w=Pd(l);w.forEach(I=>{u[I]=c[I]+1,h[I]=1});let x=E5(c,u,h),_=x.filter((I,T)=>w.indexOf(T)===-1);return{nonStrided:h.every(I=>I===1),$begin:c,$end:u,$strides:h,size:x,newShape:m,outShape:_}}var re={};ze(re,{Serializable:()=>W5,SerializationMap:()=>Ys,registerClass:()=>Ta});var W5=class{getClassName(){return this.constructor.className}static fromConfig(e,t){return new e(t)}},Ys=class{constructor(){this.classNameMap={}}static getMap(){return Ys.instance==null&&(Ys.instance=new Ys),Ys.instance}static register(e){Ys.getMap().classNameMap[e.className]=[e,e.fromConfig]}};function Ta(e){M(e.className!=null,()=>"Class being registered does not have the static className property defined."),M(typeof e.className=="string",()=>"className is required to be a string, but got type "+typeof e.className),M(e.className.length>0,()=>"Class being registered has an empty-string as its className, which is disallowed."),Ys.register(e)}var B2={};ze(B2,{TEST_EPSILON_FLOAT16:()=>B5,encodeStrings:()=>V5,expectArrayBuffersEqual:()=>fI,expectArraysClose:()=>uI,expectArraysEqual:()=>hI,expectNumbersClose:()=>dI,expectPromiseToFail:()=>cI,expectValuesInRange:()=>pI,testEpsilon:()=>jm});var mI=.001,B5=.1;function uI(e,t,n){return n==null&&(n=jm()),Gm(e,t,(r,a)=>qm(r,a,n))}function jm(){return z.backend.floatPrecision()===32?mI:B5}function Gm(e,t,n){let r=!0;if((tn(e)||tn(t))&&(r=!1),tn(e)&&tn(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: ${o}`)}if(Array.isArray(e)&&Array.isArray(t)){let i=Or(e),o=Or(t);if(!ta(i,o))throw new Error(`Arrays have different shapes. Actual: [${i}]. Expected: [${o}]`)}let a=tn(e)?e:Xs(e),s=tn(t)?t:Xs(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 cI(e,t){e().then(()=>t.fail(),()=>t())}function hI(e,t){let n=typeof t=="string"||typeof t=="number"||typeof t=="boolean"?[t]:t;return ka(e)||ka(e[0])||ka(t)||ka(t[0])?Gm(e,n,(r,a)=>r==a):Gm(e,t,(r,a)=>qm(r,a,0))}function dI(e,t,n){if(n==null&&(n=jm()),!qm(e,t,n))throw new Error(`Numbers differ: actual === ${e}, expected === ${t}`)}function qm(e,t,n){return!isFinite(e)&&!isFinite(t)?!0:!(isNaN(e)||isNaN(t)||Math.abs(e-t)>n)}function pI(e,t,n){for(let r=0;r<e.length;r++)if(e[r]<t||e[r]>n)throw new Error(`Value out of range:${e[r]} low: ${t}, high: ${n}`)}function fI(e,t){expect(new Float32Array(e)).toEqual(new Float32Array(t))}function V5(e){for(let t=0;t<e.length;t++){let n=e[t];Array.isArray(n)?V5(n):e[t]=Xu(n)}return e}var V2="3.0.0";function U2(){Q().set("PROD",!0)}function $4(){Q().set("DEBUG",!0)}function D4(){Q().set("DEPRECATION_WARNINGS_ENABLED",!1),console.warn("TensorFlow.js deprecation warnings have been disabled.")}function Cf(e){Q().getBool("DEPRECATION_WARNINGS_ENABLED")&&console.warn(e+" You can disable deprecation warnings with tf.disableDeprecationWarnings().")}Xk(Cf);function O4(){z.disposeVariables()}function Ln(){return z}function Gh(){return z.memory()}function Bo(e){return z.profile(e)}function U(e,t){return z.tidy(e,t)}function Ce(e){Nm(e).forEach(t=>t.dispose())}function Bt(e){return z.keep(e)}function z4(e){return z.time(e)}function H2(e){return z.setBackend(e)}function j2(){return z.ready()}function qh(){return z.backendName}function P4(e){z.removeBackend(e)}function G2(e){return z.findBackend(e)}function L4(e){return z.findBackendFactory(e)}function Iu(e,t,n=1){return z.registerBackend(e,t,n)}function Rf(){return z.backend}function W4(e,t){Q().setPlatform(e,t)}function AI(e,t){let n=R(e,"a","add"),r=R(t,"b","add");[n,r]=vt(n,r);let a={a:n,b:r};return z.runKernel(fa,a)}var oe=L({add_:AI});function yI(e,t){let n=R(e,"a","floorDiv"),r=R(t,"b","floorDiv");[n,r]=vt(n,r);let a={a:n,b:r};return z.runKernel(ls,a)}var Xh=L({floorDiv_:yI});function gI(e,t){let n=R(e,"a","div"),r=R(t,"b","div");if([n,r]=vt(n,r),n.dtype==="int32"&&r.dtype==="int32")return Xh(n,r);let a={a:n,b:r},s={};return z.runKernel(ss,a,s)}var Ne=L({div_:gI});function xI(e,t){let n=R(e,"a","mul"),r=R(t,"b","mul");[n,r]=vt(n,r);let a={a:n,b:r};return z.runKernel(xs,a)}var W=L({mul_:xI});function wI(e){let t=R(e,"x","abs");if(t.dtype==="complex64"){let n={x:t};return z.runKernel(lu,n)}else{let n={x:t};return z.runKernel(zi,n)}}var $t=L({abs_:wI});function _I(e){let t={x:R(e,"x","acos")};return z.runKernel(Pi,t)}var Ff=L({acos_:_I});function bI(e){let t={x:R(e,"x","acosh")};return z.runKernel(Li,t)}var Mf=L({acosh_:bI});function vI(e){M(Array.isArray(e),()=>"The argument passed to tf.addN() must be a list of tensors"),M(e.length>=1,()=>`Must pass at least one tensor to tf.addN(), but got ${e.length}`);let t=e.map((a,s)=>R(a,`tensors${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(!ta(a.shape,n.shape))throw new Error("All tensors passed to tf.addN() must have the same shape")});let r=t;return z.runKernel(Ka,r)}var Kh=L({addN_:vI});function kI(e,t=null,n=!1){let r={x:R(e,"x","all","bool")},a={axis:t,keepDims:n};return z.runKernel(dh,r,a)}var Zh=L({all_:kI});function II(e,t=null,n=!1){let r={x:R(e,"x","any","bool")},a={axis:t,keepDims:n};return z.runKernel(ph,r,a)}var Nu=L({any_:II});function NI(e,t=0){let n={x:R(e,"x","argMax")},r={axis:t};return z.runKernel(Za,n,r)}var Su=L({argMax_:NI});function SI(e,t=0){let n={x:R(e,"x","argMin")},r={axis:t};return z.runKernel(su,n,r)}var $f=L({argMin_:SI});function TI(e){let t={x:R(e,"x","asin")};return z.runKernel(Wi,t)}var Df=L({asin_:TI});function EI(e){let t={x:R(e,"x","asinh")};return z.runKernel(Bi,t)}var Of=L({asinh_:EI});function CI(e){let t={x:R(e,"x","atan")};return z.runKernel(Vi,t)}var zf=L({atan_:CI});function RI(e,t){let n=R(e,"a","atan2"),r=R(t,"b","atan2");[n,r]=vt(n,r);let a={a:n,b:r};return z.runKernel(Hi,a)}var Pf=L({atan2_:RI});function FI(e){let t={x:R(e,"x","atanh")};return z.runKernel(Ui,t)}var Lf=L({atanh_:FI});function MI(e,t,n,r,a="NHWC",s){let i=e[3],o=[...t,i],l=U5(a);return tc(e,o,n,s,r,null,null,l)}function H5(e,t,n,r,a,s,i="channelsLast"){let[o,l]=Ld(t),c;if(i==="channelsLast")c=[o,l,e[3],e[3]];else if(i==="channelsFirst")c=[o,l,e[1],e[1]];else throw new Error(`Unknown dataFormat ${i}`);return tc(e,c,n,r,a,s,!1,i)}function $I(e,t,n,r,a,s,i="NDHWC"){let[o,l,c]=Xm(t),u,h;if(i==="NDHWC")h="channelsLast",u=[o,l,c,e[4],e[4]];else if(i==="NCDHW")h="channelsFirst",u=[o,l,c,e[1],e[1]];else throw new Error(`Unknown dataFormat ${i}`);return j5(e,u,n,r,a,!1,h,s)}function tc(e,t,n,r,a,s,i=!1,o="channelsLast"){let[l,c,u,h]=[-1,-1,-1,-1];if(o==="channelsLast")[l,c,u,h]=e;else if(o==="channelsFirst")[l,h,c,u]=e;else throw new Error(`Unknown dataFormat ${o}`);let[d,p,,f]=t,[m,A]=Ld(n),[y,g]=Ld(r),w=ll(d,y),x=ll(p,g),{padInfo:_,outHeight:I,outWidth:T}=DI(a,c,u,m,A,w,x,s,o),E=i?f*h:f,N;return o==="channelsFirst"?N=[l,E,I,T]:o==="channelsLast"&&(N=[l,I,T,E]),{batchSize:l,dataFormat:o,inHeight:c,inWidth:u,inChannels:h,outHeight:I,outWidth:T,outChannels:E,padInfo:_,strideHeight:m,strideWidth:A,filterHeight:d,filterWidth:p,effectiveFilterHeight:w,effectiveFilterWidth:x,dilationHeight:y,dilationWidth:g,inShape:e,outShape:N,filterShape:t}}function j5(e,t,n,r,a,s=!1,i="channelsLast",o){let[l,c,u,h,d]=[-1,-1,-1,-1,-1];if(i==="channelsLast")[l,c,u,h,d]=e;else if(i==="channelsFirst")[l,d,c,u,h]=e;else throw new Error(`Unknown dataFormat ${i}`);let[p,f,m,,A]=t,[y,g,w]=Xm(n),[x,_,I]=Xm(r),T=ll(p,x),E=ll(f,_),N=ll(m,I),{padInfo:F,outDepth:$,outHeight:D,outWidth:P}=OI(a,c,u,h,y,g,w,T,E,N,o),H=s?A*d:A,V;return i==="channelsFirst"?V=[l,H,$,D,P]:i==="channelsLast"&&(V=[l,$,D,P,H]),{batchSize:l,dataFormat:i,inDepth:c,inHeight:u,inWidth:h,inChannels:d,outDepth:$,outHeight:D,outWidth:P,outChannels:H,padInfo:F,strideDepth:y,strideHeight:g,strideWidth:w,filterDepth:p,filterHeight:f,filterWidth:m,effectiveFilterDepth:T,effectiveFilterHeight:E,effectiveFilterWidth:N,dilationDepth:x,dilationHeight:_,dilationWidth:I,inShape:e,outShape:V,filterShape:t}}function zI(e,t,n,r,a){r==null&&(r=Km(e,t,n));let s=e[0],i=e[1],o=Qs((s-t+2*r)/n+1,a),l=Qs((i-t+2*r)/n+1,a);return[o,l]}function PI(e,t,n,r,a,s){a==null&&(a=Km(e,t,r));let i=e[0],o=e[1],l=e[2],c=Qs((i-t+2*a)/r+1,s),u=Qs((o-t+2*a)/r+1,s),h=Qs((l-t+2*a)/r+1,s);return[c,u,h,n]}function Km(e,t,n,r=1){let a=ll(t,r);return Math.floor((e[0]*(n-1)-n+a)/2)}function Ld(e){return typeof e=="number"?[e,e,e]:e.length===2?[e[0],e[1],1]:e}function Xm(e){return typeof e=="number"?[e,e,e]:e}function ll(e,t){return t<=1?e:e+(e-1)*(t-1)}function DI(e,t,n,r,a,s,i,o,l){let c,u,h;if(typeof e=="number"){c={top:e,bottom:e,left:e,right:e,type:e===0?"VALID":"NUMBER"};let d=zI([t,n],s,r,e,o);u=d[0],h=d[1]}else if(e==="same"){u=Math.ceil(t/r),h=Math.ceil(n/a);let d=Math.max(0,(u-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;c={top:f,bottom:m,left:A,right:y,type:"SAME"}}else if(e==="valid")c={top:0,bottom:0,left:0,right:0,type:"VALID"},u=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];c={top:d,bottom:p,left:f,right:m,type:d===0&&p===0&&f===0&&m===0?"VALID":"EXPLICIT"},u=Qs((t-s+d+p)/r+1,o),h=Qs((n-i+f+m)/a+1,o)}else throw Error(`Unknown padding parameter: ${e}`);return{padInfo:c,outHeight:u,outWidth:h}}function OI(e,t,n,r,a,s,i,o,l,c,u){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=PI([t,n,r,1],o,1,a,e,u);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+c-r,g=Math.floor(m/2),w=m-g,x=Math.floor(A/2),_=A-x,I=Math.floor(y/2),T=y-I;h={top:x,bottom:_,left:I,right:T,front:g,back:w,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-c+1)/i);else throw Error(`Unknown padding parameter: ${e}`);return{padInfo:h,outDepth:d,outHeight:p,outWidth:f}}function Qs(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 Ea(e){let[t,n,r]=Ld(e);return t===1&&n===1&&r===1}function zr(e,t){return Ea(e)||Ea(t)}function U5(e){if(e==="NHWC")return"channelsLast";if(e==="NCHW")return"channelsFirst";throw new Error(`Unknown dataFormat ${e}`)}function LI(e,t){let n={x:R(e,"x","reshape","string_or_numeric")},r={shape:t};return z.runKernel(ko,n,r)}var q=L({reshape_:LI});function WI(e,t,n,r,a){let s=R(e,"x","avgPool","float32"),i=1;M(zr(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=q(s,[1,s.shape[0],s.shape[1],s.shape[2]])),M(o.rank===4,()=>`Error in avgPool: x must be rank 4 but got rank ${o.rank}.`),a!=null&&M(Ut(r),()=>`Error in avgPool: pad must be an integer when using, dimRoundingMode ${a} but got pad ${r}.`);let c={x:o},u={filterSize:t,strides:n,pad:r,dimRoundingMode:a},h=z.runKernel(Ja,c,u);return h=ye(h,s.dtype),l?q(h,[h.shape[1],h.shape[2],h.shape[3]]):h}var Tu=L({avgPool_:WI});function BI(e,t,n,r,a,s="NDHWC"){let i=R(e,"x","avgPool3d","float32"),o=i,l=!1;i.rank===4&&(l=!0,o=q(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),M(o.rank===5,()=>`Error in avgPool3d: x must be rank 5 but got rank ${o.rank}.`),M(s==="NDHWC",()=>`Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of ${s}`),a!=null&&M(Ut(r),()=>`Error in avgPool3d: pad must be an integer when using, dimRoundingMode ${a} but got pad ${r}.`);let c={x:o},u={filterSize:t,strides:n,pad:r,dimRoundingMode:a,dataFormat:s},h=z.runKernel(iu,c,u);return h=ye(h,o.dtype),l?q(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}var Wf=L({avgPool3d_:BI});function VI(e,t=0){M(e.length>=1,()=>"Pass at least one tensor to concat");let n=Qu(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 Nr(n[0]);let r=n,a={axis:t};return z.runKernel(Gi,r,a)}var ct=L({concat_:VI});function UI(e){let t={x:R(e,"x","sigmoid")};return z.runKernel(Rs,t)}var er=L({sigmoid_:UI});function HI(e,t,n){let r=R(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 z.runKernel(To,a,s)}var Me=L({slice_:HI});function jI(e){let t={x:R(e,"x","tanh")};return z.runKernel(zs,t)}var Vo=L({tanh_:jI});function GI(e,t,n,r,a,s){let i=R(e,"forgetBias","basicLSTMCell"),o=R(t,"lstmKernel","basicLSTMCell"),l=R(n,"lstmBias","basicLSTMCell"),c=R(r,"data","basicLSTMCell"),u=R(a,"c","basicLSTMCell"),h=R(s,"h","basicLSTMCell"),d=ct([c,h],1),p=qe(d,o),f=oe(p,l),m=f.shape[0],A=f.shape[1]/4,y=[m,A],g=Me(f,[0,0],y),w=Me(f,[0,A],y),x=Me(f,[0,A*2],y),_=Me(f,[0,A*3],y),I=oe(W(er(g),Vo(w)),W(u,er(oe(i,x)))),T=W(Vo(I),er(_));return[I,T]}var B4=L({basicLSTMCell_:GI});function qI(e,t,n){let r=R(e,"x","batchToSpaceND"),a=t.reduce((o,l)=>o*l);M(r.rank>=1+t.length,()=>`input rank is ${r.rank} but should be > than blockShape.length ${t.length}`),M(n.length===t.length,()=>`crops.length is ${n.length} but should be equal to blockShape.length ${t.length}`),M(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 z.runKernel(ou,s,i)}var Eu=L({batchToSpaceND_:qI});function XI(e){let t;return e.rank===0||e.rank===1?t=q(e,[1,1,1,e.size]):e.rank===2?t=q(e,[1,1,e.shape[0],e.shape[1]]):e.rank===3?t=q(e,[1,e.shape[0],e.shape[1],e.shape[2]]):t=e,t}function KI(e,t,n,r,a,s){s==null&&(s=.001);let i=R(e,"x","batchNorm"),o=R(t,"mean","batchNorm"),l=R(n,"variance","batchNorm"),c;a!=null&&(c=R(a,"scale","batchNorm"));let u;r!=null&&(u=R(r,"offset","batchNorm")),M(o.rank===l.rank,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),M(u==null||o.rank===u.rank,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),M(c==null||o.rank===c.rank,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let h={x:XI(i),scale:c,offset:u,mean:o,variance:l},d={varianceEpsilon:s},p=z.runKernel(us,h,d);return q(p,i.shape)}var Vs=L({batchNorm_:KI});function ZI(e,t,n,r,a,s){let i=R(e,"x","batchNorm"),o=R(t,"mean","batchNorm"),l=R(n,"variance","batchNorm"),c;a!=null&&(c=R(a,"scale","batchNorm"));let u;return r!=null&&(u=R(r,"offset","batchNorm")),M(i.rank===2,()=>`Error in batchNorm2D: x must be rank 2 but got rank ${i.rank}.`),M(o.rank===2||o.rank===1,()=>`Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank ${o.rank}.`),M(l.rank===2||l.rank===1,()=>`Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank ${l.rank}.`),c!=null&&M(c.rank===2||c.rank===1,()=>`Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank ${c.rank}.`),u!=null&&M(u.rank===2||u.rank===1,()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${u.rank}.`),Vs(i,o,l,u,c,s)}var q2=L({batchNorm2d_:ZI});function JI(e,t,n,r,a,s){let i=R(e,"x","batchNorm"),o=R(t,"mean","batchNorm"),l=R(n,"variance","batchNorm"),c;a!=null&&(c=R(a,"scale","batchNorm"));let u;return r!=null&&(u=R(r,"offset","batchNorm")),M(i.rank===3,()=>`Error in batchNorm3D: x must be rank 3 but got rank ${i.rank}.`),M(o.rank===3||o.rank===1,()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${o.rank}.`),M(l.rank===3||l.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${l.rank}.`),c!=null&&M(c.rank===3||c.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${c.rank}.`),u!=null&&M(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${u.rank}.`),Vs(i,o,l,u,c,s)}var X2=L({batchNorm3d_:JI});function YI(e,t,n,r,a,s){let i=R(e,"x","batchNorm"),o=R(t,"mean","batchNorm"),l=R(n,"variance","batchNorm"),c;a!=null&&(c=R(a,"scale","batchNorm"));let u;return r!=null&&(u=R(r,"offset","batchNorm")),M(i.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${i.rank}.`),M(o.rank===4||o.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${o.rank}.`),M(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${l.rank}.`),c!=null&&M(c.rank===4||c.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${c.rank}.`),u!=null&&M(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${u.rank}.`),Vs(i,o,l,u,c,s)}var K2=L({batchNorm4d_:YI});function QI(e,t,n){let r=R(e,"x","bincount"),a=R(t,"weights","bincount");M(r.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${r.dtype}`),M(n>=0,()=>`size must be non-negative, but got ${n}.`),M(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: ${a.shape}.`);let s={x:r,weights:a},i={size:n};return z.runKernel(Ah,s,i)}var Z2=L({bincount_:QI});function eN(e,t){let n=R(e,"broadcastTo","x"),r=n.shape;if(t.some(l=>!(l>0)||l%1!=0))throw new Error(`broadcastTo(): Invalid broadcast shape [${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=q(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,c)=>l>1?c:-1).filter(l=>l>=0).length===0)return Nr(n);let i={x:n},o={reps:s};return z.runKernel(Aa,i,o)}var Cu=L({broadcastTo_:eN});function tN(e){let t={x:R(e,"x","ceil")};return z.runKernel(ji,t)}var Bf=L({ceil_:tN});function nN(e,t,n){let r=R(e,"x","clipByValue");M(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 z.runKernel(ma,a,s)}var pn=L({clipByValue_:nN});function rN(e){return ct(e,0)}var J2=L({concat1d_:rN});function aN(e,t){return ct(e,t)}var Jh=L({concat2d_:aN});function sN(e,t){return ct(e,t)}var Y2=L({concat3d_:sN});function iN(e,t){return ct(e,t)}var Q2=L({concat4d_:iN});function oN(e,t,n,r,a="NHWC",s=[1,1],i){let o=R(e,"x","conv2d"),l=R(t,"filter","conv2d"),c=o,u=!1;o.rank===3&&(u=!0,c=q(o,[1,o.shape[0],o.shape[1],o.shape[2]])),M(c.rank===4,()=>`Error in conv2d: input must be rank 4, but got rank ${c.rank}.`),M(l.rank===4,()=>`Error in conv2d: filter must be rank 4, but got rank ${l.rank}.`),i!=null&&M(Ut(r),()=>`Error in conv2d: pad must be an integer when using, dimRoundingMode ${i} but got pad ${r}.`);let h=a==="NHWC"?c.shape[3]:c.shape[1];M(h===l.shape[2],()=>`Error in conv2d: depth of input (${h}) must match input depth for filter ${l.shape[2]}.`),M(zr(n,s),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${s}'`);let d={x:c,filter:l},p={strides:n,pad:r,dataFormat:a,dilations:s,dimRoundingMode:i},f=z.runKernel(es,d,p);return u?q(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var Zr=L({conv2d_:oN});function lN(e,t,n,r,a="NWC",s=1,i){let o=R(e,"x","conv1d"),l=R(t,"filter","conv1d"),c=o,u=!1;o.rank===2&&(u=!0,c=q(o,[1,o.shape[0],o.shape[1]])),M(c.rank===3,()=>`Error in conv1d: input must be rank 3, but got rank ${c.rank}.`),M(l.rank===3,()=>`Error in conv1d: filter must be rank 3, but got rank ${l.rank}.`),i!=null&&M(Ut(r),()=>`Error in conv1d: pad must be an integer when using, dimRoundingMode ${i} but got pad ${r}.`),M(c.shape[2]===l.shape[1],()=>`Error in conv1d: depth of input (${c.shape[2]}) must match input depth for filter ${l.shape[1]}.`),M(zr(n,s),()=>`Error in conv1D: Either stride or dilation must be 1. Got stride ${n} and dilation '${s}'`),M(a==="NWC",()=>`Error in conv1d: got dataFormat of ${a} but only NWC is currently supported.`);let h=q(l,[1,l.shape[0],l.shape[1],l.shape[2]]),d=q(c,[c.shape[0],1,c.shape[1],c.shape[2]]),p=Zr(d,h,[1,n],r,"NHWC",[1,s],i);return u?q(p,[p.shape[2],p.shape[3]]):q(p,[p.shape[0],p.shape[2],p.shape[3]])}var Yh=L({conv1d_:lN});function uN(e,t,n,r,a,s="NHWC",i){M(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let o=e,l=t,c=!1;t.rank===3&&(c=!0,l=q(t,[1,t.shape[0],t.shape[1],t.shape[2]]),o=[1,e[0],e[1],e[2]]),M(o.length===4,()=>`Error in conv2dDerInput: inShape must be length 4, but got length ${o.length}.`),M(l.rank===4,()=>`Error in conv2dDerInput: dy must be rank 4, but got rank ${l.rank}`),M(n.rank===4,()=>`Error in conv2dDerInput: filter must be rank 4, but got rank ${n.rank}`);let u=s==="NHWC"?o[3]:o[1],h=s==="NHWC"?l.shape[3]:l.shape[1];M(u===n.shape[2],()=>`Error in conv2dDerInput: depth of input (${u}) must match input depth for filter ${n.shape[2]}.`),M(h===n.shape[3],()=>`Error in conv2dDerInput: depth of output (${h}) must match output depth for filter ${n.shape[3]}.`),i!=null&&M(Ut(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=z.runKernel(ts,d,p);return c?q(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var Zm=L({conv2DBackpropInput_:uN});function cN(e,t,n,r,a,s){let i=R(e,"x","conv2dTranspose"),o=R(t,"filter","conv2dTranspose");return Zm(n,i,o,r,a,"NHWC",s)}var Qh=L({conv2dTranspose_:cN});function hN(e,t,n,r,a="NDHWC",s=[1,1,1]){let i=R(e,"x","conv3d"),o=R(t,"filter","conv3d"),l=i,c=!1;i.rank===4&&(c=!0,l=q(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),M(l.rank===5,()=>`Error in conv3d: input must be rank 5, but got rank ${l.rank}.`),M(o.rank===5,()=>`Error in conv3d: filter must be rank 5, but got rank ${o.rank}.`),M(l.shape[4]===o.shape[3],()=>`Error in conv3d: depth of input (${l.shape[4]}) must match input depth for filter ${o.shape[3]}.`),M(zr(n,s),()=>`Error in conv3D: Either strides or dilations must be 1. Got strides ${n} and dilations '${s}'`),M(a==="NDHWC",()=>`Error in conv3d: got dataFormat of ${a} but only NDHWC is currently supported.`);let u={x:l,filter:o},h={strides:n,pad:r,dataFormat:a,dilations:s},d=z.runKernel(uu,u,h);return c?q(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var Vf=L({conv3d_:hN});function dN(e,t,n,r,a){M(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let s=e,i=t,o=!1;t.rank===4&&(o=!0,i=q(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]]),s=[1,e[0],e[1],e[2],e[3]]);let l=s[4],c=i.shape[4];M(s.length===5,()=>`Error in conv3dDerInput: inShape must be length 5, but got length ${s.length}.`),M(i.rank===5,()=>`Error in conv3dDerInput: dy must be rank 5, but got rank ${i.rank}`),M(n.rank===5,()=>`Error in conv3dDerInput: filter must be rank 5, but got rank ${n.rank}`),M(l===n.shape[3],()=>`Error in conv3dDerInput: depth of input (${l}) must match input depth for filter ${n.shape[3]}.`),M(c===n.shape[4],()=>`Error in conv3dDerInput: depth of output (${c}) must match output depth for filter ${n.shape[4]}.`);let u={dy:i,filter:n},h={pad:a,strides:r,inputShape:s},d=z.runKernel(wh,u,h);return o?q(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var G5=L({conv3DBackpropInput_:dN});function pN(e,t,n,r,a){let s=R(e,"x","conv3dTranspose"),i=R(t,"filter","conv3dTranspose");return G5(n,s,i,r,a)}var V4=L({conv3dTranspose_:pN});function fN(e){let t={x:R(e,"x","cos")};return z.runKernel(ns,t)}var Ru=L({cos_:fN});function mN(e){let t={x:R(e,"x","cosh")};return z.runKernel(qi,t)}var ed=L({cosh_:mN});function AN(e,t=0,n=!1,r=!1){let a={x:R(e,"x","cumsum")},s={axis:t,exclusive:n,reverse:r};return z.runKernel(rs,a,s)}var td=L({cumsum_:AN});function yN(e,t,n,r=!1){let a=R(e,"x","denseBincount"),s=R(t,"weights","denseBincount");M(a.dtype==="int32",()=>`Error in denseBincount: input dtype must be int32, but got ${a.dtype}`),M(a.rank<=2,()=>`Error in denseBincount: input must be at most rank 2, but got rank ${a.rank}.`),M(n>=0,()=>`size must be non-negative, but got ${n}.`),M(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 z.runKernel(_h,i,o)}var e0=L({denseBincount_:yN});function gN(e,t,n="NHWC"){let r=R(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];M(a*t>=0,()=>`Negative dimension size caused by overflow when multiplying
${a} and ${t} for depthToSpace with input shape
${r.shape}`),M(s*t>=0,()=>`Negative dimension size caused by overflow when multiplying
${s} and ${t} for depthToSpace with input shape
${r.shape}`),M(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 z.runKernel(Ki,o,l)}var Uf=L({depthToSpace_:gN});function xN(e,t,n,r,a="NHWC",s=[1,1],i){let o=R(e,"x","depthwiseConv2d"),l=R(t,"filter","depthwiseConv2d"),c=o,u=!1;o.rank===3&&(u=!0,c=q(o,[1,o.shape[0],o.shape[1],o.shape[2]])),M(c.rank===4,()=>`Error in depthwiseConv2d: input must be rank 4, but got rank ${c.rank}.`),M(l.rank===4,()=>`Error in depthwiseConv2d: filter must be rank 4, but got rank ${l.rank}.`),M(c.shape[3]===l.shape[2],()=>`Error in depthwiseConv2d: number of input channels (${c.shape[3]}) must match the inChannels dimension in filter ${l.shape[2]}.`),i!=null&&M(Ut(r),()=>`Error in depthwiseConv2d: pad must be an integer when using, dimRoundingMode ${i} but got pad ${r}.`);let h={x:c,filter:l},d={strides:n,pad:r,dataFormat:a,dilations:s,dimRoundingMode:i},p=z.runKernel(as,h,d);return u?q(p,[p.shape[1],p.shape[2],p.shape[3]]):p}var Uo=L({depthwiseConv2d_:xN});function wN(e){let t={x:R(e,"x","diag")};return z.runKernel(kh,t)}var U4=L({diag_:wN});function _N(e,t,n,r,a=[1,1],s="NHWC"){let i=R(e,"x","dilation2d"),o=R(t,"filter","dilation2d");M(i.rank===3||i.rank===4,()=>`Error in dilation2d: input must be rank 3 or 4, but got rank ${i.rank}.`),M(o.rank===3,()=>`Error in dilation2d: filter must be rank 3, but got rank ${o.rank}.`),M(s==="NHWC",()=>`Error in dilation2d: Only NHWC is currently supported, but got dataFormat of ${s}`);let l=i,c=!1;i.rank===3&&(l=q(i,[1,i.shape[0],i.shape[1],i.shape[2]]),c=!0);let u={x:l,filter:o},h={strides:n,pad:r,dilations:a},d=z.runKernel(cu,u,h);return c?q(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var Hf=L({dilation2d_:_N});function bN(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 Ot(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 At(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 vN(e,t){let n=R(e,"a","equal"),r=R(t,"b","equal");[n,r]=vt(n,r),At(n.shape,r.shape);let a={a:n,b:r};return z.runKernel(Yi,a)}var xa=L({equal_:vN});function kN(e,t,n){let r=R(t,"a","where"),a=R(n,"b","where"),s=R(e,"condition","where","bool"),i=At(r.shape,a.shape),o=Cu(r,i),l=Cu(a,i);s.rank===1&&M(s.shape[0]===r.shape[0],()=>"The first dimension of `a` must match the size of `condition`."),s.rank!==1&&en(s.shape,l.shape,"Error in where: ");let c={condition:s,t:o,e:l};return z.runKernel(No,c)}var fn=L({where_:kN});function IN(e){let t={x:R(e,"x","zerosLike")};return z.runKernel(zo,t)}var He=L({zerosLike_:IN});function NN(e,t){let n=R(e,"a","div"),r=R(t,"b","div");[n,r]=vt(n,r);let a=Ne(n,r),s=He(a),i=xa(r,s);return fn(i,s,a)}var jf=L({divNoNan_:NN});function SN(e,t){let n=R(e,"t1","dot"),r=R(t,"t2","dot");M((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(M(a===s,()=>`Error in dot: inner dimensions of inputs must match, but got ${a} and ${s}.`),n.rank===1&&r.rank===1){let i=q(n,[1,-1]),o=q(r,[-1,1]),l=qe(i,o);return q(l,[])}else if(n.rank===1&&r.rank===2){let i=q(n,[1,-1]),o=q(r,[r.shape[0],r.shape[1]]),l=qe(i,o);return q(l,[l.size])}else if(n.rank===2&&r.rank===1){let i=q(r,[-1,1]),o=qe(n,i);return q(o,[o.size])}else{let i=q(r,[r.shape[0],r.shape[1]]);return qe(n,i)}}var t0=L({dot_:SN});function TN(e){let t={x:R(e,"x","elu")};return z.runKernel(Zi,t)}var Ho=L({elu_:TN});function EN(e){let t=R(e,"x","erf");M(t.dtype==="int32"||t.dtype==="float32",()=>"Input dtype must be `int32` or `float32`."),t.dtype==="int32"&&(t=ye(t,"float32"));let n={x:t};return z.runKernel(Ji,n)}var Gf=L({erf_:EN});function CN(e){let t={x:R(e,"x","exp")};return z.runKernel(is,t)}var Wn=L({exp_:CN});function RN(e,t=0){let n=R(e,"x","expandDims","string_or_numeric");M(t<=n.rank,()=>"Axis must be <= rank of the tensor");let r={input:n},a={dim:t};return z.runKernel(Qi,r,a)}var vn=L({expandDims_:RN});function FN(e){let t={x:R(e,"x","expm1")};return z.runKernel(eo,t)}var qf=L({expm1_:FN});function MN(e,t){let n=R(e,"x","tile","string_or_numeric");M(n.rank===t.length,()=>`Error in transpose: rank of input ${n.rank} must match length of reps ${t}.`);let r={x:n},a={reps:t};return z.runKernel(Aa,r,a)}var wa=L({tile_:MN});function $N(e,t,n,r="float32"){t==null&&(t=e);let a=We([e,t],r),s=e<=t?e:t;for(let o=0;o<s;++o)a.set(1,o,o);let i=q(a.toTensor(),[e,t]);if(n==null)return i;if(n.length===1)return wa(vn(i,0),[n[0],1,1]);if(n.length===2)return wa(vn(vn(i,0),0),[n[0],n[1],1,1]);if(n.length===3)return wa(vn(vn(vn(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 ${n.length}D.`)}var Xf=L({eye_:$N});function Fu(e,t,n){let r={shape:e,value:t,dtype:n};return z.runKernel(hu,{},r)}function DN(e){let t={x:R(e,"x","floor")};return z.runKernel(os,t)}var jo=L({floor_:DN});function ON(e,t,n=0,r=0){let a=R(e,"x","gather"),s=R(t,"indices","gather","int32"),i={x:a,indices:s},o={axis:n,batchDims:r};return z.runKernel(no,i,o)}var Us=L({gather_:ON});function zN(e,t){let n=R(e,"a","greater"),r=R(t,"b","greater");[n,r]=vt(n,r),At(n.shape,r.shape);let a={a:n,b:r};return z.runKernel(ao,a)}var tr=L({greater_:zN});function PN(e,t){let n=R(e,"a","greaterEqual"),r=R(t,"b","greaterEqual");[n,r]=vt(n,r),At(n.shape,r.shape);let a={a:n,b:r};return z.runKernel(cs,a)}var _a=L({greaterEqual_:PN});function LN(e){let t={input:R(e,"input","imag")};return z.runKernel(Ch,t)}var nd=L({imag_:LN});function WN(e){let t={x:R(e,"x","isFinite")};return z.runKernel(io,t)}var n0=L({isFinite_:WN});function BN(e){let t={x:R(e,"x","isInf")};return z.runKernel(oo,t)}var r0=L({isInf_:BN});function VN(e){let t={x:R(e,"x","isNaN")};return z.runKernel(lo,t)}var a0=L({isNaN_:VN});function UN(e,t=.2){let n={x:R(e,"x","leakyRelu")},r={alpha:t};return z.runKernel(hs,n,r)}var Mu=L({leakyRelu_:UN});function HN(e,t){let n=R(e,"a","less"),r=R(t,"b","less");[n,r]=vt(n,r),At(n.shape,r.shape);let a={a:n,b:r};return z.runKernel(uo,a)}var rd=L({less_:HN});function jN(e,t){let n=R(e,"a","lessEqual"),r=R(t,"b","lessEqual");[n,r]=vt(n,r),At(n.shape,r.shape);let a={a:n,b:r};return z.runKernel(co,a)}var Hs=L({lessEqual_:jN});function s0(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 z.runKernel(Rh,{},r)}function GN(e,t=5,n=1,r=1,a=.5){let s=R(e,"x","localResponseNormalization");M(s.rank===4||s.rank===3,()=>`Error in localResponseNormalization: x must be rank 3 or 4 but got
rank ${s.rank}.`),M(Ut(t),()=>`Error in localResponseNormalization: depthRadius must be an integer but got depthRadius ${t}.`);let i=s,o=!1;s.rank===3&&(o=!0,i=q(s,[1,s.shape[0],s.shape[1],s.shape[2]]));let l={x:i},c={depthRadius:t,bias:n,alpha:r,beta:a},u=z.runKernel(fu,l,c);return o?q(u,[u.shape[1],u.shape[2],u.shape[3]]):u}var Kf=L({localResponseNormalization_:GN});function qN(e){let t={x:R(e,"x","log")};return z.runKernel(ds,t)}var kn=L({log_:qN});function XN(e){let t={x:R(e,"x","log1p")};return z.runKernel(ho,t)}var ad=L({log1p_:XN});function H4(e){return M(Ia(e),()=>"The f passed in grad(f) must be a function"),(t,n)=>{let r=R(t,"x","tf.grad","string_or_numeric"),a=n!=null?R(n,"dy","tf.grad"):null;return z.tidy(()=>{let{value:s,grads:i}=z.gradients(()=>e(r),[r],a);return a!=null&&en(s.shape,a.shape,"The shape of dy passed in grad(f)(x, dy) must match the shape returned by f(x)"),Wd(i),i[0]})}}function j4(e){return M(Ia(e),()=>"The f passed in grads(f) must be a function"),(t,n)=>{M(Array.isArray(t),()=>"The args passed in grads(f)(args) must be an array of `Tensor`s or `TensorLike`s");let r=Qu(t,"args","tf.grads","string_or_numeric"),a=n!=null?R(n,"dy","tf.grads"):null;return z.tidy(()=>{let{value:s,grads:i}=z.gradients(()=>e(...r),r,a);return a!=null&&en(s.shape,a.shape,"The shape of dy passed in grads(f)([x1,...], dy) must match the shape returned by f([x1,...])"),Wd(i),i})}}function G4(e){return M(Ia(e),()=>"The f passed in valueAndGrad(f) must be a function"),(t,n)=>{M(t instanceof Qe,()=>"The x passed in valueAndGrad(f)(x) must be a tensor"),M(n==null||n instanceof Qe,()=>"The dy passed in valueAndGrad(f)(x, dy) must be a tensor");let{grads:r,value:a}=z.gradients(()=>e(t),[t],n);return Wd(r),{grad:r[0],value:a}}}function q4(e){return M(Ia(e),()=>"The f passed in valueAndGrads(f) must be a function"),(t,n)=>{M(Array.isArray(t)&&t.every(a=>a instanceof Qe),()=>"The args passed in valueAndGrads(f)(args) must be array of tensors"),M(n==null||n instanceof Qe,()=>"The dy passed in valueAndGrads(f)(args, dy) must be a tensor");let r=z.gradients(()=>e(...t),t,n);return n!=null&&en(r.value.shape,n.shape,"The shape of dy passed in valueAndGrads(f)([x1,...], dy) must match the shape returned by f([x1,...])"),Wd(r.grads),r}}function i0(e,t){M(Ia(e),()=>"The f passed in variableGrads(f) must be a function"),M(t==null||Array.isArray(t)&&t.every(c=>c instanceof vu),()=>"The varList passed in variableGrads(f, varList) must be an array of variables");let n=t!=null;if(!n){t=[];for(let c in z.registeredVariables)t.push(z.registeredVariables[c])}let r=n?t.filter(c=>!c.trainable):null,a=t.length;t=t.filter(c=>c.trainable),M(t.length>0,()=>`variableGrads() expects at least one of the input variables to be trainable, but none of the ${a} variables is trainable.`);let s=!0,{value:i,grads:o}=z.gradients(e,t,null,s);M(o.some(c=>c!=null),()=>"Cannot find a connection between any variable and the result of the loss function y=f(x). Please make sure the operations that use variables are inside the function f passed to minimize()."),M(i.rank===0,()=>`The f passed in variableGrads(f) must return a scalar, but it returned a rank-${i.rank} tensor`);let l={};return t.forEach((c,u)=>{o[u]!=null&&(l[c.name]=o[u])}),r!=null&&r.forEach(c=>l[c.name]=null),{value:i,grads:l}}function Sr(e){return z.customGrad(e)}function Wd(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 KN(e){let t={x:R(e,"x","neg")};return z.runKernel(mo,t)}var _t=L({neg_:KN});function ZN(e){let t={x:R(e,"x","softplus")};return z.runKernel(Ro,t)}var Go=L({softplus_:ZN});function JN(e){let t=R(e,"x","logSigmoid");return Sr(n=>({value:_t(Go(_t(n))),gradFunc:r=>W(r,er(_t(n)))}))(t)}var o0=L({logSigmoid_:JN});function YN(e,t=null,n=!1){let r={x:R(e,"x","max")},a={reductionIndices:t,keepDims:n};return z.runKernel(ps,r,a)}var Bn=L({max_:YN});function QN(e,t){let n=R(e,"a","sub"),r=R(t,"b","sub");[n,r]=vt(n,r);let a={a:n,b:r};return z.runKernel(Os,a)}var we=L({sub_:QN});function eS(e,t=null,n=!1){let r=R(e,"x","sum");r.dtype==="bool"&&(r=ye(r,"int32"));let a={x:r},s={axis:t,keepDims:n};return z.runKernel(Ms,a,s)}var Te=L({sum_:eS});function tS(e,t=-1){let n=R(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 ${t}`);return Sr((r,a)=>{let s=!0,i=Bn(r,t,!0),o=we(r,i),l=we(ye(o,"float32"),kn(Te(Wn(o),t,s)));return a([l]),{value:l,gradFunc:(c,u)=>{let[h]=u,d=!0,p=Wn(h);return we(c,W(Te(c,t,d),p))}}})(n)}var sd=L({logSoftmax_:tS});function Jm(e,t){for(let n=0;n<e.length;++n)if(e[e.length-n-1]!==t-1-n)return!1;return!0}function q5(e,t,n){let r=e.length+t.length,a=[],s=0,i=0;for(let o=0;o<r;o++)n.indexOf(o)===-1?a.push(e[s++]):a.push(t[i++]);return a}function X5(e,t){let n=[],r=e.length;for(let s=0;s<r;s++)t.indexOf(s)===-1&&n.push(e[s]);let a=t.map(s=>e[s]);return[n,a]}function ei(e,t){let n=t.map(r=>1);return q5(e,n,t)}function nS(e,t,n){M(Jm(t,n),()=>`${e} supports only inner-most axes for now. Got axes ${t} and rank-${n} input.`)}function K5(e,t){if(Jm(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 Ym(e){return e.map((t,n)=>[n,t]).sort((t,n)=>t[1]-n[1]).map(t=>t[0])}function rS(e,t){let n=[];for(let r=t-e;r<t;++r)n.push(r);return n}function aS(e,t=null,n=!1){let r=R(e,"x","logSumExp"),a=ar(t,r.shape),s=Bn(r,a,!0),i=we(r,s),o=Wn(i),l=Te(o,a),c=kn(l),u=oe(q(s,c.shape),c);if(n){let h=ei(u.shape,a);return q(u,h)}return u}var Zf=L({logSumExp_:aS});function sS(e,t){let n=R(e,"a","logicalAnd","bool"),r=R(t,"b","logicalAnd","bool");At(n.shape,r.shape);let a={a:n,b:r};return z.runKernel(po,a)}var nr=L({logicalAnd_:sS});function iS(e){let t={x:R(e,"x","logicalNot","bool")};return z.runKernel(du,t)}var $u=L({logicalNot_:iS});function oS(e,t){let n=R(e,"a","logicalOr","bool"),r=R(t,"b","logicalOr","bool");At(n.shape,r.shape);let a={a:n,b:r};return z.runKernel(pu,a)}var id=L({logicalOr_:oS});function lS(e,t){let n=R(e,"a","logicalXor","bool"),r=R(t,"b","logicalXor","bool");return At(n.shape,r.shape),nr(id(e,t),$u(nr(e,t)))}var l0=L({logicalXor_:lS});function uS(e,t,n,r,a){let s=R(e,"x","maxPool"),i=1,o=s,l=!1;s.rank===3&&(l=!0,o=q(s,[1,s.shape[0],s.shape[1],s.shape[2]])),M(o.rank===4,()=>`Error in maxPool: input must be rank 4 but got rank ${o.rank}.`),M(zr(n,i),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${n} and dilations '${i}'`),a!=null&&M(Ut(r),()=>`Error in maxPool: pad must be an integer when using, dimRoundingMode ${a} but got pad ${r}.`);let c={x:o},u={filterSize:t,strides:n,pad:r,dimRoundingMode:a},h=z.runKernel(ms,c,u);return l?q(h,[h.shape[1],h.shape[2],h.shape[3]]):h}var Du=L({maxPool_:uS});function cS(e,t=[1,1,1],n,r,a,s="NDHWC"){let i=R(e,"x","maxPool3d"),o=i,l=!1;i.rank===4&&(l=!0,o=q(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),M(o.rank===5,()=>`Error in maxPool3d: x must be rank 5 but got rank ${o.rank}.`),M(s==="NDHWC",()=>`Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of ${s}`),a!=null&&M(Ut(r),()=>`Error in maxPool3d: pad must be an integer when using, dimRoundingMode ${a} but got pad ${r}.`);let c={x:o},u={filterSize:t,strides:n,pad:r,dimRoundingMode:a,dataFormat:s},h=z.runKernel(mu,c,u);return l?q(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}var Jf=L({maxPool3d_:cS});function hS(e,t,n,r,a=!1){let s={x:R(e,"x","maxPoolWithArgmax")},i={filterSize:t,strides:n,pad:r,includeBatchInIndex:a},o=z.runKernel(Dh,s,i);return{result:o[0],indexes:o[1]}}var u0=L({maxPoolWithArgmax_:hS});function dS(e,t){let n=R(e,"a","maximum"),r=R(t,"b","maximum");[n,r]=vt(n,r),n.dtype==="bool"&&(n=ye(n,"int32"),r=ye(r,"int32")),At(n.shape,r.shape);let a={a:n,b:r};return z.runKernel(fs,a)}var Tr=L({maximum_:dS});function pS(e,t=null,n=!1){let r={x:R(e,"x","mean")},a={axis:t,keepDims:n};return z.runKernel(As,r,a)}var bt=L({mean_:pS});function fS(e,t=null,n=!1){let r={x:R(e,"x","min")},a={axis:t,keepDims:n};return z.runKernel(ys,r,a)}var qo=L({min_:fS});function mS(e,t){let n=R(e,"a","minimum"),r=R(t,"b","minimum");[n,r]=vt(n,r),n.dtype==="bool"&&(n=ye(n,"int32"),r=ye(r,"int32")),At(n.shape,r.shape);let a={a:n,b:r};return z.runKernel(gs,a)}var Xo=L({minimum_:mS});function AS(e,t,n){M(n==="reflect"||n==="symmetric",()=>`Invalid mode. Mode must be either reflect or symmetric. Got ${n}.`);let r=R(e,"x","mirrorPad");if(r.rank===0)throw new Error("mirrorPad(scalar) is not defined. Pass non-scalar to mirrorPad");M(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++)M(t[o].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),M(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 z.runKernel(Au,i,s)}var Yf=L({mirrorPad_:AS});function yS(e,t){let n=R(e,"a","mod"),r=R(t,"b","mod");[n,r]=vt(n,r);let a={a:n,b:r};return z.runKernel(fo,a)}var Qf=L({mod_:yS});function gS(e){let t=R(e,"x","square"),n={};return z.runKernel("Square",{x:t},n)}var ot=L({square_:gS});function xS(e,t=null,n=!1){e=R(e,"x","moments");let r=ar(t,e.shape),a=bt(e,r,n),s=a.shape;n||(s=ei(a.shape,r));let i=ot(we(ye(e,"float32"),q(a,s))),o=bt(i,r,n);return{mean:a,variance:o}}var od=L({moments_:xS});function wS(e,t,n,r){let a=R(t,"data","multiRNNCell"),s=Qu(n,"c","multiRNNCell"),i=Qu(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 c=[],u=[];for(let h=0;h<l.length;h+=2)c.push(l[h]),u.push(l[h+1]);return[c,u]}var X4=L({multiRNNCell_:wS});function _S(e,t,n,r=!1){let a=R(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?q(a,[1,-1]):a},l={numSamples:t,seed:n,normalized:r},c=z.runKernel(Oh,o,l);return i===1?q(c,[c.size]):c}var c0=L({multinomial_:_S});function bS(e,t){let n=R(e,"a","notEqual"),r=R(t,"b","notEqual");[n,r]=vt(n,r),At(n.shape,r.shape);let a={a:n,b:r};return z.runKernel(Ao,a)}var js=L({notEqual_:bS});function Ct(e,t="float32"){if(t==="complex64"){let r=Ct(e,"float32"),a=Ct(e,"float32");return ga(r,a)}let n=Fd(Dt(e),t);return z.makeTensor(n,e,t)}function Er(e,t="float32"){if(t==="complex64"){let r=Er(e,"float32"),a=Ct(e,"float32");return ga(r,a)}let n=gm(Dt(e),t);return z.makeTensor(n,e,t)}function vS(e){let t={x:R(e,"x","onesLike")};return z.runKernel(wo,t)}var In=L({onesLike_:vS});function kS(e,t){let n=R(e,"v1","outerProduct"),r=R(t,"v2","outerProduct");M(n.rank===1&&r.rank===1,()=>`Error in outerProduct: inputs must be rank 1, but got ranks ${n.rank} and ${r.rank}.`);let a=q(n,[-1,1]),s=q(r,[1,-1]);return qe(a,s)}var K4=L({outerProduct_:kS});function IS(e,t,n=0){let r=R(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 z.runKernel(_s,s,a)}var Jr=L({pad_:IS});function NS(e,t,n=0){return M(t.length===2,()=>"Invalid number of paddings. Must be length of 2."),Jr(e,[t],n)}var Z4=L({pad1d_:NS});function SS(e,t,n=0){return M(t.length===2&&t[0].length===2&&t[1].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),Jr(e,t,n)}var J4=L({pad2d_:SS});function TS(e,t,n=0){return M(t.length===3&&t[0].length===2&&t[1].length===2&&t[2].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),Jr(e,t,n)}var Y4=L({pad3d_:TS});function ES(e,t,n=0){return M(t.length===4&&t[0].length===2&&t[1].length===2&&t[2].length===2&&t[3].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),Jr(e,t,n)}var Q4=L({pad4d_:ES});function CS(e,t,n){let r=R(e,"x","spaceToBatchND");M(r.rank>=1+t.length,()=>`input rank ${r.rank} should be > than [blockShape] ${t.length}`),M(n.length===t.length,()=>`paddings.shape[0] ${n.length} must be equal to [blockShape] ${t.length}`),M(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 z.runKernel(xu,a,s)}var Ou=L({spaceToBatchND_:CS});function MS(e,t,n,r,a,s){a==null&&(a=[1,1]),s==null&&(s=1),r===0&&(r="valid");let i=R(e,"x","maxPool"),o=i,l=!1;i.rank===3&&(l=!0,o=q(i,[1,i.shape[0],i.shape[1],i.shape[2]])),M(zr(s,a),()=>`Error in pool: Either strides or dilations must be 1. Got strides ${s} and dilations '${a}'`);let c=H5(o.shape,t,s,a,r),u=[c.dilationHeight,c.dilationWidth],h;r==="same"?h=FS([c.filterHeight,c.filterWidth],u):h=[[0,0],[0,0]];let d=u[0]===1&&u[1]===1,[p,f]=RS([c.inHeight,c.inWidth],u,h),m=d?r:"valid",A=d?o:Ou(o,u,p),y=(n==="avg"?()=>Tu(A,t,s,m):()=>Du(A,t,s,m))(),g=d?y:Eu(y,u,f);return l?q(g,[g.shape[1],g.shape[2],g.shape[3]]):g}function RS(e,t,n){let r=n.map(u=>u[0]),a=n.map(u=>u[1]),s=e.concat(r,a),i=t.map((u,h)=>(u-s[h]%u)%u),o=a.map((u,h)=>u+i[h]),l=t.map((u,h)=>[r[h],o[h]]),c=t.map((u,h)=>[0,i[h]]);return[l,c]}function FS(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 h0=L({pool_:MS});function $S(e,t){let n=R(e,"base","pow"),r=R(t,"exp","pow");[n,r]=vt(n,r);let a={a:n,b:r};return z.runKernel(bs,a)}var Yr=L({pow_:$S});function DS(e,t){let n=R(e,"x","prelu"),r=R(t,"alpha","prelu"),a={x:n,alpha:r};return z.runKernel(vs,a)}var zu=L({prelu_:DS});function OS(e,t=null,n=!1){let r=R(e,"x","prod");r.dtype==="bool"&&(r=ye(r,"int32"));let a={x:r},s={axis:t,keepDims:n};return z.runKernel(bo,a,s)}var ld=L({prod_:OS});function zS(e,t,n){let r=Dt(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 z.makeTensor(a,e,n)}var e8=L({rand_:zS}),Qm=Qo(B8()),eA=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=Qm.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}},PS=class{constructor(e,t,n,r){this.alpha=e,this.beta=1/t,this.dtype=n;let a=r||Math.random();this.randu=Qm.alea(a.toString()),this.randn=new eA(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)}},LS=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=Qm.alea(r)}convertValue(e){return this.canReturnFloat()?e:Math.round(e)}nextValue(){return this.convertValue(this.min+this.range*this.random())}};function WS(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 PS(t,n,r,a),i=We(e,r);for(let o=0;o<i.values.length;o++)i.values[o]=s.nextValue();return i.toTensor()}var t8=L({randomGamma_:WS});function BS(e,t=0,n=1,r,a){if(r!=null&&r==="bool")throw new Error(`Unsupported data type ${r}`);let s=new eA(t,n,r,!1,a),i=We(e,r);for(let o=0;o<i.values.length;o++)i.values[o]=s.nextValue();return i.toTensor()}var d0=L({randomNormal_:BS});function VS(e,t=0,n=1,r="float32",a){let s=We(e,r),i=new LS(t,n,null,a);for(let o=0;o<s.values.length;o++)s.values[o]=i.nextValue();return s.toTensor()}var Ko=L({randomUniform_:VS});function ud(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 z.runKernel(yu,{},a)}function US(e){let t={input:R(e,"input","real")};return z.runKernel(zh,t)}var Pu=L({real_:US});function HS(e){let t={x:R(e,"x","reciprocal")};return z.runKernel(vo,t)}var em=L({reciprocal_:HS});function jS(e){let t={x:R(e,"x","relu")};return z.runKernel(ks,t)}var Cr=L({relu_:jS});function GS(e){let t={x:R(e,"x","relu6")};return z.runKernel(Ns,t)}var cd=L({relu6_:GS});function qS(e,t){let n={x:R(e,"x","reverse")},r={dims:t};return z.runKernel(Ss,n,r)}var Nn=L({reverse_:qS});function XS(e){let t=R(e,"x","reverse");return M(t.rank===1,()=>`Error in reverse1D: x must be rank 1 but got rank ${t.rank}.`),Nn(t,0)}var n8=L({reverse1d_:XS});function KS(e,t){let n=R(e,"x","reverse");return M(n.rank===2,()=>`Error in reverse2D: x must be rank 2 but got rank ${n.rank}.`),Nn(n,t)}var r8=L({reverse2d_:KS});function ZS(e,t){let n=R(e,"x","reverse");return M(n.rank===3,()=>`Error in reverse3D: x must be rank 3 but got rank ${n.rank}.`),Nn(n,t)}var a8=L({reverse3d_:ZS});function JS(e,t){let n=R(e,"x","reverse");return M(n.rank===4,()=>`Error in reverse4D: x must be rank 4 but got rank ${n.rank}.`),Nn(n,t)}var s8=L({reverse4d_:JS});function YS(e){let t={x:R(e,"x","round")};return z.runKernel(Ts,t)}var tm=L({round_:YS});function QS(e){let t={x:R(e,"x","rsqrt")};return z.runKernel(Es,t)}var hd=L({rsqrt_:QS});function Se(e,t){if((tn(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"&&tn(e)&&!(e instanceof Uint8Array))throw new Error("When making a scalar from encoded string, the value must be `Uint8Array`.");return Na(e,[],[],t)}function eT(e){let t={x:R(e,"x","selu")};return z.runKernel(So,t)}var dd=L({selu_:eT});function tT(e,t,n,r,a,s=[1,1],i="NHWC"){let o=R(e,"x","separableConv2d"),l=R(t,"depthwiseFilter","separableConv2d"),c=R(n,"pointwiseFilter","separableConv2d"),u=o,h=!1;if(o.rank===3&&(h=!0,u=q(o,[1,o.shape[0],o.shape[1],o.shape[2]])),i==="NCHW")throw new Error("separableConv2d currently does not support dataFormat NCHW; only NHWC is supported");M(u.rank===4,()=>`Error in separableConv2d: input must be rank 4, but got rank ${u.rank}.`),M(l.rank===4,()=>`Error in separableConv2d: depthwise filter must be rank 4, but got rank ${l.rank}.`),M(c.rank===4,()=>`Error in separableConv2d: pointwise filter must be rank 4, but got rank ${l.rank}.`),M(c.shape[0]===1,()=>`Error in separableConv2d: the first dimension of pointwise filter must be 1, but got ${c.shape[0]}.`),M(c.shape[1]===1,()=>`Error in separableConv2d: the second dimension of pointwise filter must be 1, but got ${c.shape[1]}.`);let d=l.shape[2],p=l.shape[3];M(c.shape[2]===d*p,()=>`Error in separableConv2d: the third dimension of pointwise filter must be ${d*p}, but got ${c.shape[2]}.`);let f=Uo(u,l,r,a,i,s),m=Zr(f,c,1,"valid",i);return h?q(m,[m.shape[1],m.shape[2],m.shape[3]]):m}var nm=L({separableConv2d_:tT});async function nT(e,t){let n=R(e,"x","setdiff1d"),r=R(t,"y","setdiff1d");M(n.dtype===r.dtype,()=>`x and y should have the same dtype, but got x (${n.dtype}) and y (${r.dtype}).`),M(n.rank===1,()=>`x should be 1D tensor, but got x (${n.shape}).`),M(r.rank===1,()=>`y should be 1D tensor, but got y (${r.shape}).`);let a=await n.data(),s=await r.data(),i=new Set(s),o=0;for(let u=0;u<a.length;u++)i.has(a[u])||o++;let l=new Mt([o],n.dtype),c=new Mt([o],"int32");for(let u=0,h=0;u<a.length;u++)i.has(a[u])||(l.values[h]=a[u],c.values[h]=u,h++);return[l.toTensor(),c.toTensor()]}var p0=nT;function rT(e){let t={x:R(e,"x","sign")};return z.runKernel(Co,t)}var rm=L({sign_:rT});function aT(e){let t={x:R(e,"x","sin")};return z.runKernel(Cs,t)}var pd=L({sin_:aT});function sT(e){let t={x:R(e,"x","sinh")};return z.runKernel(Eo,t)}var fd=L({sinh_:sT});function iT(e,t,n){let r=R(e,"x","slice1d");return M(r.rank===1,()=>`slice1d expects a rank-1 tensor, but got a rank-${r.rank} tensor`),Me(r,[t],[n])}var md=L({slice1d_:iT});function oT(e,t,n){let r=R(e,"x","slice2d");return M(r.rank===2,()=>`slice2d expects a rank-2 tensor, but got a rank-${r.rank} tensor`),Me(r,t,n)}var am=L({slice2d_:oT});function lT(e,t,n){let r=R(e,"x","slice3d");return M(r.rank===3,()=>`slice3d expects a rank-3 tensor, but got a rank-${r.rank} tensor`),Me(r,t,n)}var Ad=L({slice3d_:lT});function uT(e,t,n){let r=R(e,"x","slice4d");return M(r.rank===4,()=>`slice4d expects a rank-4 tensor, but got a rank-${r.rank} tensor`),Me(r,t,n)}var Lu=L({slice4d_:uT});function cT(e,t=-1){let n=R(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 ${t}`);let r={logits:n},a={dim:t};return z.runKernel($s,r,a)}var Wu=L({softmax_:cT});function hT(e){M(e.dtype==="complex64",()=>`The dtype for tf.spectral.fft() must be complex64 but got ${e.dtype}.`);let t={input:e};return z.runKernel(Th,t)}var Bu=L({fft_:hT});function dT(e){M(e.dtype==="complex64",()=>`The dtype for tf.spectral.ifft() must be complex64 but got ${e.dtype}.`);let t={input:e};return z.runKernel(Eh,t)}var Zo=L({ifft_:dT});function pT(e){let t=e.shape[e.shape.length-1],n=e.size/t,r;if(t<=2){let a=q(e,[n,t]);r=Zo(a)}else{let a=[n,2*(t-1)],s=q(Pu(e),[n,t]),i=q(nd(e),[n,t]),o=Nn(Me(s,[0,1],[n,t-2]),1),l=W(Nn(Me(i,[0,1],[n,t-2]),1),Se(-1)),c=ct([s,o],1),u=ct([i,l],1),h=q(ga(c,u),[a[0],a[1]]);r=Zo(h)}if(r=Pu(r),e.rank===3&&e.shape[0]!==0){let a=r,s=e.shape[0];r=q(r,[s,r.shape[0]/s,r.shape[1]]),a.dispose()}return r}var yd=L({irfft_:pT});function fT(e,t,n=0){let r={x:R(e,"x","split")},a={numOrSizeSplits:t,axis:n};return z.runKernel(Fo,r,a)}var an=L({split_:fT});function mT(e,t){M(e.dtype==="float32",()=>`The dtype for rfft() must be real value but got ${e.dtype}`);let n=e.shape[e.shape.length-1],r=e.size/n,a;if(t!=null&&t<n){let f=e.shape.map(A=>0),m=e.shape.map(A=>A);m[e.shape.length-1]=t,a=Me(e,f,m),n=t}else if(t!=null&&t>n){let f=e.shape.map(m=>m);f[e.shape.length-1]=t-n,a=ct([e,Ct(f)],e.shape.length-1),n=t}else a=e;let s=He(a),i=q(ga(a,s),[r,n]),o=Bu(i),l=Math.floor(n/2)+1,c=Pu(o),u=nd(o),h=an(c,[l,n-l],c.shape.length-1),d=an(u,[l,n-l],u.shape.length-1),p=a.shape.slice();return p[a.shape.length-1]=l,q(ga(h[0],d[0]),p)}var Vu=L({rfft_:mT});function AT(e){let t={x:R(e,"x","sqrt")};return z.runKernel(Fs,t)}var Xt=L({sqrt_:AT});function yT(e,t){let n=R(e,"a","squaredDifference"),r=R(t,"b","squaredDifference");[n,r]=vt(n,r),At(n.shape,r.shape);let a={a:n,b:r},s={};return z.runKernel(Ds,a,s)}var gd=L({squaredDifference_:yT});function gT(e,t){let n=R(e,"x","squeeze");return q(n,G0(n.shape,t).newShape)}var ba=L({squeeze_:gT});function xT(e,t=0){let n=Qu(e,"tensors","stack","string_or_numeric");M(n.length>=1,()=>"Pass at least one tensor to tf.stack"),n.length>0&&M(t<=n[0].rank,()=>"Axis must be <= rank of the tensor");let r=n,a={axis:t};return z.runKernel(_o,r,a)}var Sn=L({stack_:xT});function wT(e,t=0){let n={x:R(e,"x","step")},r={alpha:t};return z.runKernel(ya,n,r)}var Jo=L({step_:wT});function _T(e,t,n,r,a=0,s=0,i=0,o=0,l=0){let c={x:R(e,"x","stridedSlice")},u={begin:t,end:n,strides:r,beginMask:a,endMask:s,ellipsisMask:i,newAxisMask:o,shrinkAxisMask:l};return z.runKernel(Mo,c,u)}var sm=L({stridedSlice_:_T});function bT(e){let t={x:R(e,"x","tan")};return z.runKernel($o,t)}var im=L({tan_:bT});function Qt(e,t){qs(e);let n=Or(e,t);if(n.length!==1)throw new Error("tensor1d() requires values to be a flat/TypedArray");return Na(e,null,n,t)}function fr(e,t,n){if(qs(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 Na(e,t,r,n)}function i8(e,t,n){if(qs(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 Na(e,t,r,n)}function o8(e,t,n){if(qs(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 Na(e,t,r,n)}function l8(e,t,n){if(qs(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,Na(e,t,r,n)}function vT(e,t=1,n=!0){let r=R(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]=z.runKernel(Do,s,i);return{values:o,indices:l}}var om=L({topk_:vT});function kT(e,t=0,n=1,r,a){if(r!=null&&r==="bool")throw new Error("Unsupported data type $ { dtype }");let s=new eA(t,n,r,!0,a),i=We(e,r);for(let o=0;o<i.values.length;o++)i.values[o]=s.nextValue();return i.toTensor()}var xd=L({truncatedNormal_:kT});function IT(e,t=0){let n=R(e,"x","unique","string_or_numeric");M(n.rank>0,()=>"The input tensor must be at least 1D");let r={x:n},a={axis:t},[s,i]=z.runKernel(Bh,r,a);return{values:s,indices:i}}var wd=L({unique_:IT});function NT(e,t,n){let r=R(e,"x","unsortedSegmentSum"),a=R(t,"segmentIds","unsortedSegmentSum","int32");M(Ut(n),()=>"numSegments must be of dtype int");let s={x:r,segmentIds:a},i={numSegments:n};return z.runKernel(_u,s,i)}var lm=L({unsortedSegmentSum_:NT});function ST(e,t=0){let n=R(e,"x","unstack","string_or_numeric");M(t>=-n.shape.length&&t<n.shape.length,()=>`Axis = ${t} is not in [-${n.shape.length}, ${n.shape.length})`);let r={value:n},a={axis:t};return z.runKernel(Oo,r,a)}var rr=L({unstack_:ST});function f0(e,t=!0,n,r){return z.makeVariable(e,t,n,r)}function Z5(e,t){let n=[];for(let s=0;s<t.length;s++)t[s]&&n.push(s);let r=We(e,"int32"),a=We([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 TT(e){let t=R(e,"condition","whereAsync","bool"),n=await t.data(),r=Z5(t.shape,n);return e!==t&&t.dispose(),r}var um=TT;async function ET(e,t,n){let r=R(e,"tensor","boolMask"),a=R(t,"mask","boolMask","bool"),s=n==null?0:n,i=a.rank,o=r.shape;M(i>0,()=>"mask cannot be scalar"),en(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 c=o.slice(0,s).concat([l],o.slice(s+i)),u=q(r,c),h=q(a,[-1]),d=await um(h),p=ba(d,[1]),f=Us(u,p,s);return e!==r&&r.dispose(),t!==a&&a.dispose(),p.dispose(),u.dispose(),h.dispose(),d.dispose(),f}var u8=ET;function CT(e,t="euclidean",n=null,r=!1){e=R(e,"x","norm");let a=J5(e,t,n),s=a.shape;if(r){let i=ar(n,e.shape);s=ei(a.shape,i)}return q(a,s)}function J5(e,t,n=null){if(e.rank===0)return $t(e);if(e.rank!==1&&n===null)return J5(q(e,[-1]),t,n);if(e.rank===1||typeof n=="number"||Array.isArray(n)&&n.length===1){if(t===1)return Te($t(e),n);if(t===Infinity)return Bn($t(e),n);if(t===-Infinity)return qo($t(e),n);if(t==="euclidean"||t===2)return Xt(Te(Yr($t(e),Se(2,"int32")),n));throw new Error(`Error in norm: invalid ord value: ${t}`)}if(Array.isArray(n)&&n.length===2){if(t===1)return Bn(Te($t(e),n[0]),n[1]-1);if(t===Infinity)return Bn(Te($t(e),n[1]),n[0]);if(t===-Infinity)return qo(Te($t(e),n[1]),n[0]);if(t==="fro"||t==="euclidean")return Xt(Te(ot(e),n));throw new Error(`Error in norm: invalid ord value: ${t}`)}throw new Error(`Error in norm: invalid axis: ${n}`)}var _d=L({norm_:CT});function RT(e,t,n,r,a=!0){let s=R(e,"v","movingAverage"),i=R(t,"x","movingAverage"),o=R(n,"decay","movingAverage");i5(s,i),M(ta(s.shape,i.shape),()=>"Shape mismatch in v and x");let l=Se(1),c=we(l,o),u=W(we(i,s),c);if(a){M(r!=null,()=>"When using zeroDebias: true, step is required.");let h=R(r,"step","movingAverage");u=Ne(u,we(l,Yr(o,h)))}return oe(s,u)}var c8=L({movingAverage_:RT});function FT(e,t,n){let r=R(e,"indices","scatterND","int32"),a=R(t,"updates","scatterND");Hm(a,r,n);let s={indices:r,updates:a},i={shape:n};return z.runKernel(Io,s,i)}var m0=L({scatterND_:FT});function MT(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 $T(e,t,n,r=0){let a=R(e,"sparseIndices","sparseToDense","int32"),s=R(t,"sparseValues","sparseToDense"),i=R(r,"defaultValue","sparseToDense",s.dtype);MT(a,s,n,i);let o={sparseIndices:a,sparseValues:s,defaultValue:i},l={outputShape:n};return z.runKernel(Wh,o,l)}var cm=L({sparseToDense_:$T});function DT(e,t){let n=R(t,"indices","gatherND","int32"),r={params:R(e,"x","gatherND"),indices:n};return z.runKernel(ro,r)}var A0=L({gatherND_:DT});function OT(e,t){if(t==null)return e.shape.slice();if(ta(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 zT(e,t,n,r){let a=R(e,"x","dropout");if(M(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.`),M(t>=0&&t<1,()=>`rate must be a float in the range [0, 1), but got ${t}.`),t===0)return e instanceof Qe?a.clone():a;let s=OT(a,n),i=1-t,o=Ne(jo(oe(Ko(s,0,1,"float32",r),i)),i);return W(a,o)}var y0=L({dropout_:zT});function g0(e){return Math.floor(Math.pow(2,Math.ceil(Math.log(e)/Math.log(2))))}function hm(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 Qt(a,"float32")}async function PT(e,t,n=1){let r=R(e,"predictions","inTopK"),a=R(t,"targets","inTopK");M(r.rank>1,()=>`inTopK() expects the predictions to be of rank 2 or higher, but got ${r.rank}`),M(r.rank-1===a.rank,()=>`predictions rank should be 1 larger than targets rank, but got predictions rank ${r.rank} and targets rank ${a.rank}`),en(r.shape.slice(0,r.shape.length-1),a.shape,"predictions's shape should be align with the targets' shape, except the last dimension.");let s=r.shape[r.shape.length-1];M(n>0&&n<=s,()=>`'k' passed to inTopK() must be > 0 && <= the predictions last dimension (${s}), but got ${n}`);let i=await r.data(),o=await a.data(),[l,c]=[i.length/s,s],u=q0("bool",l);for(let h=0;h<l;h++){let d=h*c,p=i.subarray(d,d+c),f=[];for(let m=0;m<p.length;m++)f.push({value:p[m],index:m});f.sort((m,A)=>A.value-m.value),u[h]=0;for(let m=0;m<n;m++)if(f[m].index===o[h]){u[h]=1;break}}return e!==r&&r.dispose(),t!==a&&a.dispose(),pr(u,a.shape,"bool")}var h8=PT,va={};ze(va,{conv2d:()=>LT,depthwiseConv2d:()=>WT,matMul:()=>BT});function VT(e,t,n,r,a,s="NHWC",i){let o=e;e.rank===3&&(o=q(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let l=t;l.rank===3&&(l=q(t,[1,t.shape[0],t.shape[1],t.shape[2]])),M(o.rank===4,()=>`Error in conv2dDerFilter: input must be rank 4, but got shape ${o.shape}.`),M(l.rank===4,()=>`Error in conv2dDerFilter: dy must be rank 4, but got shape ${l.shape}.`),M(n.length===4,()=>`Error in conv2dDerFilter: filterShape must be length 4, but got ${n}.`);let c=s==="NHWC"?o.shape[3]:o.shape[1],u=s==="NHWC"?l.shape[3]:l.shape[1];M(c===n[2],()=>`Error in conv2dDerFilter: depth of input ${c}) must match input depth in filter (${n[2]}.`),M(u===n[3],()=>`Error in conv2dDerFilter: depth of dy (${u}) must match output depth for filter (${n[3]}).`),i!=null&&M(Ut(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 z.runKernel(gh,h,d)}var tA=L({conv2DBackpropFilter_:VT});function Bd(e,t,n){if(n==null||n==="linear")return e;if(n==="relu")return W(e,Jo(t));throw new Error(`Cannot compute gradient for fused activation ${n}.`)}function Vd(e,t){let n=t,r=Ot(e.shape,t.shape);return r.length>0&&(n=Te(n,r)),q(n,e.shape)}function Ud(e,t,n,r){if(t==="linear")return e;if(t==="relu")return Cr(e);if(t==="elu")return Ho(e);if(t==="relu6")return cd(e);if(t==="prelu")return zu(e,n);if(t==="leakyrelu")return Mu(e,r);throw new Error(`Unknown fused activation ${t}.`)}var Hd=(e,t)=>!(e>0)||t==="linear";function UT({x:e,filter:t,strides:n,pad:r,dataFormat:a="NHWC",dilations:s=[1,1],dimRoundingMode:i,bias:o,activation:l="linear",preluActivationWeights:c,leakyreluAlpha:u}){if(l=l||"linear",Hd(z.state.gradientDepth,l)===!1){let _=Zr(e,t,n,r,a,s,i);return o!=null&&(_=oe(_,o)),Ud(_,l,c,u)}let h=R(e,"x","conv2d"),d=R(t,"filter","conv2d"),p=h,f=!1;h.rank===3&&(f=!0,p=q(h,[1,h.shape[0],h.shape[1],h.shape[2]])),M(p.rank===4,()=>`Error in fused conv2d: input must be rank 4, but got rank ${p.rank}.`),M(d.rank===4,()=>`Error in fused conv2d: filter must be rank 4, but got rank ${d.rank}.`),i!=null&&M(Ut(r),()=>`Error in fused conv2d: pad must be an integer when using, dimRoundingMode ${i} but got pad ${r}.`),M(p.shape[3]===d.shape[2],()=>`Error in conv2d: depth of input (${p.shape[3]}) must match input depth for filter ${d.shape[2]}.`),M(zr(n,s),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${s}'`),M(a==="NHWC",()=>`Error in conv2d: got dataFormat of ${a} but only NHWC is currently supported.`);let m=tc(p.shape,d.shape,n,s,r,i),A;o!=null&&(A=R(o,"bias","fused conv2d"),[A]=vt(A,h),At(m.outShape,A.shape));let y;c!=null&&(y=R(c,"prelu weights","fused conv2d"));let g=(_,I)=>{let[T,E,N,F]=I,$=Bd(_,N,l);M(Ea(s),()=>`Error in gradient of fused conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${s}'`);let D=Zm(E.shape,$,T,n,r),P=tA(E,$,T.shape,n,r),H=[D,P];if(F!=null){let V=Vd(F,$);H.push(V)}return H},w={x:p,filter:d,bias:A,preluActivationWeights:y},x={strides:n,pad:r,dataFormat:a,dilations:s,dimRoundingMode:i,activation:l,leakyreluAlpha:u};return o==null?Sr((_,I,T)=>{let E=z.runKernel(Ws,w,x);return T([I,_,E]),f&&(E=q(E,[E.shape[1],E.shape[2],E.shape[3]])),{value:E,gradFunc:g}})(p,d):Sr((_,I,T,E)=>{let N=z.runKernel(Ws,w,x);return E([I,_,N,T]),f&&(N=q(N,[N.shape[1],N.shape[2],N.shape[3]])),{value:N,gradFunc:g}})(p,d,A)}var LT=L({fusedConv2d_:UT});function HT(e,t,n,r,a,s=[1,1],i){let o=e;e.rank===3&&(o=q(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let l=t;l.rank===3&&(l=q(t,[1,t.shape[0],t.shape[1],t.shape[2]]));let c={x:o,dy:l},u={strides:r,pad:a,dimRoundingMode:i,dilations:s,filterShape:n};return z.runKernel(bh,c,u)}var Y5=L({depthwiseConv2dNativeBackpropFilter_:HT});function jT(e,t,n,r,a,s=[1,1],i){let o=t,l=!1;t.rank===3&&(l=!0,o=q(t,[1,t.shape[0],t.shape[1],t.shape[2]]));let c={dy:o,filter:n},u={strides:r,pad:a,dimRoundingMode:i,dilations:s,inputShape:e},h=z.runKernel(vh,c,u);return l?q(h,[h.shape[1],h.shape[2],h.shape[3]]):h}var Q5=L({depthwiseConv2dNativeBackpropInput_:jT});function GT({x:e,filter:t,strides:n,pad:r,dataFormat:a="NHWC",dilations:s=[1,1],dimRoundingMode:i,bias:o,activation:l="linear",preluActivationWeights:c,leakyreluAlpha:u}){if(Hd(z.state.gradientDepth,l)===!1){let _=Uo(e,t,n,r,a,s,i);return o!=null&&(_=oe(_,o)),Ud(_,l,c,u)}let h=R(e,"x","depthwiseConv2d"),d=R(t,"filter","depthwiseConv2d"),p=h,f=!1;h.rank===3&&(f=!0,p=q(h,[1,h.shape[0],h.shape[1],h.shape[2]])),M(p.rank===4,()=>`Error in fused depthwiseConv2d: input must be rank 4, but got rank ${p.rank}.`),M(d.rank===4,()=>`Error in fused depthwiseConv2d: filter must be rank 4, but got rank ${d.rank}.`),M(p.shape[3]===d.shape[2],()=>`Error in fused depthwiseConv2d: number of input channels (${p.shape[3]}) must match the inChannels dimension in filter ${d.shape[2]}.`),s==null&&(s=[1,1]),M(zr(n,s),()=>`Error in fused depthwiseConv2d: Either strides or dilations must be 1. Got strides ${n} and dilations '${s}'`),i!=null&&M(Ut(r),()=>`Error in fused depthwiseConv2d: pad must be an integer when using dimRoundingMode ${i} but got pad ${r}.`);let m=tc(p.shape,d.shape,n,s,r,i,!0),A;o!=null&&(A=R(o,"bias","fused conv2d"),[A]=vt(A,h),At(m.outShape,A.shape));let y;c!=null&&(y=R(c,"prelu weights","fused depthwiseConv2d"));let g=(_,I)=>{M(Ea(s),()=>`Error in gradient of fused depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '${s}'`);let[T,E,N,F]=I,$=Bd(_,N,l),D=Q5(E.shape,$,T,n,r,s,i),P=Y5(E,$,T.shape,n,r,s,i);if(F!=null){let H=Vd(A,$);return[D,P,H]}return[D,P]},w={x:p,filter:d,bias:A,preluActivationWeights:y},x={strides:n,pad:r,dataFormat:a,dilations:s,dimRoundingMode:i,activation:l,leakyreluAlpha:u};return o==null?Sr((_,I,T)=>{let E=z.runKernel(Bs,w,x);return T([I,_,E]),f&&(E=q(E,[E.shape[1],E.shape[2],E.shape[3]])),{value:E,gradFunc:g}})(p,d):Sr((_,I,T,E)=>{let N=z.runKernel(Bs,w,x);return E([I,_,N,T]),f&&(N=q(N,[N.shape[1],N.shape[2],N.shape[3]])),{value:N,gradFunc:g}})(p,d,A)}var WT=L({fusedDepthwiseConv2d_:GT});function qT({a:e,b:t,transposeA:n=!1,transposeB:r=!1,bias:a,activation:s="linear",preluActivationWeights:i,leakyreluAlpha:o}){if(Hd(z.state.gradientDepth,s)===!1){let F=qe(e,t,n,r);return a!=null&&(F=oe(F,a)),Ud(F,s,i,o)}let l=R(e,"a","fused matMul"),c=R(t,"b","fused matMul");[l,c]=vt(l,c);let u=n?l.shape[l.rank-2]:l.shape[l.rank-1],h=r?c.shape[c.rank-1]:c.shape[c.rank-2],d=n?l.shape[l.rank-1]:l.shape[l.rank-2],p=r?c.shape[c.rank-2]:c.shape[c.rank-1],f=l.shape.slice(0,-2),m=c.shape.slice(0,-2),A=Dt(f),y=Dt(m);M(l.rank>=2&&c.rank>=2&&l.rank===c.rank,()=>`Error in fused matMul: inputs must have the same rank of at least 2, got ranks ${l.rank} and ${c.rank}.`),M(ta(f,m),()=>`Error in fused matMul: outer dimensions (${f}) and (${m}) of Tensors with shapes ${l.shape} and ${c.shape} must match.`),M(u===h,()=>`Error in fused matMul: inner shapes (${u}) and (${h}) of Tensors with shapes ${l.shape} and ${c.shape} and transposeA=${n} and transposeB=${r} must match.`);let g=l.shape.slice(0,-2).concat([d,p]),w=n?q(l,[A,u,d]):q(l,[A,d,u]),x=r?q(c,[y,p,h]):q(c,[y,h,p]),_;a!=null&&(_=R(a,"bias","fused matMul"),[_]=vt(_,l),At(g,_.shape));let I;i!=null&&(I=R(i,"prelu weights","fused matMul"));let T=(F,$)=>{let[D,P,H,V]=$,K=Bd(q(F,H.shape),H,s),X,ee;if(!n&&!r?(X=qe(K,P,!1,!0),ee=qe(D,K,!0,!1)):!n&&r?(X=qe(K,P,!1,!1),ee=qe(K,D,!0,!1)):n&&!r?(X=qe(P,K,!1,!0),ee=qe(D,K,!1,!1)):(X=qe(P,K,!0,!0),ee=qe(K,D,!0,!0)),a!=null){let J=Vd(V,K);return[X,ee,J]}else return[X,ee]},E={a:w,b:x,bias:_,preluActivationWeights:I},N={transposeA:n,transposeB:r,activation:s,leakyreluAlpha:o};return a==null?Sr((F,$,D)=>{let P=z.runKernel(Ls,E,N);return D([F,$,P]),{value:q(P,g),gradFunc:T}})(w,x):Sr((F,$,D,P)=>{let H=z.runKernel(Ls,E,N);return P([F,$,H,D]),{value:q(H,g),gradFunc:T}})(w,x,_)}var BT=L({fusedMatMul_:qT});function XT(e){return hm(e,.54,.46)}var KT=L({hammingWindow_:XT});function ZT(e){return hm(e,.5,.5)}var ex=L({hannWindow_:ZT});function JT(e,t,n,r=!1,a=0){let s=0,i=[];for(;s+t<=e.size;)i.push(Me(e,s,t)),s+=n;if(r)for(;s<e.size;){let o=s+t-e.size,l=ct([Me(e,s,t-o),Fu([o],a)]);i.push(l),s+=n}return i.length===0?fr([],[0,t]):q(ct(i),[i.length,t])}var tx=L({frame_:JT});function YT(e,t,n,r,a=ex){r==null&&(r=g0(t));let s=tx(e,t,n),i=W(s,a(t)),o=[];for(let l=0;l<s.shape[0];l++)o.push(Vu(Me(i,[l,0],[1,t]),r));return ct(o)}var QT=L({stft_:YT});function eE(e,t,n,r,a="bilinear",s=0){let i=R(e,"image","cropAndResize"),o=R(t,"boxes","cropAndResize","float32"),l=R(n,"boxInd","cropAndResize","int32"),c=o.shape[0];M(i.rank===4,()=>`Error in cropAndResize: image must be rank 4,but got rank ${i.rank}.`),M(o.rank===2&&o.shape[1]===4,()=>`Error in cropAndResize: boxes must be have size [${c},4] but had shape ${o.shape}.`),M(l.rank===1&&l.shape[0]===c,()=>`Error in cropAndResize: boxInd must be have size [${c}] but had shape ${o.shape}.`),M(r.length===2,()=>`Error in cropAndResize: cropSize must be of length 2, but got length ${r.length}.`),M(r[0]>=1&&r[1]>=1,()=>`cropSize must be atleast [1,1], but was ${r}`),M(a==="bilinear"||a==="nearest",()=>`method must be bilinear or nearest, but was ${a}`);let u={image:i,boxes:o,boxInd:l},h={method:a,extrapolationValue:s,cropSize:r};return z.runKernel(Xi,u,h)}var tE=L({cropAndResize_:eE});function nE(e){let t=R(e,"image","flipLeftRight","float32");M(t.rank===4,()=>`Error in flipLeftRight: image must be rank 4,but got rank ${t.rank}.`);let n={image:t};return z.runKernel(to,n,{})}var rE=L({flipLeftRight_:nE});function aE(e,t,n=0,r=.5){let a=R(e,"image","rotateWithOffset","float32");M(a.rank===4,()=>`Error in rotateWithOffset: image must be rank 4,but got rank ${a.rank}.`);let s={image:a},i={radians:t,fillValue:n,center:r};return z.runKernel(Po,s,i)}var sE=L({rotateWithOffset_:aE});function ul(e,t,n,r,a,s){r==null&&(r=.5),a==null&&(a=Number.NEGATIVE_INFINITY),s==null&&(s=0);let i=e.shape[0];return n=Math.min(n,i),M(0<=r&&r<=1,()=>`iouThreshold must be in [0, 1], but was '${r}'`),M(e.rank===2,()=>`boxes must be a 2D tensor, but was of rank '${e.rank}'`),M(e.shape[1]===4,()=>`boxes must have 4 columns, but 2nd dimension was ${e.shape[1]}`),M(t.rank===1,()=>"scores must be a 1D tensor"),M(t.shape[0]===i,()=>`scores has incompatible shape with boxes. Expected ${i}, but was ${t.shape[0]}`),M(0<=s&&s<=1,()=>`softNmsSigma must be in [0, 1], but was '${s}'`),{maxOutputSize:n,iouThreshold:r,scoreThreshold:a,softNmsSigma:s}}function iE(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY){let s=R(e,"boxes","nonMaxSuppression"),i=R(t,"scores","nonMaxSuppression"),o=ul(s,i,n,r,a);n=o.maxOutputSize,r=o.iouThreshold,a=o.scoreThreshold;let l={maxOutputSize:n,iouThreshold:r,scoreThreshold:a};return z.runKernel(yo,{boxes:s,scores:i},l)}var oE=L({nonMaxSuppression_:iE});function uE(e,t,n){let r=lE(e,t,n),a=r<0?-(r+1):r;e.splice(a,0,t)}function lE(e,t,n){return hE(e,t,n||cE)}function cE(e,t){return e>t?1:e<t?-1:0}function hE(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 nx(e,t,n,r,a){return nA(e,t,n,r,a,0)}function rx(e,t,n,r,a,s){return nA(e,t,n,r,a,0,!1,s,!0)}function ax(e,t,n,r,a,s){return nA(e,t,n,r,a,s,!0)}function nA(e,t,n,r,a,s,i=!1,o=!1,l=!1){let c=[];for(let A=0;A<t.length;A++)t[A]>a&&c.push({score:t[A],boxIndex:A,suppressBeginIndex:0});c.sort(sx);let u=s>0?-.5/s:0,h=[],d=[];for(;h.length<n&&c.length>0;){let A=c.pop(),{score:y,boxIndex:g,suppressBeginIndex:w}=A;if(y<a)break;let x=!1;for(let _=h.length-1;_>=w;--_){let I=dE(e,g,h[_]);if(I>=r){x=!0;break}if(A.score=A.score*pE(r,u,I),A.score<=a)break}A.suppressBeginIndex=h.length,x||(A.score===y?(h.push(g),d.push(A.score)):A.score>a&&uE(c,A,sx))}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 dE(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]),c=Math.min(a[0],a[2]),u=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-c)*(d-u);if(p<=0||f<=0)return 0;let m=Math.max(s,c),A=Math.max(i,u),y=Math.min(o,h),g=Math.min(l,d),w=Math.max(y-m,0)*Math.max(g-A,0);return w/(p+f-w)}function pE(e,t,n){let r=Math.exp(t*n*n);return n<=e?r:0}function sx(e,t){return e.score-t.score||e.score===t.score&&t.boxIndex-e.boxIndex}async function fE(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY){let s=R(e,"boxes","nonMaxSuppressionAsync"),i=R(t,"scores","nonMaxSuppressionAsync"),o=ul(s,i,n,r,a);n=o.maxOutputSize,r=o.iouThreshold,a=o.scoreThreshold;let l=await Promise.all([s.data(),i.data()]),c=l[0],u=l[1],{selectedIndices:h}=nx(c,u,n,r,a);return s!==e&&s.dispose(),i!==t&&i.dispose(),Qt(h,"int32")}var mE=fE;function AE(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,s=0){let i=R(e,"boxes","nonMaxSuppression"),o=R(t,"scores","nonMaxSuppression"),l=ul(i,o,n,r,a,s);n=l.maxOutputSize,r=l.iouThreshold,a=l.scoreThreshold,s=l.softNmsSigma;let c={boxes:i,scores:o},u={maxOutputSize:n,iouThreshold:r,scoreThreshold:a,softNmsSigma:s},h=z.runKernel(xo,c,u);return{selectedIndices:h[0],selectedScores:h[1]}}var yE=L({nonMaxSuppressionWithScore_:AE});async function gE(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,s=0){let i=R(e,"boxes","nonMaxSuppressionAsync"),o=R(t,"scores","nonMaxSuppressionAsync"),l=ul(i,o,n,r,a,s);n=l.maxOutputSize,r=l.iouThreshold,a=l.scoreThreshold,s=l.softNmsSigma;let c=await Promise.all([i.data(),o.data()]),u=c[0],h=c[1],{selectedIndices:d,selectedScores:p}=ax(u,h,n,r,a,s);return i!==e&&i.dispose(),o!==t&&o.dispose(),{selectedIndices:Qt(d,"int32"),selectedScores:Qt(p)}}var xE=gE;function wE(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,s=!1){let i=R(e,"boxes","nonMaxSuppression"),o=R(t,"scores","nonMaxSuppression"),l=ul(i,o,n,r,a,null),c=l.maxOutputSize,u=l.iouThreshold,h=l.scoreThreshold,d={boxes:i,scores:o},p={maxOutputSize:c,iouThreshold:u,scoreThreshold:h,padToMaxOutputSize:s},f=z.runKernel(go,d,p);return{selectedIndices:f[0],validOutputs:f[1]}}var _E=L({nonMaxSuppressionPadded_:wE});async function bE(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,s=!1){let i=R(e,"boxes","nonMaxSuppressionAsync"),o=R(t,"scores","nonMaxSuppressionAsync"),l=ul(i,o,n,r,a,null),c=l.maxOutputSize,u=l.iouThreshold,h=l.scoreThreshold,[d,p]=await Promise.all([i.data(),o.data()]),{selectedIndices:f,validOutputs:m}=rx(d,p,c,u,h,s);return i!==e&&i.dispose(),o!==t&&o.dispose(),{selectedIndices:Qt(f,"int32"),validOutputs:Se(m,"int32")}}var vE=bE;function kE(e,t,n=!1,r=!1){let a=R(e,"images","resizeBilinear");M(a.rank===3||a.rank===4,()=>`Error in resizeBilinear: x must be rank 3 or 4, but got rank ${a.rank}.`),M(t.length===2,()=>`Error in resizeBilinear: new shape must 2D, but got shape ${t}.`),M(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=q(a,[1,a.shape[0],a.shape[1],a.shape[2]]));let[]=t,o={images:s},l={alignCorners:n,halfPixelCenters:r,size:t},c=z.runKernel(Is,o,l);return i?q(c,[c.shape[1],c.shape[2],c.shape[3]]):c}var ix=L({resizeBilinear_:kE});function IE(e,t,n=!1,r=!1){let a=R(e,"images","resizeNearestNeighbor");M(a.rank===3||a.rank===4,()=>`Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank ${a.rank}.`),M(t.length===2,()=>`Error in resizeNearestNeighbor: new shape must 2D, but got shape ${t}.`),M(a.dtype==="float32"||a.dtype==="int32",()=>"`images` must have `int32` or `float32` as dtype"),M(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=q(a,[1,a.shape[0],a.shape[1],a.shape[2]]));let[]=t,o={images:s},l={alignCorners:n,halfPixelCenters:r,size:t},c=z.runKernel(gu,o,l);return i?q(c,[c.shape[1],c.shape[2],c.shape[3]]):c}var ox=L({resizeNearestNeighbor_:IE});function NE(e,t,n){M(t%1==0,()=>`bandPart(): numLower must be an integer, got ${t}.`),M(n%1==0,()=>`bandPart(): numUpper must be an integer, got ${n}.`);let r=R(e,"a","bandPart");M(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 (${i}).`);t<0&&(t=s),n<0&&(n=i);let o=q(ud(0,s,1,"int32"),[-1,1]),l=ud(0,i,1,"int32"),c=we(o,l),u=nr(Hs(c,Se(+t,"int32")),_a(c,Se(-n,"int32"))),h=Ct([s,i],r.dtype);return q(Sn(rr(q(r,[-1,s,i])).map(d=>fn(u,d,h))),a)}var SE=L({bandPart_:NE});function TE(e){let t;if(Array.isArray(e)){t=!1,M(e!=null&&e.length>0,()=>"Gram-Schmidt process: input must not be null, undefined, or empty");let a=e[0].shape[0];for(let s=1;s<e.length;++s)M(e[s].shape[0]===a,()=>`Gram-Schmidt: Non-unique lengths found in the input vectors: (${e[s].shape[0]} vs. ${a})`)}else t=!0,e=an(e,e.shape[0],0).map(a=>ba(a,[0]));M(e.length<=e[0].shape[0],()=>`Gram-Schmidt: Number of vectors (${e.length}) exceeds number of dimensions (${e[0].shape[0]}).`);let n=[],r=e;for(let a=0;a<e.length;++a)n.push(z.tidy(()=>{let s=r[a];if(a>0)for(let i=0;i<a;++i){let o=W(Te(W(n[i],s)),n[i]);s=we(s,o)}return Ne(s,_d(s,"euclidean"))}));return t?Sn(n,0):n}var EE=L({gramSchmidt_:TE});function CE(e,t=!1){if(M(e.rank>=2,()=>`qr() requires input tensor to have a rank >= 2, but got rank ${e.rank}`),e.rank===2)return lx(e,t);{let n=e.shape.slice(0,e.shape.length-2).reduce((l,c)=>l*c),r=rr(q(e,[n,e.shape[e.shape.length-2],e.shape[e.shape.length-1]]),0),a=[],s=[];r.forEach(l=>{let[c,u]=lx(l,t);a.push(c),s.push(u)});let i=q(Sn(a,0),e.shape),o=q(Sn(s,0),e.shape);return[i,o]}}function lx(e,t=!1){return z.tidy(()=>{M(e.shape.length===2,()=>`qr2d() requires a 2D Tensor, but got a ${e.shape.length}D Tensor.`);let n=e.shape[0],r=e.shape[1],a=Xf(n),s=Nr(e),i=fr([[1]],[1,1]),o=Nr(i),l=n>=r?r:n;for(let c=0;c<l;++c){let u=s,h=o,d=a;[o,s,a]=z.tidy(()=>{let p=Me(s,[c,c],[n-c,1]),f=_d(p),m=Me(s,[c,c],[1,1]),A=fn(tr(m,0),fr([[-1]]),fr([[1]])),y=we(m,W(A,f)),g=Ne(p,y);g.shape[0]===1?o=Nr(i):o=ct([i,Me(g,[1,0],[g.shape[0]-1,g.shape[1]])],0);let w=_t(Ne(qe(A,y),f)),x=Me(s,[c,0],[n-c,r]),_=W(w,o),I=at(o);if(c===0)s=we(x,qe(_,qe(I,x)));else{let N=we(x,qe(_,qe(I,x)));s=ct([Me(s,[0,0],[c,r]),N],0)}let T=at(_),E=Me(a,[0,c],[n,a.shape[1]-c]);if(c===0)a=we(E,qe(qe(E,o),T));else{let N=we(E,qe(qe(E,o),T));a=ct([Me(a,[0,0],[n,c]),N],1)}return[o,s,a]}),Ce([u,h,d])}return!t&&n>r&&(a=Me(a,[0,0],[n,r]),s=Me(s,[0,0],[r,r])),[a,s]})}var RE=L({qr_:CE}),sn;(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"})(sn||(sn={}));function FE(e,t,n=sn.SUM_BY_NONZERO_WEIGHTS){let r=R(e,"losses","computeWeightedLoss"),a=null;t!=null&&(a=R(t,"weights","computeWeightedLoss"));let s=a==null?r:W(r,a);if(n===sn.NONE)return s;if(n===sn.SUM)return Te(s);if(n===sn.MEAN){if(a==null)return bt(s);{let i=r.size/a.size,o=Ne(Te(s),Te(a));return i>1?Ne(o,Se(i)):o}}if(n===sn.SUM_BY_NONZERO_WEIGHTS){if(a==null)return Ne(Te(s),Se(r.size));{let i=W(a,Er(r.shape)),o=ye(Te(js(i,Se(0))),"float32");return Ne(Te(s),o)}}throw Error(`Unknown reduction: ${n}`)}var ra=L({computeWeightedLoss_:FE});function ME(e,t,n,r=sn.SUM_BY_NONZERO_WEIGHTS){let a=R(e,"labels","absoluteDifference"),s=R(t,"predictions","absoluteDifference"),i=null;n!=null&&(i=R(n,"weights","absoluteDifference")),en(a.shape,s.shape,"Error in absoluteDifference: ");let o=$t(we(a,s));return ra(o,i,r)}var $E=L({absoluteDifference_:ME});function DE(e,t,n,r,a=sn.SUM_BY_NONZERO_WEIGHTS){let s=R(e,"labels","cosineDistance"),i=R(t,"predictions","cosineDistance"),o=null;r!=null&&(o=R(r,"weights","cosineDistance")),en(s.shape,i.shape,"Error in cosineDistance: ");let l=Se(1),c=we(l,Te(W(s,i),n,!0));return ra(c,o,a)}var OE=L({cosineDistance_:DE});function zE(e,t,n,r=sn.SUM_BY_NONZERO_WEIGHTS){let a=R(e,"labels","hingeLoss"),s=R(t,"predictions","hingeLoss"),i=null;n!=null&&(i=R(n,"weights","hingeLoss")),en(a.shape,s.shape,"Error in hingeLoss: ");let o=Se(1);a=we(W(Se(2),a),o);let l=Cr(we(o,W(a,s)));return ra(l,i,r)}var PE=L({hingeLoss_:zE});function LE(e,t,n,r=1,a=sn.SUM_BY_NONZERO_WEIGHTS){let s=R(e,"labels","huberLoss"),i=R(t,"predictions","huberLoss"),o=null;n!=null&&(o=R(n,"weights","huberLoss")),en(s.shape,i.shape,"Error in huberLoss: ");let l=Se(r),c=$t(we(i,s)),u=Xo(c,l),h=we(c,u),d=oe(W(Se(.5),ot(u)),W(l,h));return ra(d,o,a)}var WE=L({huberLoss_:LE});function BE(e,t,n,r=1e-7,a=sn.SUM_BY_NONZERO_WEIGHTS){let s=R(e,"labels","logLoss"),i=R(t,"predictions","logLoss"),o=null;n!=null&&(o=R(n,"weights","logLoss")),en(s.shape,i.shape,"Error in logLoss: ");let l=Se(1),c=Se(r),u=_t(W(s,kn(oe(i,c)))),h=W(we(l,s),kn(oe(we(l,i),c))),d=we(u,h);return ra(d,o,a)}var VE=L({logLoss_:BE});function UE(e,t,n,r=sn.SUM_BY_NONZERO_WEIGHTS){let a=R(e,"labels","meanSquaredError"),s=R(t,"predictions","meanSquaredError"),i=null;n!=null&&(i=R(n,"weights","meanSquaredError")),en(a.shape,s.shape,"Error in meanSquaredError: ");let o=gd(a,s);return ra(o,i,r)}var HE=L({meanSquaredError_:UE});function jE(e,t){let n=R(e,"labels","sigmoidCrossEntropyWithLogits"),r=R(t,"logits","sigmoidCrossEntropyWithLogits");en(n.shape,r.shape,"Error in sigmoidCrossEntropyWithLogits: ");let a=Cr(r),s=W(r,n),i=ad(Wn(_t($t(r))));return oe(we(a,s),i)}function GE(e,t,n,r=0,a=sn.SUM_BY_NONZERO_WEIGHTS){let s=R(e,"multiClassLabels","sigmoidCrossEntropy"),i=R(t,"logits","sigmoidCrossEntropy"),o=null;if(n!=null&&(o=R(n,"weights","sigmoidCrossEntropy")),en(s.shape,i.shape,"Error in sigmoidCrossEntropy: "),r>0){let c=Se(r),u=Se(1),h=Se(.5);s=oe(W(s,we(u,c)),W(h,c))}let l=jE(s,i);return ra(l,o,a)}var qE=L({sigmoidCrossEntropy_:GE});function XE(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 ${n}`);return Sr((r,a,s)=>{let i=Zf(a,[n],!0),o=we(ye(a,"float32"),i);s([r,o]);let l=_t(W(o,r));return{value:Te(l,[n]),gradFunc:(c,u)=>{let[h,d]=u,p=ei(c.shape,[n]);return[W(q(c,p),we(ye(h,"float32"),Wn(d))),W(q(c,p),we(Wn(d),ye(h,"float32")))]}}})(e,t)}function KE(e,t,n,r=0,a=sn.SUM_BY_NONZERO_WEIGHTS){let s=R(e,"onehotLabels","softmaxCrossEntropy"),i=R(t,"logits","softmaxCrossEntropy"),o=null;if(n!=null&&(o=R(n,"weights","softmaxCrossEntropy")),en(s.shape,i.shape,"Error in softmaxCrossEntropy: "),r>0){let c=Se(r),u=Se(1),h=Se(s.shape[1]);s=oe(W(s,we(u,c)),Ne(c,h))}let l=XE(s,i);return ra(l,o,a)}var ZE=L({softmaxCrossEntropy_:KE}),d8={fft:Bu,ifft:Zo,rfft:Vu,irfft:yd},p8={hammingWindow:KT,hannWindow:ex,frame:tx,stft:QT},St={flipLeftRight:rE,resizeNearestNeighbor:ox,resizeBilinear:ix,rotateWithOffset:sE,cropAndResize:tE,nonMaxSuppression:oE,nonMaxSuppressionAsync:mE,nonMaxSuppressionWithScore:yE,nonMaxSuppressionWithScoreAsync:xE,nonMaxSuppressionPadded:_E,nonMaxSuppressionPaddedAsync:vE},x0={bandPart:SE,gramSchmidt:EE,qr:RE},f8={absoluteDifference:$E,computeWeightedLoss:ra,cosineDistance:OE,hingeLoss:PE,huberLoss:WE,logLoss:VE,meanSquaredError:HE,sigmoidCrossEntropy:qE,softmaxCrossEntropy:ZE},Qr=class extends W5{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 Ce(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 i0(e,t)}dispose(){this.iterations_!=null&&Ce(this.iterations_)}async saveIterations(){return this.iterations_==null&&(this.iterations_=0),{name:"iter",tensor:Se(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 ${this.getClassName()}`)}async extractIterations(e){return this.iterations_=(await e[0].tensor.data())[0],e.slice(1)}};Object.defineProperty(Qr,Symbol.hasInstance,{value:e=>e.minimize!=null&&e.computeGradients!=null&&e.applyGradients!=null});var bd=class extends Qr{constructor(e,t,n=null){super();this.learningRate=e,this.rho=t,this.epsilon=n,this.accumulatedGrads=[],this.accumulatedUpdates=[],n==null&&(this.epsilon=z.backend.epsilon())}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let r=z.registeredVariables[t],a=!1;this.accumulatedGrads[n]==null&&(this.accumulatedGrads[n]={originalName:`${t}/accum_grad`,variable:U(()=>He(r).variable(a))}),this.accumulatedUpdates[n]==null&&(this.accumulatedUpdates[n]={originalName:`${t}/accum_var`,variable:U(()=>He(r).variable(a))});let s=Array.isArray(e)?e[n].tensor:e[t];if(s==null)return;let i=this.accumulatedGrads[n].variable,o=this.accumulatedUpdates[n].variable;U(()=>{let l=oe(W(i,this.rho),W(ot(s),1-this.rho)),c=W(Ne(Xt(oe(o,this.epsilon)),Xt(oe(i,this.epsilon))),s),u=oe(W(o,this.rho),W(ot(c),1-this.rho));i.assign(l),o.assign(u);let h=oe(W(c,-this.learningRate),r);r.assign(h)})}),this.incrementIterations()}dispose(){this.accumulatedUpdates!=null&&(Ce(this.accumulatedGrads.map(e=>e.variable)),Ce(this.accumulatedUpdates.map(e=>e.variable)))}async getWeights(){let e=[...this.accumulatedGrads,...this.accumulatedUpdates];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=e.length/2,n=!1;this.accumulatedGrads=e.slice(0,t).map(r=>({originalName:r.name,variable:r.tensor.variable(n)})),this.accumulatedUpdates=e.slice(t,t*2).map(r=>({originalName:r.name,variable:r.tensor.variable(n)}))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}};bd.className="Adadelta";Ta(bd);var vd=class extends Qr{constructor(e,t=.1){super();this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let r=z.registeredVariables[t];if(this.accumulatedGrads[n]==null){let i=!1;this.accumulatedGrads[n]={originalName:`${t}/accumulator`,variable:U(()=>Fu(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;U(()=>{let i=oe(s,ot(a));s.assign(i);let o=oe(W(Ne(a,Xt(oe(i,z.backend.epsilon()))),-this.learningRate),r);r.assign(o)})}),this.incrementIterations()}dispose(){this.accumulatedGrads!=null&&Ce(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)}};vd.className="Adagrad";Ta(vd);var kd=class extends Qr{constructor(e,t,n,r=null){super();this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=r,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],U(()=>{this.accBeta1=Se(t).variable(),this.accBeta2=Se(n).variable()}),r==null&&(this.epsilon=z.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);U(()=>{let n=we(1,this.accBeta1),r=we(1,this.accBeta2);t.forEach((a,s)=>{let i=z.registeredVariables[a],o=!1;this.accumulatedFirstMoment[s]==null&&(this.accumulatedFirstMoment[s]={originalName:`${a}/m`,variable:U(()=>He(i).variable(o))}),this.accumulatedSecondMoment[s]==null&&(this.accumulatedSecondMoment[s]={originalName:`${a}/v`,variable:U(()=>He(i).variable(o))});let l=Array.isArray(e)?e[s].tensor:e[a];if(l==null)return;let c=this.accumulatedFirstMoment[s].variable,u=this.accumulatedSecondMoment[s].variable,h=oe(W(c,this.beta1),W(l,1-this.beta1)),d=oe(W(u,this.beta2),W(ot(l),1-this.beta2)),p=Ne(h,n),f=Ne(d,r);c.assign(h),u.assign(d);let m=oe(W(Ne(p,oe(Xt(f),this.epsilon)),-this.learningRate),i);i.assign(m)}),this.accBeta1.assign(W(this.accBeta1,this.beta1)),this.accBeta2.assign(W(this.accBeta2,this.beta2))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),this.accumulatedFirstMoment!=null&&Ce(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedSecondMoment!=null&&Ce(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),U(()=>{this.accBeta1.assign(Yr(this.beta1,this.iterations_+1)),this.accBeta2.assign(Yr(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)}};kd.className="Adam";Ta(kd);var Id=class extends Qr{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=[],U(()=>{this.iteration=Se(0).variable(),this.accBeta1=Se(t).variable()}),r==null&&(this.epsilon=z.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);U(()=>{let n=we(1,this.accBeta1),r=Ne(-this.learningRate,oe(W(this.iteration,this.decay),1));t.forEach((a,s)=>{let i=z.registeredVariables[a],o=!1;this.accumulatedFirstMoment[s]==null&&(this.accumulatedFirstMoment[s]={originalName:`${a}/m`,variable:He(i).variable(o)}),this.accumulatedWeightedInfNorm[s]==null&&(this.accumulatedWeightedInfNorm[s]={originalName:`${a}/v`,variable:He(i).variable(o)});let l=Array.isArray(e)?e[s].tensor:e[a];if(l==null)return;let c=this.accumulatedFirstMoment[s].variable,u=this.accumulatedWeightedInfNorm[s].variable,h=oe(W(c,this.beta1),W(l,1-this.beta1)),d=W(u,this.beta2),p=$t(l),f=Tr(d,p);c.assign(h),u.assign(f);let m=oe(W(Ne(r,n),Ne(h,oe(f,this.epsilon))),i);i.assign(m)}),this.iteration.assign(oe(this.iteration,1)),this.accBeta1.assign(W(this.accBeta1,this.beta1))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),this.accumulatedFirstMoment!=null&&Ce(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedWeightedInfNorm!=null&&Ce(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)}};Id.className="Adamax";Ta(Id);var Uu=class extends Qr{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=z.registeredVariables[t];U(()=>{let s=oe(W(this.c,r),a);a.assign(s)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=Bt(Se(-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)}};Uu.className="SGD";Ta(Uu);var Nd=class extends Uu{constructor(e,t,n=!1){super(e);this.learningRate=e,this.momentum=t,this.useNesterov=n,this.accumulations=[],this.m=Se(this.momentum)}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let r=z.registeredVariables[t];if(this.accumulations[n]==null){let i=!1;this.accumulations[n]={originalName:`${t}/momentum`,variable:U(()=>He(r).variable(i))}}let a=this.accumulations[n].variable,s=Array.isArray(e)?e[n].tensor:e[t];s!=null&&U(()=>{let i,o=oe(W(this.m,a),s);this.useNesterov?i=oe(W(this.c,oe(s,W(o,this.m))),r):i=oe(W(this.c,o),r),a.assign(o),r.assign(i)})}),this.incrementIterations()}dispose(){this.m.dispose(),this.accumulations!=null&&Ce(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)}};Nd.className="Momentum";Ta(Nd);var Sd=class extends Qr{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=z.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=z.registeredVariables[t],a=!1;this.accumulatedMeanSquares[n]==null&&(this.accumulatedMeanSquares[n]={originalName:`${t}/rms`,variable:U(()=>He(r).variable(a))}),this.accumulatedMoments[n]==null&&(this.accumulatedMoments[n]={originalName:`${t}/momentum`,variable:U(()=>He(r).variable(a))}),this.accumulatedMeanGrads[n]==null&&this.centered&&(this.accumulatedMeanGrads[n]={originalName:`${t}/mg`,variable:U(()=>He(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;U(()=>{let l=oe(W(i,this.decay),W(ot(s),1-this.decay));if(this.centered){let c=this.accumulatedMeanGrads[n].variable,u=oe(W(c,this.decay),W(s,1-this.decay)),h=Ne(W(s,this.learningRate),Xt(we(l,oe(ot(u),this.epsilon)))),d=oe(W(o,this.momentum),h);i.assign(l),c.assign(u),o.assign(d);let p=we(r,d);r.assign(p)}else{let c=oe(W(i,this.decay),W(ot(s),1-this.decay)),u=oe(W(o,this.momentum),Ne(W(s,this.learningRate),Xt(oe(c,this.epsilon))));i.assign(c),o.assign(u);let h=we(r,u);r.assign(h)}})}),this.incrementIterations()}dispose(){this.accumulatedMeanSquares!=null&&Ce(this.accumulatedMeanSquares.map(e=>e.variable)),this.accumulatedMeanGrads!=null&&this.centered&&Ce(this.accumulatedMeanGrads.map(e=>e.variable)),this.accumulatedMoments!=null&&Ce(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)}};Sd.className="RMSProp";Ta(Sd);var ti=class{static sgd(e){return new Uu(e)}static momentum(e,t,n=!1){return new Nd(e,t,n)}static rmsprop(e,t=.9,n=0,r=null,a=!1){return new Sd(e,t,n,r,a)}static adam(e=.001,t=.9,n=.999,r=null){return new kd(e,t,n,r)}static adadelta(e=.001,t=.95,n=null){return new bd(e,t,n)}static adamax(e=.002,t=.9,n=.999,r=null,a=0){return new Id(e,t,n,r,a)}static adagrad(e,t=.1){return new vd(e,t)}},Gs={sgd:ti.sgd,momentum:ti.momentum,adadelta:ti.adadelta,adagrad:ti.adagrad,rmsprop:ti.rmsprop,adamax:ti.adamax,adam:ti.adam},JE=(()=>typeof requestAnimationFrame!="undefined"?requestAnimationFrame:typeof setImmediate!="undefined"?setImmediate:e=>e())();function Td(){return new Promise(e=>JE(()=>e()))}var C={};ze(C,{ERF_A1:()=>lC,ERF_A2:()=>uC,ERF_A3:()=>cC,ERF_A4:()=>hC,ERF_A5:()=>dC,ERF_P:()=>oC,PARALLELIZE_THRESHOLD:()=>rA,SELU_SCALE:()=>cx,SELU_SCALEALPHA:()=>ux,applyActivation:()=>Ud,assertAndGetBroadcastShape:()=>At,assertAxesAreInnerMostDims:()=>nS,assertParamsConsistent:()=>YE,assignToTypedArray:()=>wC,axesAreInnerMostDims:()=>Jm,calculateShapes:()=>T5,combineLocations:()=>q5,complexWithEvenIndex:()=>yC,complexWithOddIndex:()=>gC,computeConv2DInfo:()=>tc,computeConv3DInfo:()=>j5,computeDefaultPad:()=>Km,computeDilation2DInfo:()=>MI,computeOptimalWindowSize:()=>eC,computeOutAndReduceShapes:()=>X5,computeOutShape:()=>QE,computePool2DInfo:()=>H5,computePool3DInfo:()=>$I,convertConv2DDataFormat:()=>U5,eitherStridesOrDilationsAreOne:()=>zr,expandShapeToKeepDim:()=>ei,exponent:()=>bC,exponents:()=>_C,fromStringArrayToUint8:()=>IC,fromUint8ToStringArray:()=>kC,getAxesPermutation:()=>K5,getBroadcastDims:()=>bN,getComplexWithIndex:()=>xC,getFusedBiasGradient:()=>Vd,getFusedDyActivation:()=>Bd,getImageCenter:()=>tC,getInnerMostAxes:()=>rS,getPermuted:()=>rC,getReductionAxes:()=>Ot,getReshaped:()=>nC,getReshapedPermuted:()=>aC,getSliceBeginCoords:()=>sC,getSliceSize:()=>iC,getUndoAxesPermutation:()=>Ym,log:()=>fC,mergeRealAndImagArrays:()=>mC,prepareAndValidate:()=>S5,prepareSplitSize:()=>vC,segment_util:()=>hx,shouldFuse:()=>Hd,slice_util:()=>rn,splitRealAndImagArrays:()=>AC,tupleValuesAreOne:()=>Ea,upcastType:()=>Qn,validateInput:()=>Hm,validateUpdateShape:()=>Um,warn:()=>pC});function YE(e,t){let n=e[0].length;e.forEach((a,s)=>{M(a.length===n,()=>`Error in concat${n}D: rank of tensors[${s}] must be the same as the rank of the rest (${n})`)}),M(t>=0&&t<n,()=>`Error in concat${n}D: axis must be between 0 and ${n-1}.`);let r=e[0];e.forEach((a,s)=>{for(let i=0;i<n;i++)M(i===t||a[i]===r[i],()=>`Error in concat${n}D: Shape of tensors[${s}] (${a}) does not match the shape of the rest (${r}) along the non-concatenated axis ${s}.`)})}function QE(e,t){let n=e[0].slice();for(let r=1;r<e.length;r++)n[t]+=e[r][t];return n}var rA=30;function eC(e){return e<=rA?e:Rd(e,Math.floor(Math.sqrt(e)))}function tC(e,t,n){let r=n*(typeof e=="number"?e:e[0]),a=t*(typeof e=="number"?e:e[1]);return[r,a]}function nC(e,t,n,r=!0){let a=[];if(r)a=a.concat(t.slice(0)),a.push(e[0]/n),a=a.concat(e.slice(1));else{a=a.concat(e[0]);let s=t.length;for(let i=0;i<s;++i)a=a.concat([e[i+1]/t[i],t[i]]);a=a.concat(e.slice(s+1))}return a}function rC(e,t,n=!0){let r=[];if(n){r.push(t);for(let a=t+1;a<e;++a)a<=2*t?(r.push(a),r.push(a-(t+1))):r.push(a)}else{let a=[],s=[];for(let i=1;i<e;++i)i>=t*2+1||i%2==1?s.push(i):a.push(i);r.push(...a),r.push(0),r.push(...s)}return r}function aC(e,t,n,r=!0){let a=[];r?a.push(e[0]/n):a.push(e[0]*n);for(let s=1;s<e.length;++s)s<=t.length?r?a.push(t[s-1]*e[s]):a.push(e[s]/t[s-1]):a.push(e[s]);return a}function sC(e,t){let n=[0];for(let r=0;r<t;++r)n.push(e[r][0]);return n}function iC(e,t,n){let r=e.slice(0,1);for(let a=0;a<n;++a)r.push(e[a+1]-t[a][0]-t[a][1]);return r}var ux=1.7580993408473768,cx=1.0507009873554805,oC=.3275911,lC=.254829592,uC=-.284496736,cC=1.421413741,hC=-1.453152027,dC=1.061405429;function pC(...e){Q().getBool("IS_TEST")||console.warn(...e)}function fC(...e){Q().getBool("IS_TEST")||console.log(...e)}function mC(e,t){if(e.length!==t.length)throw new Error(`Cannot merge real and imag arrays of different lengths. real:${e.length}, imag: ${t.length}.`);let n=new Float32Array(e.length*2);for(let r=0;r<n.length;r+=2)n[r]=e[r/2],n[r+1]=t[r/2];return n}function AC(e){let t=new Float32Array(e.length/2),n=new Float32Array(e.length/2);for(let r=0;r<e.length;r+=2)t[r/2]=e[r],n[r/2]=e[r+1];return{real:t,imag:n}}function yC(e){let t=Math.ceil(e.length/4),n=new Float32Array(t),r=new Float32Array(t);for(let a=0;a<e.length;a+=4)n[Math.floor(a/4)]=e[a],r[Math.floor(a/4)]=e[a+1];return{real:n,imag:r}}function gC(e){let t=Math.floor(e.length/4),n=new Float32Array(t),r=new Float32Array(t);for(let a=2;a<e.length;a+=4)n[Math.floor(a/4)]=e[a],r[Math.floor(a/4)]=e[a+1];return{real:n,imag:r}}function xC(e,t){let n=e[t*2],r=e[t*2+1];return{real:n,imag:r}}function wC(e,t,n,r){e[r*2]=t,e[r*2+1]=n}function _C(e,t){let n=new Float32Array(e/2),r=new Float32Array(e/2);for(let a=0;a<Math.ceil(e/2);a++){let s=(t?2:-2)*Math.PI*(a/e);n[a]=Math.cos(s),r[a]=Math.sin(s)}return{real:n,imag:r}}function bC(e,t,n){let r=(n?2:-2)*Math.PI*(e/t),a=Math.cos(r),s=Math.sin(r);return{real:a,imag:s}}function vC(e,t,n=0){let r=[];if(typeof t=="number")M(e.shape[n]%t==0,()=>"Number of splits must evenly divide the axis."),r=new Array(t).fill(e.shape[n]/t);else{let a=t.reduce((i,o)=>(o===-1&&(i+=1),i),0);M(a<=1,()=>"There should be only one negative value in split array.");let s=t.indexOf(-1);if(s!==-1){let i=t.reduce((o,l)=>l>0?o+l:o);t[s]=e.shape[n]-i}M(e.shape[n]===t.reduce((i,o)=>i+o),()=>"The sum of sizes must match the size of the axis dimension."),r=t}return r}var hx={};ze(hx,{collectGatherOpShapeInfo:()=>TC,computeOutShape:()=>SC,segOpComputeOptimalWindowSize:()=>NC});function NC(e,t){let n=!1,r;for(e<=rA?(r=e,n=!0):r=Rd(e,Math.floor(Math.sqrt(e)));!n;)r>t||r===e?n=!0:r=Rd(e,r+1);return r}function SC(e,t,n){let r=[],a=e.length;for(let s=0;s<a;s++)s!==t?r.push(e[s]):r.push(n);return r}function TC(e,t,n,r){let a=t.shape.length,s=e.shape.length;if(r!==0&&(r<-a||r>a))throw new Error(`Expect batchDims in the range of [-${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}]: ${t.shape[h]}.`);let i=e.shape[n],o=[],l=1,c=1,u=1;for(let h=0;h<r;++h)o.push(e.shape[h]),l*=e.shape[h];for(let h=r;h<n;h++)o.push(e.shape[h]),c*=e.shape[h];for(let h=r;h<a;h++)o.push(t.shape[h]);for(let h=n+1;h<s;h++)o.push(e.shape[h]),u*=e.shape[h];return{batchSize:l,sliceSize:u,outerSize:c,dimSize:i,outputShape:o}}function kC(e){try{return e.map(t=>$d(t))}catch(t){throw new Error(`Failed to decode encoded string bytes into utf-8, error: ${t}`)}}function IC(e){return e.map(t=>Xu(t))}var Rr={};ze(Rr,{nonMaxSuppressionV3Impl:()=>nx,nonMaxSuppressionV4Impl:()=>rx,nonMaxSuppressionV5Impl:()=>ax,whereImpl:()=>Z5});function ve(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&v.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the CPU backend.`)})}var EC=Rr.whereImpl,w0=class extends au{constructor(){super();this.blockSize=48,this.firstUse=!0,this.data=new hh(this,Ln())}write(e,t,n){this.firstUse&&(this.firstUse=!1,Q().get("IS_NODE")&&C.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={};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}}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){this.data.set(e,{values:t,dtype:r,refCount:1})}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 C.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 We(e.shape,e.dtype,n)}makeOutput(e,t,n){let r=this.write(e,t,n);return Ln().makeTensorFromDataId(r,t,n,this)}disposeData(e){if(this.data.has(e)){let{complexTensorInfos:t}=this.data.get(e);t!=null&&(this.disposeData(t.real.dataId),this.disposeData(t.imag.dataId)),this.data.delete(e)}}disposeIntermediateTensorInfo(e){let t=e.dataId;if(this.data.has(t)){let n=this.data.get(t);n.refCount--,n.refCount<1&&this.disposeData(t)}}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){ve([e],"where");let t=this.readSync(e.dataId);return EC(e.shape,t)}dispose(){}floatPrecision(){return 32}epsilon(){return super.epsilon()}},dm={};ze(dm,{addImpl:()=>px,bincountImpl:()=>aA,bincountReduceImpl:()=>fx,ceilImpl:()=>mx,concatImpl:()=>sA,expImpl:()=>Ax,expm1Impl:()=>yx,floorImpl:()=>gx,gatherV2Impl:()=>xx,greaterImpl:()=>wx,lessImpl:()=>_x,linSpaceImpl:()=>bx,logImpl:()=>vx,maxImpl:()=>kx,maximumImpl:()=>Ix,minimumImpl:()=>Nx,multiplyImpl:()=>iA,negImpl:()=>Sx,notEqualImpl:()=>Tx,prodImpl:()=>Ex,rangeImpl:()=>lA,rsqrtImpl:()=>Cx,simpleAbsImpl:()=>dx,sliceImpl:()=>jd,squaredDifferenceImpl:()=>Rx,stridedSliceImpl:()=>Fx,subImpl:()=>Mx,tileImpl:()=>$x,topKImpl:()=>Dx,transposeImpl:()=>oA,uniqueImpl:()=>Ox});function dx(e){let t=new Float32Array(e.length);for(let n=0;n<e.length;++n)t[n]=Math.abs(e[n]);return t}var CC=e=>{let{x:t}=e.inputs,n=e.backend;ve(t,"abs");let r=new Float32Array(v.sizeFromShape(t.shape)),a=n.data.get(t.dataId).values;return r=dx(a),n.makeOutput(r,t.shape,"float32")},RC={kernelName:zi,backendName:"cpu",kernelFunc:CC};function Rt(e){return(t,n,r,a,s)=>{let i=C.assertAndGetBroadcastShape(t,n),o=i.length,l=v.computeStrides(i),c=v.sizeFromShape(i),u=v.getTypedArrayFromDType(s,c),h=t.length,d=n.length,p=v.computeStrides(t),f=v.computeStrides(n),m=C.getBroadcastDims(t,i),A=C.getBroadcastDims(n,i);if(m.length+A.length===0)for(let y=0;y<u.length;++y)u[y]=e(r[y%r.length],a[y%a.length]);else for(let y=0;y<u.length;++y){let g=v.indexToLoc(y,o,l),w=g.slice(-h);m.forEach(T=>w[T]=0);let x=v.locToIndex(w,h,p),_=g.slice(-d);A.forEach(T=>_[T]=0);let I=v.locToIndex(_,d,f);u[y]=e(r[x],a[I])}return[u,i]}}function Tn(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 FC={kernelName:yh,backendName:"cpu",kernelFunc:Tn};function Gd(e,t,n="float32"){if(n==="complex64"){let a=Gd(e,t,"float32"),s=Gd(e,t,"float32");return Tn({inputs:{real:a,imag:s},backend:e})}let r=v.makeZerosTypedArray(v.sizeFromShape(t),n);return e.makeTensorInfo(t,n,r)}function Pr(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 MC={kernelName:so,backendName:"cpu",kernelFunc:Pr};function ni(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 $C={kernelName:zh,backendName:"cpu",kernelFunc:ni};function Ca(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dtype:s}=r;if(s==="complex64"){if(a.dtype==="complex64")return Pr({inputs:{x:a},backend:n});let i=Gd(n,a.shape,a.dtype),o=Ca({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=Tn({inputs:{real:o,imag:i},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=ni({inputs:{input:a},backend:n}),o=Ca({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=Pr({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,c]=Rt((u,h)=>u!==h?1:0)(a.shape,[],i,o,"bool");return n.makeTensorInfo(c,"bool",l)}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var DC={kernelName:Qa,backendName:"cpu",kernelFunc:Ca};function Ht(e,t,n,r){return n==null?({inputs:a,backend:s})=>{let{a:i,b:o}=a,l=s;ve([i,o],e);let c=l.data.get(i.dataId).values,u=l.data.get(o.dataId).values,h=r||i.dtype,[d,p]=t(i.shape,o.shape,c,u,h);return l.makeTensorInfo(p,h,d)}:({inputs:a,backend:s})=>{let{a:i,b:o}=a,l=s;if(i.dtype==="complex64"||o.dtype==="complex64"){let c=Ca({inputs:{x:i},backend:l,attrs:{dtype:"complex64"}}),u=l.data.get(c.dataId),h=u.complexTensorInfos.real,d=u.complexTensorInfos.imag,p=l.data.get(h.dataId).values,f=l.data.get(d.dataId).values,m=Ca({inputs:{x:o},backend:l,attrs:{dtype:"complex64"}}),A=l.data.get(m.dataId),y=A.complexTensorInfos.real,g=A.complexTensorInfos.imag,w=l.data.get(y.dataId).values,x=l.data.get(g.dataId).values,[_,I,T]=n(i.shape,o.shape,p,f,w,x),E=l.makeTensorInfo(T,"float32",_),N=l.makeTensorInfo(T,"float32",I),F=Tn({inputs:{real:E,imag:N},backend:l});return l.disposeIntermediateTensorInfo(c),l.disposeIntermediateTensorInfo(m),l.disposeIntermediateTensorInfo(E),l.disposeIntermediateTensorInfo(N),F}else{let c=l.data.get(i.dataId).values,u=l.data.get(o.dataId).values,h=r||i.dtype,[d,p]=t(i.shape,o.shape,c,u,h);return l.makeTensorInfo(p,h,d)}}}function uA(e){return(t,n,r,a,s,i)=>{let o=C.assertAndGetBroadcastShape(t,n),l=v.sizeFromShape(o),c=o.length,u=v.computeStrides(o),h=v.getTypedArrayFromDType("float32",l),d=v.getTypedArrayFromDType("float32",l),p=C.getBroadcastDims(t,o),f=C.getBroadcastDims(n,o),m=C.mergeRealAndImagArrays(r,a),A=C.mergeRealAndImagArrays(s,i),y=t.length,g=v.computeStrides(t),w=n.length,x=v.computeStrides(n);if(p.length+f.length===0)for(let _=0;_<h.length;_++){let I=_%m.length,T=_%A.length,E=e(m[I*2],m[I*2+1],A[T*2],A[T*2+1]);h[_]=E.real,d[_]=E.imag}else for(let _=0;_<h.length;_++){let I=v.indexToLoc(_,c,u),T=I.slice(-y);p.forEach(D=>T[D]=0);let E=v.locToIndex(T,y,g),N=I.slice(-w);f.forEach(D=>N[D]=0);let F=v.locToIndex(N,w,x),$=e(m[E*2],m[E*2+1],A[F*2],A[F*2+1]);h[_]=$.real,d[_]=$.imag}return[h,d,o]}}var px=Rt((e,t)=>e+t),OC=uA((e,t,n,r)=>({real:e+n,imag:t+r})),nc=Ht(fa,px,OC),zC={kernelName:fa,backendName:"cpu",kernelFunc:nc};function aA(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 fx(e,t,n,r=!1){let a=e.shape[0],s=e.shape[1],i=We([a,n],t.dtype);for(let o=0;o<a;o++)for(let l=0;l<s;l++){let c=e.get(o,l);if(c<0)throw new Error("Input x must be non-negative!");c>=n||(r?i.set(1,o,c):t.size>0?i.set(i.get(o,c)+t.get(o,l),o,c):i.set(i.get(o,c)+1,o,c))}return i}function cl(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 st(e,t,n){return({inputs:r,attrs:a,backend:s})=>{let{x:i}=r;if(ve(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,c=v.sizeFromShape(i.shape),u=n||i.dtype,h=v.getArrayFromDType(u,c);for(let d=0;d<c;++d)h[d]=t(l[d],a);return o.makeTensorInfo(i.shape,u,h)}}function hl(e,t,n){return({inputs:r,attrs:a,backend:s})=>{let{x:i}=r;if(ve(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,c=n||i.dtype,u=t(l,c,a);return o.makeTensorInfo(i.shape,c,u)}}var mx=cl(e=>Math.ceil(e)),PC=hl(ji,mx),LC={kernelName:ji,backendName:"cpu",kernelFunc:PC};function sA(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"?C.fromUint8ToStringArray(i.vals):i.vals,l=0;for(let c=0;c<i.shape[0];++c){let u=c*t[1]+s;for(let h=0;h<i.shape[1];++h)a[u+h]=o[l++]}s+=i.shape[1]})}return a}var Ax=cl(e=>Math.exp(e)),zx=hl(is,Ax),WC={kernelName:is,backendName:"cpu",kernelFunc:zx},yx=cl(e=>Math.expm1(e)),BC=hl(eo,yx),VC={kernelName:eo,backendName:"cpu",kernelFunc:BC},gx=cl(e=>Math.floor(e)),UC=hl(os,gx),HC={kernelName:os,backendName:"cpu",kernelFunc:UC};function xx(e,t,n){let r=We(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 c=e.locToIndex(s);r.values[a]=e.values[c]}return r}var wx=Rt((e,t)=>e>t?1:0),jC=Ht(ao,wx,null,"bool"),GC={kernelName:ao,backendName:"cpu",kernelFunc:jC},_x=Rt((e,t)=>e<t?1:0),qC=Ht(uo,_x,null,"bool"),XC={kernelName:uo,backendName:"cpu",kernelFunc:qC};function bx(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 vx=cl(e=>Math.log(e)),KC=hl(ds,vx),ZC={kernelName:ds,backendName:"cpu",kernelFunc:KC};function kx(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 c=e[i+l];c>o&&(o=c)}a[s]=o}return a}var Ix=Rt((e,t)=>Math.max(e,t)),JC=Ht(fs,Ix),YC={kernelName:fs,backendName:"cpu",kernelFunc:JC},Nx=Rt((e,t)=>Math.min(e,t)),QC=Ht(gs,Nx),eR={kernelName:gs,backendName:"cpu",kernelFunc:QC},iA=Rt((e,t)=>e*t),tR=uA((e,t,n,r)=>({real:e*n-t*r,imag:e*r+t*n})),cA=Ht(xs,iA,tR),nR={kernelName:xs,backendName:"cpu",kernelFunc:cA};function Sx(e,t,n){let r=v.createScalarValue(-1,n);return iA([],t,r,e,n)}function rR(e){let{inputs:t,backend:n}=e,{x:r}=t;ve(r,"neg");let a=n.data.get(r.dataId).values,[s,i]=Sx(a,r.shape,r.dtype);return n.makeTensorInfo(i,r.dtype,s)}var aR={kernelName:mo,backendName:"cpu",kernelFunc:rR},Tx=Rt((e,t)=>e!==t?1:0),sR=Ht(Ao,Tx,null,"bool"),iR={kernelName:Ao,backendName:"cpu",kernelFunc:sR};function oA(e,t,n,r,a){let s=t.length,i=v.sizeFromShape(t),o=v.computeStrides(t),l=v.computeStrides(a),c=v.getTypedArrayFromDType(n,v.sizeFromShape(a));for(let u=0;u<i;++u){let h=v.indexToLoc(u,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);c[p]=e[u]}return c}function sr(e){let{inputs:t,attrs:n,backend:r}=e,{x:a}=t,{perm:s}=n;ve(a,"transpose");let i=a.shape.length,o=new Array(i);for(let u=0;u<o.length;u++)o[u]=a.shape[s[u]];let l=r.data.get(a.dataId).values,c=oA(l,a.shape,a.dtype,s,o);return{dataId:r.write(c,o,a.dtype),shape:o,dtype:a.dtype}}var oR={kernelName:Ps,backendName:"cpu",kernelFunc:sr};function Ex(e,t,n,r){let[a,s]=C.computeOutAndReduceShapes(e,r),i=Qn(t,"int32"),o=v.makeZerosTypedArray(v.sizeFromShape(a),i),l=v.sizeFromShape(s);for(let c=0;c<o.length;++c){let u=c*l,h=1;for(let d=0;d<l;++d)h*=n[u+d];o[c]=h}return{outVals:o,outShape:a,outDtype:i}}function lR(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;ve(a,"prod");let o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=C.getAxesPermutation(l,o),u=l,h=a,d=[];c!=null&&(h=sr({inputs:{x:a},backend:n,attrs:{perm:c}}),d.push(h),u=C.getInnerMostAxes(u.length,o));let p=n.data.get(h.dataId).values,{outVals:f,outShape:m,outDtype:A}=Ex(h.shape,h.dtype,p,u),y=m;return i&&(y=C.expandShapeToKeepDim(m,l)),d.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.makeTensorInfo(y,A,f)}var uR={kernelName:bo,backendName:"cpu",kernelFunc:lR};function lA(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 c=1;c<l.length;c++)l[c]=l[c-1]+n;return l}var Cx=cl(e=>1/Math.sqrt(e)),cR=hl(Es,Cx),hR={kernelName:Es,backendName:"cpu",kernelFunc:cR};function jd(e,t,n,r,a){let s=rn.isSliceContinous(r,t,n),i=v.sizeFromShape(n),o=v.computeStrides(r);if(s){let h=rn.computeFlatOffset(t,o);return a==="string"?e.slice(h,h+i):e.subarray(h,h+i)}let l=a==="string"?C.fromUint8ToStringArray(e):e,c=We(r,a,l),u=We(n,a);for(let h=0;h<u.size;++h){let d=u.indexToLoc(h),p=d.map((f,m)=>f+t[m]);u.set(c.get(...p),...d)}return a==="string"?C.fromStringArrayToUint8(u.values):u.values}function ri(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,size:i}=r;ve(a,"slice");let[o,l]=rn.parseSliceParams(a,s,i);rn.assertParamsValid(a,o,l);let c=n.data.get(a.dataId).values,u=jd(c,o,l,a.shape,a.dtype);return n.makeTensorInfo(l,a.dtype,u)}var dR={kernelName:To,backendName:"cpu",kernelFunc:ri},Rx=Rt((e,t)=>{let n=e-t;return n*n}),pR=Ht(Ds,Rx),fR={kernelName:Ds,backendName:"cpu",kernelFunc:pR};function Fx(e,t,n,r){let a=We(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 Mx=Rt((e,t)=>e-t),mR=uA((e,t,n,r)=>({real:e-n,imag:t-r})),hA=Ht(Os,Mx,mR),AR={kernelName:Os,backendName:"cpu",kernelFunc:hA};function $x(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=We(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 Dx(e,t,n,r,a){let s=t[t.length-1],[i,o]=[e.length/s,s],l=v.getTypedArrayFromDType(n,i*r),c=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,w)=>w.value-g.value);let m=h*r,A=l.subarray(m,m+r),y=c.subarray(m,m+r);for(let g=0;g<r;g++)A[g]=f[g].value,y[g]=f[g].index}let u=t.slice();return u[u.length-1]=r,[We(u,n,l),We(u,"int32",c)]}function Ox(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 Mt(s,r,e),c=[],u=s[0]===1&&s[2]===1;for(let f=0;f<n[a];f++){let m;if(u)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,c.push(f)}}let h=s.slice();h[1]=Object.keys(i).length;let d=new Mt(h,r);c.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 _0="3.0.0";Iu("cpu",()=>new w0,1);var Px=st(Zi,e=>e>=0?e:Math.exp(e)-1),yR={kernelName:Zi,backendName:"cpu",kernelFunc:Px};function Lx(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{alpha:s}=r;ve([a],"leakyRelu");let i=v.sizeFromShape(a.shape),o=n.data.get(a.dataId).values,l=v.getTypedArrayFromDType("float32",i);for(let c=0;c<o.length;c++)l[c]=o[c]<0?s*o[c]:o[c];return n.makeTensorInfo(a.shape,"float32",l)}var gR={kernelName:hs,backendName:"cpu",kernelFunc:Lx},xR=Rt((e,t)=>e<0?t*e:e);function Wx(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t;ve([r,a],"prelu");let s=n.data.get(r.dataId).values,i=n.data.get(a.dataId).values,[o,l]=xR(r.shape,a.shape,s,i,r.dtype);return n.makeTensorInfo(l,r.dtype,o)}var wR={kernelName:vs,backendName:"cpu",kernelFunc:Wx},Bx=st(ks,e=>Math.max(0,e)),_R={kernelName:ks,backendName:"cpu",kernelFunc:Bx},Vx=st(Ns,e=>Math.min(Math.max(0,e),6)),bR={kernelName:Ns,backendName:"cpu",kernelFunc:Vx};function dA(e,t,n,r,a){if(n==="linear")return Pr({inputs:{x:t},backend:e});if(n==="relu")return Bx({inputs:{x:t},backend:e});if(n==="elu")return Px({inputs:{x:t},backend:e});if(n==="relu6")return Vx({inputs:{x:t},backend:e});if(n==="prelu")return Wx({inputs:{x:t,alpha:r},backend:e});if(n==="leakyrelu")return Lx({inputs:{x:t},backend:e,attrs:{alpha:a}});throw new Error(`Activation ${n} has not been implemented for the CPU backend.`)}function yt(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{shape:s}=r,i=v.sizeFromShape(a.shape),o=v.inferFromImplicitShape(s,i),l=v.sizeFromShape(o);v.assert(i===l,()=>`The new shape (${o}) has ${l} elements and the old shape (${a.shape}) has ${i} elements. The new shape and old shape must have the same number of elements.`),n.incRef(a.dataId);let c=n.data.get(a.dataId);if(c.complexTensorInfos!=null){let u=c.complexTensorInfos.real,h=c.complexTensorInfos.imag;u.shape=o,h.shape=o}return{dataId:a.dataId,shape:o,dtype:a.dtype}}var vR={kernelName:ko,backendName:"cpu",kernelFunc:yt};function Ux(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;ve([a,s],"matMul");let l=a.shape.length,c=s.shape.length,u=i?a.shape[l-2]:a.shape[l-1],h=o?s.shape[c-1]:s.shape[c-2],d=i?a.shape[l-1]:a.shape[l-2],p=o?s.shape[c-2]:s.shape[c-1],f=a.shape.slice(0,-2),m=s.shape.slice(0,-2),A=v.sizeFromShape(f),y=v.sizeFromShape(m),g=A===y||A===1||y===1;v.assert(l>=2&&c>=2&&g,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${f}) and (${m}).`);let w=(A>y?a.shape.slice(0,-2):s.shape.slice(0,-2)).concat([d,p]);v.assert(u===h,()=>`Error in matMul: inner shapes (${u}) and (${h}) of Tensors with shapes ${a.shape} and ${s.shape} and transposeA=${i} and transposeB=${o} must match.`);let x=i?[A,u,d]:[A,d,u],_=o?[y,p,h]:[y,h,p],I=yt({inputs:{x:a},backend:n,attrs:{shape:x}}),T=yt({inputs:{x:s},backend:n,attrs:{shape:_}}),E=i?I.shape[1]:I.shape[2],N=i?I.shape[2]:I.shape[1],F=o?T.shape[1]:T.shape[2],$=Math.max(A,y),D=n.data.get(I.dataId).values,P=n.data.get(T.dataId).values,H=v.computeStrides(I.shape),V=v.computeStrides(T.shape),[K,X,ee]=i?[H[0],1,H[1]]:[H[0],H[1],1],[J,ae,Y]=o?[1,V[1],V[0]]:[V[1],1,V[0]],ue=N*F,ne=We([$,N,F],I.dtype),de=ne.values,he=n.blockSize;for(let me=0;me<$;me++)for(let Ae=0;Ae<N;Ae+=he)for(let ke=0;ke<F;ke+=he)for(let Ee=0;Ee<E;Ee+=he){let Re=Math.min(Ae+he,N),Oe=Math.min(ke+he,F),Ke=Math.min(Ee+he,E);for(let Ve=Ae;Ve<Re;Ve++)for(let rt=ke;rt<Oe;rt++){let it=0;for(let je=Ee;je<Ke;je++){let lt=Math.min(me,A-1)*K,ut=Math.min(me,y-1)*Y,On=D[lt+Ve*X+je*ee],Ye=P[je*J+rt*ae+ut];it+=On*Ye}de[me*ue+(Ve*F+rt)]+=it}}return n.disposeIntermediateTensorInfo(I),n.disposeIntermediateTensorInfo(T),n.makeTensorInfo(w,ne.dtype,ne.values)}var kR={kernelName:Ya,backendName:"cpu",kernelFunc:Ux};function IR(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:c,activation:u,leakyreluAlpha:h}=r,d,p,f,m=[];d=Ux({inputs:{a,b:s},attrs:{transposeA:l,transposeB:c},backend:n}),i&&(p=nc({inputs:{a:d,b:i},backend:n}),m.push(d),d=p),u&&(f=dA(n,d,u,o,h),m.push(d),d=f);for(let A of m)n.disposeIntermediateTensorInfo(A);return d}var NR={kernelName:Ls,backendName:"cpu",kernelFunc:IR},SR=st(Pi,e=>Math.acos(e)),TR={kernelName:Pi,backendName:"cpu",kernelFunc:SR},ER=st(Li,e=>Math.acosh(e)),CR={kernelName:Li,backendName:"cpu",kernelFunc:ER};function RR(e){let{inputs:t,backend:n}=e,r=t;ve(t,"addN");let a=r.map(o=>n.data.get(o.dataId).values),s=We(r[0].shape,r[0].dtype),i=s.values;for(let o=0;o<r.length;o++){let l=a[o];for(let c=0;c<i.length;c++)i[c]+=l[c]}return n.makeTensorInfo(s.shape,s.dtype,s.values)}var FR={kernelName:Ka,backendName:"cpu",kernelFunc:RR};function MR(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;ve(a,"all");let o=v.parseAxisParam(s,a.shape),l=o,c=C.getAxesPermutation(l,a.shape.length),u=a;c!=null&&(u=sr({inputs:{x:a},backend:n,attrs:{perm:c}}),l=C.getInnerMostAxes(l.length,a.shape.length)),C.assertAxesAreInnerMostDims("all",l,u.shape.length);let[h,d]=C.computeOutAndReduceShapes(u.shape,l),p=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(h),u.dtype),m=n.data.get(u.dataId).values;for(let y=0;y<f.length;++y){let g=y*p,w=m[g];for(let x=0;x<p;++x){let _=m[g+x];w=w&&_}f[y]=w}c!=null&&n.disposeIntermediateTensorInfo(u);let A=n.makeTensorInfo(h,u.dtype,f);if(i){let y=C.expandShapeToKeepDim(h,o),g=yt({inputs:{x:A},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(A),g}return A}var $R={kernelName:dh,backendName:"cpu",kernelFunc:MR};function DR(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;ve(a,"any");let o=v.parseAxisParam(s,a.shape),l=o,c=C.getAxesPermutation(l,a.shape.length),u=a;c!=null&&(u=sr({inputs:{x:a},backend:n,attrs:{perm:c}}),l=C.getInnerMostAxes(l.length,a.shape.length)),C.assertAxesAreInnerMostDims("any",l,u.shape.length);let[h,d]=C.computeOutAndReduceShapes(u.shape,l),p=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(h),u.dtype),m=n.data.get(u.dataId).values;for(let y=0;y<f.length;++y){let g=y*p,w=m[g];for(let x=0;x<p;++x){let _=m[g+x];w=w||_}f[y]=w}c!=null&&n.disposeIntermediateTensorInfo(u);let A=n.makeTensorInfo(h,u.dtype,f);if(i){let y=C.expandShapeToKeepDim(h,o),g=yt({inputs:{x:A},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(A),g}return A}var OR={kernelName:ph,backendName:"cpu",kernelFunc:DR};function zR(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r;ve(a,"argMax");let i=v.parseAxisParam(s,a.shape),o=C.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=sr({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],C.assertAxesAreInnerMostDims("argMax",i,l.shape.length);let[u,h]=C.computeOutAndReduceShapes(l.shape,i),d=v.sizeFromShape(u),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],w=0;for(let x=0;x<f;++x){let _=m[y+x];_>g&&(g=_,w=x)}p[A]=w}return c.forEach(A=>n.disposeIntermediateTensorInfo(A)),n.makeTensorInfo(u,"int32",p)}var PR={kernelName:Za,backendName:"cpu",kernelFunc:zR};function LR(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r;ve(a,"argMin");let i=v.parseAxisParam(s,a.shape),o=C.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=sr({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],C.assertAxesAreInnerMostDims("argMin",i,l.shape.length);let[u,h]=C.computeOutAndReduceShapes(l.shape,i),d=v.sizeFromShape(u),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],w=0;for(let x=0;x<f;++x){let _=m[y+x];_<g&&(g=_,w=x)}p[A]=w}return c.forEach(A=>n.disposeIntermediateTensorInfo(A)),n.makeTensorInfo(u,"int32",p)}var WR={kernelName:su,backendName:"cpu",kernelFunc:LR},BR=st(Wi,e=>Math.asin(e)),VR={kernelName:Wi,backendName:"cpu",kernelFunc:BR},UR=st(Bi,e=>Math.asinh(e)),HR={kernelName:Bi,backendName:"cpu",kernelFunc:UR},jR=st(Vi,e=>Math.atan(e)),GR={kernelName:Vi,backendName:"cpu",kernelFunc:jR},qR=Rt((e,t)=>Math.atan2(e,t)),XR=Ht(Hi,qR),KR={kernelName:Hi,backendName:"cpu",kernelFunc:XR},ZR=st(Ui,e=>Math.atanh(e)),JR={kernelName:Ui,backendName:"cpu",kernelFunc:ZR};function pA(e,t,n,r,a,s){let i=a.strideHeight,o=a.strideWidth,l=a.dilationHeight,c=a.dilationWidth,u=a.effectiveFilterHeight,h=a.effectiveFilterWidth,d=a.padInfo.top,p=a.padInfo.left,f=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=We(a.outShape,n),A=m.values,y=a.outShape[1]*a.outShape[2]*a.outShape[3],g=a.outShape[2]*a.outShape[3],w=a.outShape[3];for(let x=0;x<a.batchSize;++x){let _=x*y,I=x*r[0];for(let T=0;T<a.inChannels;++T)for(let E=0;E<a.outHeight;++E){let N=E*i-d,F=Math.max(0,N),$=Math.min(a.inHeight,u+N),D=_+E*g;for(let P=0;P<a.outWidth;++P){let H=P*o-p,V=Math.max(0,H),K=Math.min(a.inWidth,h+H),X=f,ee=0,J=0;for(let Y=F;Y<$;Y+=l){let ue=I+Y*r[1];for(let ne=V;ne<K;ne+=c){let de=ue+ne*r[2],he=e[de+T];s==="max"&&he>X?X=he:s==="avg"&&(ee+=he,J++)}if(isNaN(X))break}let ae=D+P*w+T;A[ae]=s==="avg"?ee/J:X}}}return m}function Hx(e,t,n,r,a=!1,s=!1){let i=We(r.outShape,"int32"),o=r.strideHeight,l=r.strideWidth,c=r.dilationHeight,u=r.dilationWidth,h=r.effectiveFilterHeight,d=r.effectiveFilterWidth,p=r.padInfo.top,f=r.padInfo.left,m=We(t,n,e);for(let A=0;A<r.batchSize;++A)for(let y=0;y<r.inChannels;++y)for(let g=0;g<r.outHeight;++g){let w=g*o-p,x=w;for(;x<0;)x+=c;let _=Math.min(r.inHeight,h+w);for(let I=0;I<r.outWidth;++I){let T=I*l-f,E=T;for(;E<0;)E+=u;let N=Math.min(r.inWidth,d+T),F=Number.NEGATIVE_INFINITY,$=-1;for(let D=x;D<_;D+=c){let P=D-w;for(let H=E;H<N;H+=u){let V=H-T,K=m.get(A,D,H,y);K>F&&(F=K,a?$=s?((A*r.inHeight+D)*r.inWidth+H)*r.inChannels+y:(D*r.inWidth+H)*r.inChannels+y:$=P*d+V)}}i.set($,A,g,I,y)}}return i}function jx(e,t,n,r,a,s){let i=a.strideDepth,o=a.strideHeight,l=a.strideWidth,c=a.dilationDepth,u=a.dilationHeight,h=a.dilationWidth,d=a.effectiveFilterDepth,p=a.effectiveFilterHeight,f=a.effectiveFilterWidth,m=a.padInfo.front,A=a.padInfo.top,y=a.padInfo.left,g=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,w=We(a.outShape,n),x=w.values,_=a.outShape[1]*a.outShape[2]*a.outShape[3]*a.outShape[4],I=a.outShape[2]*a.outShape[3]*a.outShape[4],T=a.outShape[3]*a.outShape[4],E=a.outShape[4];for(let N=0;N<a.batchSize;++N){let F=N*_,$=N*r[0];for(let D=0;D<a.inChannels;++D)for(let P=0;P<a.outDepth;++P){let H=P*i-m,V=H;for(;V<0;)V+=c;let K=Math.min(a.inDepth,d+H),X=F+P*I;for(let ee=0;ee<a.outHeight;++ee){let J=ee*o-A,ae=J;for(;ae<0;)ae+=u;let Y=Math.min(a.inHeight,p+J),ue=X+ee*T;for(let ne=0;ne<a.outWidth;++ne){let de=ne*l-y,he=de;for(;he<0;)he+=h;let me=Math.min(a.inWidth,f+de),Ae=ue+ne*E,ke=g,Ee=0,Re=0;for(let Ke=V;Ke<K;Ke+=c){let Ve=$+Ke*r[1];for(let rt=ae;rt<Y;rt+=u){let it=Ve+rt*r[2];for(let je=he;je<me;je+=h){let lt=it+je*r[3],ut=e[lt+D];if(s==="max"&&ut>ke?ke=ut:s==="avg"&&(Ee+=ut,Re++),isNaN(ke))break}if(isNaN(ke))break}if(isNaN(ke))break}let Oe=Ae+D;x[Oe]=s==="avg"?Ee/Re:ke}}}}return w}function YR(e,t){let n=We(t.outShape,"int32"),r=t.strideDepth,a=t.strideHeight,s=t.strideWidth,i=t.dilationDepth,o=t.dilationHeight,l=t.dilationWidth,c=t.effectiveFilterDepth,u=t.effectiveFilterHeight,h=t.effectiveFilterWidth,d=t.padInfo.front,p=t.padInfo.top,f=t.padInfo.left;for(let m=0;m<t.batchSize;++m)for(let A=0;A<t.inChannels;++A)for(let y=0;y<t.outDepth;++y){let g=y*r-d,w=g;for(;w<0;)w+=i;let x=Math.min(t.inDepth,c+g);for(let _=0;_<t.outHeight;++_){let I=_*a-p,T=I;for(;T<0;)T+=o;let E=Math.min(t.inHeight,u+I);for(let N=0;N<t.outWidth;++N){let F=N*s-f,$=F;for(;$<0;)$+=l;let D=Math.min(t.inWidth,h+F),P=Number.NEGATIVE_INFINITY,H=-1;for(let V=w;V<x;V+=i){let K=V-g;for(let X=T;X<E;X+=o){let ee=X-I;for(let J=$;J<D;J+=l){let ae=J-F,Y=e.get(m,V,X,J,A);Y>=P&&(P=Y,H=K*u*h+ee*u+ae)}}}n.set(H,m,y,_,N,A)}}}return n}function QR(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;ve(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(C.eitherStridesOrDilationsAreOne(i,c),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=C.computePool2DInfo(a.shape,s,i,c,o,l),h;if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))h=Pr({inputs:{x:a},backend:n});else{let d=n.data.get(a.dataId).values,p=v.computeStrides(a.shape),f=pA(d,a.shape,a.dtype,p,u,"avg");h=n.makeTensorInfo(u.outShape,a.dtype,f.values)}return h}var eF={kernelName:Ja,backendName:"cpu",kernelFunc:QR};function tF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:c}=r;ve(a,"avgPool3d");let u=C.computePool3DInfo(a.shape,s,i,1,o,l,c),h=n.data.get(a.dataId).values,d=jx(h,a.shape,a.dtype,v.computeStrides(a.shape),u,"avg");return n.makeTensorInfo(d.shape,"float32",d.values)}var nF={kernelName:iu,backendName:"cpu",kernelFunc:tF};function rF(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:c}=r;ve([a,s],"avgPool3DGrad");let u=C.computePool3DInfo(s.shape,i,o,1,l,c),h=u.strideDepth,d=u.strideHeight,p=u.strideWidth,f=u.filterDepth,m=u.filterHeight,A=u.filterWidth,y=u.dilationDepth,g=u.dilationHeight,w=u.dilationWidth,x=u.effectiveFilterDepth,_=u.effectiveFilterHeight,I=u.effectiveFilterWidth,T=x-1-u.padInfo.front,E=I-1-u.padInfo.left,N=_-1-u.padInfo.top,F=We(s.shape,"float32"),$=1/(f*m*A),D=n.bufferSync(a);for(let P=0;P<u.batchSize;++P)for(let H=0;H<u.inChannels;++H)for(let V=0;V<u.inDepth;++V)for(let K=0;K<u.inHeight;++K)for(let X=0;X<u.inWidth;++X){let ee=V-T,J=K-N,ae=X-E,Y=0;for(let ue=0;ue<x;ue+=y){let ne=(ee+ue)/h;if(!(ne<0||ne>=u.outDepth||Math.floor(ne)!==ne))for(let de=0;de<_;de+=g){let he=(J+de)/d;if(!(he<0||he>=u.outHeight||Math.floor(he)!==he))for(let me=0;me<I;me+=w){let Ae=(ae+me)/p;Ae<0||Ae>=u.outWidth||Math.floor(Ae)!==Ae||(Y+=D.get(P,ne,he,Ae,H))}}}F.set(Y*$,P,V,K,X,H)}return n.makeTensorInfo(F.shape,F.dtype,F.values)}var aF={kernelName:mh,backendName:"cpu",kernelFunc:rF};function sF(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;ve([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:c}=r,u=C.computePool2DInfo(i.shape,o,l,1,c),h=u.strideHeight,d=u.strideWidth,p=u.filterHeight,f=u.filterWidth,m=u.dilationHeight,A=u.dilationWidth,y=u.effectiveFilterHeight,g=u.effectiveFilterWidth,w=g-1-u.padInfo.left,x=y-1-u.padInfo.top,_=We(i.shape,"float32"),I=1/(p*f),T=n.data.get(a.dataId).values,E=We(a.shape,"float32",T);for(let N=0;N<u.batchSize;++N)for(let F=0;F<u.inChannels;++F)for(let $=0;$<u.inHeight;++$)for(let D=0;D<u.inWidth;++D){let P=$-x,H=D-w,V=0;for(let K=0;K<y;K+=m){let X=(P+K)/h;if(!(X<0||X>=u.outHeight||Math.floor(X)!==X))for(let ee=0;ee<g;ee+=A){let J=(H+ee)/d;J<0||J>=u.outWidth||Math.floor(J)!==J||(V+=E.get(N,X,J,F))}}_.set(V*I,N,$,D,F)}return n.makeTensorInfo(_.shape,_.dtype,_.values)}var iF={kernelName:fh,backendName:"cpu",kernelFunc:sF};function oF(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."),ve([a,o,l,s,i],"batchNorm");let{varianceEpsilon:c}=r;c==null&&(c=.001);let u=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(u.length),A=f.length,y=p.length,g=d.length,w=h.length,x=0,_=0,I=0,T=0;for(let E=0;E<u.length;++E)m[E]=f[x++]+(u[E]-h[_++])*p[I++]/Math.sqrt(d[T++]+c),x>=A&&(x=0),_>=w&&(_=0),I>=y&&(I=0),T>=g&&(T=0);return n.makeTensorInfo(a.shape,a.dtype,m)}var lF={kernelName:us,backendName:"cpu",kernelFunc:oF};function uF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;ve([a],"batchToSpaceND");let o=s.reduce((y,g)=>y*g),l=C.getReshaped(a.shape,s,o),c=C.getPermuted(l.length,s.length),u=C.getReshapedPermuted(a.shape,s,o),h=C.getSliceBeginCoords(i,s.length),d=C.getSliceSize(u,i,s.length),p=yt({inputs:{x:a},backend:n,attrs:{shape:l}}),f=sr({inputs:{x:p},backend:n,attrs:{perm:c}}),m=yt({inputs:{x:f},backend:n,attrs:{shape:u}}),A=ri({inputs:{x:m},backend:n,attrs:{begin:h,size:d}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),A}var cF={kernelName:ou,backendName:"cpu",kernelFunc:uF};function hF(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,c=aA(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}var dF={kernelName:Ah,backendName:"cpu",kernelFunc:hF},pF=st(ma,(e,t)=>{let n=t;return e>n.clipValueMax?n.clipValueMax:e<n.clipValueMin?n.clipValueMin:e}),fF={kernelName:ma,backendName:"cpu",kernelFunc:pF},mF=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 c=0;c<o.length;c++){let u=o[c],h=l[c];r[c]=Math.hypot(u,h)}return n.makeOutput(r,t.shape,"float32")},AF={kernelName:lu,backendName:"cpu",kernelFunc:mF};function dl(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 yF={kernelName:Ch,backendName:"cpu",kernelFunc:dl};function pl(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=C.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 Pr({inputs:{x:o[0]},backend:n});let l=o.map(m=>m.shape);if(C.assertParamsConsistent(l,s),o[0].dtype==="complex64"){let m=o.map(x=>ni({inputs:{input:x},backend:n})),A=o.map(x=>dl({inputs:{input:x},backend:n})),y=pl({inputs:m,backend:n,attrs:{axis:s}}),g=pl({inputs:A,backend:n,attrs:{axis:s}}),w=Tn({inputs:{real:y,imag:g},backend:n});return m.forEach(x=>n.disposeIntermediateTensorInfo(x)),A.forEach(x=>n.disposeIntermediateTensorInfo(x)),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(g),w}let c=o.map(m=>{let A=v.sizeFromShape(m.shape.slice(s));return yt({inputs:{x:m},backend:n,attrs:{shape:[-1,A]}})}),u=c.map(m=>({vals:n.data.get(m.dataId).values,shape:m.shape}));i=C.computeOutShape(c.map(m=>m.shape),1);let h=c[0].shape[0]===1,d=sA(u,i,t[0].dtype,h),p=C.computeOutShape(o.map(m=>m.shape),s),f=n.makeTensorInfo(p,t[0].dtype,d);return c.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var gF={kernelName:Gi,backendName:"cpu",kernelFunc:pl};function Gx(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:c,dimRoundingMode:u}=r;ve([a,s],"conv2d");let h=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(a.shape,s.shape,i,c,o,u,!1,h),p=d.filterHeight,f=d.filterWidth,m=d.dilationHeight,A=d.dilationWidth,y=d.padInfo.left,g=d.padInfo.top,w=d.dataFormat==="channelsLast",x=new Mt(d.outShape,a.dtype),_=v.computeStrides(a.shape),I=v.computeStrides(s.shape),T=_[0],E=w?_[1]:_[2],N=w?_[2]:1,F=w?1:_[1],$=x.strides[0],D=w?x.strides[1]:x.strides[2],P=w?x.strides[2]:1,H=w?1:x.strides[1],V=n.data.get(a.dataId).values,K=n.data.get(s.dataId).values,X=x.values;for(let ee=0;ee<d.batchSize;++ee){let J=ee*T,ae=ee*$;for(let Y=0;Y<d.outHeight;++Y){let ue=ae+Y*D,ne=Y*d.strideHeight-g;for(let de=0;de<p;++de){let he=ne+de*m;if(he<0||he>=d.inHeight)continue;let me=de*I[0],Ae=J+he*E;for(let ke=0;ke<d.outWidth;++ke){let Ee=ue+ke*P,Re=ke*d.strideWidth-y;for(let Oe=0;Oe<f;++Oe){let Ke=Re+Oe*A;if(Ke<0||Ke>=d.inWidth)continue;let Ve=me+Oe*I[1],rt=Ae+Ke*N,it=Ve;for(let je=0;je<d.inChannels;++je){let lt=V[rt+je*F];for(let ut=0;ut<d.outChannels;++ut)X[Ee+ut*H]+=lt*K[it+ut];it+=d.outChannels}}}}}}return n.makeTensorInfo(x.shape,x.dtype,X)}var xF={kernelName:es,backendName:"cpu",kernelFunc:Gx};function wF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:c,filterShape:u}=r;ve([a,s],"conv2dBackpropFilter");let h=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(a.shape,u,i,1,o,c,!1,h),{strideHeight:p,strideWidth:f,filterHeight:m,filterWidth:A}=d,y=d.dataFormat==="channelsLast",g=new Mt(d.filterShape,"float32"),w=d.padInfo.left,x=d.padInfo.top,_=n.data.get(a.dataId).values,I=n.data.get(s.dataId).values,T=new Mt(a.shape,a.dtype,_),E=new Mt(s.shape,s.dtype,I);for(let N=0;N<m;++N){let F=Math.max(0,Math.ceil((x-N)/p)),$=Math.min(d.outHeight,(d.inHeight+x-N)/p);for(let D=0;D<A;++D){let P=Math.max(0,Math.ceil((w-D)/f)),H=Math.min(d.outWidth,(d.inWidth+w-D)/f);for(let V=0;V<d.inChannels;++V)for(let K=0;K<d.outChannels;++K){let X=0;for(let ee=0;ee<d.batchSize;++ee)for(let J=F;J<$;++J){let ae=N+J*p-x;for(let Y=P;Y<H;++Y){let ue=D+Y*f-w;y?X+=T.get(ee,ae,ue,V)*E.get(ee,J,Y,K):X+=T.get(ee,V,ae,ue)*E.get(ee,K,J,Y)}}g.set(X,N,D,V,K)}}}return n.makeTensorInfo(g.shape,g.dtype,g.values)}var _F={kernelName:gh,backendName:"cpu",kernelFunc:wF};function bF(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:c,dimRoundingMode:u}=r;ve([a,s],"conv2dBackpropInput");let h=v.computeStrides(s.shape),d=v.computeStrides(a.shape),p=C.convertConv2DDataFormat(c),f=C.computeConv2DInfo(i,s.shape,o,1,l,u,!1,p),m=new Mt(f.inShape,"float32"),A=m.values,y=n.data.get(a.dataId).values,g=n.data.get(s.dataId).values,[w,x,_]=h,{batchSize:I,filterHeight:T,filterWidth:E,inChannels:N,inHeight:F,inWidth:$,outChannels:D,outHeight:P,outWidth:H,strideHeight:V,strideWidth:K}=f;p=f.dataFormat;let X=T-1-f.padInfo.top,ee=E-1-f.padInfo.left,J=p==="channelsLast",ae=m.strides[0],Y=J?m.strides[1]:m.strides[2],ue=J?m.strides[2]:1,ne=J?1:m.strides[1],de=d[0],he=J?d[1]:d[2],me=J?d[2]:1,Ae=J?1:d[1];for(let ke=0;ke<I;++ke)for(let Ee=0;Ee<N;++Ee)for(let Re=0;Re<F;++Re){let Oe=Re-X,Ke=Math.max(0,Math.ceil(Oe/V)),Ve=Math.min(P,(T+Oe)/V);for(let rt=0;rt<$;++rt){let it=rt-ee,je=Math.max(0,Math.ceil(it/K)),lt=Math.min(H,(E+it)/K),ut=0;for(let Ye=Ke;Ye<Ve;++Ye){let xn=Ye*V-Oe;for(let qt=je;qt<lt;++qt){let wn=qt*K-it,qn=de*ke+he*Ye+me*qt,hn=w*(T-1-xn)+x*(E-1-wn)+_*Ee;for(let nn=0;nn<D;++nn){let Xn=y[qn+Ae*nn],kr=g[hn+nn];ut+=Xn*kr}}}let On=ae*ke+Y*Re+ue*rt+ne*Ee;A[On]=ut}}return n.makeTensorInfo(m.shape,m.dtype,m.values)}var vF={kernelName:ts,backendName:"cpu",kernelFunc:bF};function kF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r;ve([a,s],"conv3d");let c=C.computeConv3DInfo(a.shape,s.shape,i,l,o),{filterDepth:u,filterHeight:h,filterWidth:d,dilationDepth:p,dilationHeight:f,dilationWidth:m,padInfo:A}=c,y=A.front,g=A.left,w=A.top,x=new Mt(c.outShape,a.dtype),_=n.data.get(a.dataId).values,I=n.data.get(s.dataId).values,T=x.values,E=v.computeStrides(a.shape),N=v.computeStrides(s.shape);for(let F=0;F<c.batchSize;++F){let $=F*E[0],D=F*x.strides[0];for(let P=0;P<c.outDepth;++P){let H=D+P*x.strides[1],V=P*c.strideDepth-y;for(let K=0;K<u;++K){let X=V+K*p;if(X<0||X>=c.inDepth)continue;let ee=K*N[0],J=$+X*E[1];for(let ae=0;ae<c.outHeight;++ae){let Y=H+ae*x.strides[2],ue=ae*c.strideHeight-w;for(let ne=0;ne<h;++ne){let de=ue+ne*f;if(de<0||de>=c.inHeight)continue;let he=ee+ne*N[1],me=J+de*E[2];for(let Ae=0;Ae<c.outWidth;++Ae){let ke=Y+Ae*c.outChannels,Ee=Ae*c.strideWidth-g;for(let Re=0;Re<d;++Re){let Oe=Ee+Re*m;if(Oe<0||Oe>=c.inWidth)continue;let Ke=he+Re*N[2],Ve=me+Oe*c.inChannels,rt=Ke;for(let it=0;it<c.inChannels;++it){let je=_[Ve+it];for(let lt=0;lt<c.outChannels;++lt)T[ke+lt]+=je*I[rt+lt];rt+=c.outChannels}}}}}}}}return n.makeTensorInfo(x.shape,x.dtype,x.values)}var IF={kernelName:uu,backendName:"cpu",kernelFunc:kF};function NF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r;ve([a,s],"conv3dBackpropFilterV2");let c=v.computeStrides(a.shape),u=v.computeStrides(s.shape),h=C.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 Mt(h.filterShape,"float32"),w=g.values,[x,_,I,T]=g.strides,E=n.data.get(s.dataId).values,[N,F,$,D]=u,P=n.data.get(a.dataId).values,[H,V,K,X]=c,ee=h.padInfo.front,J=h.padInfo.left,ae=h.padInfo.top;for(let Y=0;Y<m;++Y){let ue=Math.max(0,Math.ceil((ee-Y)/d)),ne=Math.min(h.outDepth,(h.inDepth+ee-Y)/d),de=Y*x;for(let he=0;he<A;++he){let me=Math.max(0,Math.ceil((ae-he)/p)),Ae=Math.min(h.outHeight,(h.inHeight+ae-he)/p),ke=he*_+de;for(let Ee=0;Ee<y;++Ee){let Re=Math.max(0,Math.ceil((J-Ee)/f)),Oe=Math.min(h.outWidth,(h.inWidth+J-Ee)/f),Ke=Ee*I+ke;for(let Ve=0;Ve<h.inChannels;++Ve){let rt=Ve*T+Ke;for(let it=0;it<h.outChannels;++it){let je=0;for(let lt=0;lt<h.batchSize;++lt){let ut=lt*H,On=lt*N;for(let Ye=ue;Ye<ne;++Ye){let xn=(Y+Ye*d-ee)*V+ut,qt=Ye*F+On;for(let wn=me;wn<Ae;++wn){let qn=(he+wn*p-ae)*K+xn,hn=wn*$+qt;for(let nn=Re;nn<Oe;++nn){let Xn=(Ee+nn*f-J)*X+qn,kr=nn*D+hn;je+=P[Xn+Ve]*E[kr+it]}}}}w[rt+it]=je}}}}}return n.makeTensorInfo(g.shape,g.dtype,g.values)}var SF={kernelName:xh,backendName:"cpu",kernelFunc:NF};function TF(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r;ve([a],"conv3dBackpropInputV2");let c=v.computeStrides(a.shape),u=v.computeStrides(s.shape),h=C.computeConv3DInfo(l,s.shape,o,1,i),d=new Mt(h.inShape,"float32"),p=d.values,[f,m,A,y]=d.strides,g=n.data.get(a.dataId).values,[w,x,_,I]=c,T=n.data.get(s.dataId).values,[E,N,F,$]=u,{batchSize:D,filterDepth:P,filterHeight:H,filterWidth:V,inChannels:K,inDepth:X,inHeight:ee,inWidth:J,outChannels:ae,outDepth:Y,outHeight:ue,outWidth:ne,strideDepth:de,strideHeight:he,strideWidth:me}=h,Ae=P-1-h.padInfo.front,ke=H-1-h.padInfo.top,Ee=V-1-h.padInfo.left;for(let Re=0;Re<D;++Re)for(let Oe=0;Oe<K;++Oe)for(let Ke=0;Ke<X;++Ke){let Ve=Ke-Ae,rt=Math.max(0,Math.ceil(Ve/de)),it=Math.min(Y,(P+Ve)/de);for(let je=0;je<ee;++je){let lt=je-ke,ut=Math.max(0,Math.ceil(lt/he)),On=Math.min(ue,(H+lt)/he);for(let Ye=0;Ye<J;++Ye){let xn=Ye-Ee,qt=Math.max(0,Math.ceil(xn/me)),wn=Math.min(ne,(V+xn)/me),qn=0;for(let hn=rt;hn<it;++hn){let nn=hn*de-Ve;for(let Xn=ut;Xn<On;++Xn){let kr=Xn*he-lt;for(let _n=qt;_n<wn;++_n){let ki=_n*me-xn,Pl=w*Re+x*hn+_*Xn+I*_n,cr=E*(P-1-nn)+N*(H-1-kr)+F*(V-1-ki)+$*Oe;for(let Kn=0;Kn<ae;++Kn){let hr=g[Pl+Kn],Ii=T[cr+Kn];qn+=hr*Ii}}}}p[f*Re+m*Ke+A*je+y*Ye+Oe]=qn}}}return n.makeTensorInfo(d.shape,d.dtype,d.values)}var EF={kernelName:wh,backendName:"cpu",kernelFunc:TF},CF=st(ns,e=>Math.cos(e)),RF={kernelName:ns,backendName:"cpu",kernelFunc:CF},FF=st(qi,e=>Math.cosh(e)),MF={kernelName:qi,backendName:"cpu",kernelFunc:FF};function $F(e){let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:c}=r,[u,h,d,p]=a.shape,f=s.shape[0],[m,A]=o,y=We([f,m,A,p],"float32"),g=n.data.get(s.dataId).values,w=n.data.get(i.dataId).values,x=n.data.get(a.dataId).values,_=v.computeStrides(a.shape),I=v.computeStrides(y.shape);for(let T=0;T<f;T++){let E=T*4,N=g[E],F=g[E+1],$=g[E+2],D=g[E+3],P=w[T];if(P>=u)continue;let H=m>1?($-N)*(h-1)/(m-1):0,V=A>1?(D-F)*(d-1)/(A-1):0;for(let K=0;K<m;K++){let X=m>1?N*(h-1)+K*H:.5*(N+$)*(h-1);if(X<0||X>h-1){for(let ee=0;ee<A;ee++)for(let J=0;J<p;J++){let ae=J+ee*I[2]+K*I[1]+T*I[0];y.values[ae]=c}continue}if(l==="bilinear"){let ee=Math.floor(X),J=Math.ceil(X),ae=X-ee;for(let Y=0;Y<A;Y++){let ue=A>1?F*(d-1)+Y*V:.5*(F+D)*(d-1);if(ue<0||ue>d-1){for(let me=0;me<p;me++){let Ae=me+Y*I[2]+K*I[1]+T*I[0];y.values[Ae]=c}continue}let ne=Math.floor(ue),de=Math.ceil(ue),he=ue-ne;for(let me=0;me<p;me++){let Ae=me+ne*_[2]+ee*_[1]+P*_[0],ke=x[Ae];Ae=me+de*_[2]+ee*_[1]+P*_[0];let Ee=x[Ae];Ae=me+ne*_[2]+J*_[1]+P*_[0];let Re=x[Ae];Ae=me+de*_[2]+J*_[1]+P*_[0];let Oe=x[Ae],Ke=ke+(Ee-ke)*he,Ve=Re+(Oe-Re)*he;Ae=me+Y*I[2]+K*I[1]+T*I[0],y.values[Ae]=Ke+(Ve-Ke)*ae}}}else for(let ee=0;ee<A;++ee){let J=A>1?F*(d-1)+ee*V:.5*(F+D)*(d-1);if(J<0||J>d-1){for(let ue=0;ue<p;ue++){let ne=ue+ee*I[2]+K*I[1]+T*I[0];y.values[ne]=c}continue}let ae=Math.round(J),Y=Math.round(X);for(let ue=0;ue<p;ue++){let ne=ue+ae*_[2]+Y*_[1]+P*_[0],de=ue+ee*I[2]+K*I[1]+T*I[0];y.values[de]=x[ne]}}}}return n.makeTensorInfo(y.shape,y.dtype,y.values)}var DF={kernelName:Xi,backendName:"cpu",kernelFunc:$F};function OF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r;ve(a,"cumsum");let l=C.getAxesPermutation([s],a.shape.length),c=a;l!=null&&(c=sr({inputs:{x:a},backend:n,attrs:{perm:l}}));let u=C.getInnerMostAxes(1,a.shape.length)[0];if(u!==c.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${c.shape.length-1} but got axis=${u}`);let h=Qn(c.dtype,"int32"),d=v.makeZerosTypedArray(v.sizeFromShape(c.shape),h),p=n.data.get(c.dataId).values,f=c.shape[c.shape.length-1],m=o?(y,g)=>y+f-g-1:(y,g)=>y+g;for(let y=0;y<p.length;y+=f)for(let g=0;g<f;g++){let w=m(y,g);if(g===0)d[w]=i?0:p[w];else{let x=m(y,g-1);d[w]=i?p[x]+d[x]:p[w]+d[x]}}let A=n.makeTensorInfo(c.shape,h,d);if(l!=null){let y=C.getUndoAxesPermutation(l),g=sr({inputs:{x:A},backend:n,attrs:{perm:y}});return n.disposeIntermediateTensorInfo(A),n.disposeIntermediateTensorInfo(c),g}return A}var zF={kernelName:rs,backendName:"cpu",kernelFunc:OF};function PF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.data.get(a.dataId).values,c=n.data.get(s.dataId).values,u=aA(l,c,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}else if(a.shape.length===2){let l=n.bufferSync(a),c=n.bufferSync(s),u=fx(l,c,i,o);return n.makeTensorInfo(u.shape,s.dtype,u.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var LF={kernelName:_h,backendName:"cpu",kernelFunc:PF};function WF(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],c=a.shape[2],u=a.shape[3],h=l*s,d=c*s,p=u/(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 w=Math.floor(g/s),x=g%s;for(let _=0;_<d;++_){let I=Math.floor(_/s),T=_%s,E=(x*s+T)*p;for(let N=0;N<p;++N){let F=N+E+u*(I+c*(w+l*y));m[A++]=f[F]}}}return n.makeTensorInfo([o,h,d,p],a.dtype,m)}var BF={kernelName:Ki,backendName:"cpu",kernelFunc:WF};function qx(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:c}=r;ve([a,s],"depthwiseConv2DNative");let u=v.computeStrides(a.shape),h=v.computeStrides(s.shape),d=l;d==null&&(d=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(i,d),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${d}'`);let p=C.computeConv2DInfo(a.shape,s.shape,i,d,o,c,!0),{filterHeight:f,filterWidth:m,dilationHeight:A,dilationWidth:y,padInfo:g}=p,w=g.left,x=g.top,_=p.outChannels/p.inChannels,I=new Mt(p.outShape,a.dtype),T=n.data.get(a.dataId).values,E=n.data.get(s.dataId).values,N=I.values;for(let F=0;F<p.batchSize;++F){let $=F*u[0],D=F*I.strides[0];for(let P=0;P<p.outHeight;++P){let H=D+P*I.strides[1],V=P*p.strideHeight-w;for(let K=0;K<f;++K){let X=V+K*A;if(X<0||X>=p.inHeight)continue;let ee=K*h[0],J=$+X*u[1];for(let ae=0;ae<p.outWidth;++ae){let Y=H+ae*I.strides[2],ue=ae*p.strideWidth-x;for(let ne=0;ne<m;++ne){let de=ue+ne*y;if(de<0||de>=p.inWidth)continue;let he=ee+ne*h[1],me=J+de*p.inChannels,Ae=Y,ke=he;for(let Ee=0;Ee<p.inChannels;++Ee){let Re=T[me+Ee];for(let Oe=0;Oe<_;++Oe)N[Ae+Oe]+=Re*E[ke+Oe];Ae+=_,ke+=_}}}}}}return n.makeTensorInfo(I.shape,I.dtype,I.values)}var VF={kernelName:as,backendName:"cpu",kernelFunc:qx};function UF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,filterShape:u}=r;ve([a,s],"depthwiseConv2dNativeBackpropFilter");let h=C.computeConv2DInfo(a.shape,u,i,o,l,c,!0),{strideHeight:d,strideWidth:p,filterHeight:f,filterWidth:m}=h,A=new Mt(h.filterShape,"float32"),y=h.padInfo.left,g=h.padInfo.top,w=h.outChannels/h.inChannels,x=n.data.get(a.dataId).values,_=new Mt(a.shape,a.dtype,x),I=n.data.get(s.dataId).values,T=new Mt(s.shape,s.dtype,I);for(let E=0;E<f;++E){let N=Math.max(0,Math.ceil((g-E)/d)),F=Math.min(h.outHeight,(h.inHeight+g-E)/d);for(let $=0;$<m;++$){let D=Math.max(0,Math.ceil((y-$)/p)),P=Math.min(h.outWidth,(h.inWidth+y-$)/p);for(let H=0;H<h.outChannels;++H){let V=Math.trunc(H/w),K=H%w,X=0;for(let ee=0;ee<h.batchSize;++ee)for(let J=N;J<F;++J){let ae=E+J*d-g;for(let Y=D;Y<P;++Y){let ue=$+Y*p-y;X+=_.get(ee,ae,ue,V)*T.get(ee,J,Y,H)}}A.set(X,E,$,V,K)}}}return n.makeTensorInfo(A.shape,A.dtype,A.values)}var HF={kernelName:bh,backendName:"cpu",kernelFunc:UF};function jF(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,inputShape:u}=r;ve([a,s],"depthwiseConv2DNativeBackpropInput");let h=v.computeStrides(a.shape),d=v.computeStrides(s.shape),p=C.computeConv2DInfo(u,s.shape,i,o,l,c,!0),f=new Mt(p.inShape,"float32"),m=f.values,[A,y,g]=f.strides,w=n.data.get(a.dataId).values,[x,_,I]=h,T=n.data.get(s.dataId).values,[E,N,F]=d,{batchSize:$,filterHeight:D,filterWidth:P,inChannels:H,inHeight:V,inWidth:K,outChannels:X,outHeight:ee,outWidth:J,strideHeight:ae,strideWidth:Y}=p,ue=D-1-p.padInfo.top,ne=P-1-p.padInfo.left,de=X/H;for(let he=0;he<$;++he)for(let me=0;me<H;++me)for(let Ae=0;Ae<V;++Ae){let ke=Ae-ue,Ee=Math.max(0,Math.ceil(ke/ae)),Re=Math.min(ee,(D+ke)/ae);for(let Oe=0;Oe<K;++Oe){let Ke=Oe-ne,Ve=Math.max(0,Math.ceil(Ke/Y)),rt=Math.min(J,(P+Ke)/Y),it=0;for(let je=Ee;je<Re;++je){let lt=je*ae-ke;for(let ut=Ve;ut<rt;++ut){let On=ut*Y-Ke,Ye=x*he+_*je+I*ut,xn=E*(D-1-lt)+N*(P-1-On)+F*me;for(let qt=0;qt<de;++qt){let wn=me*de+qt,qn=w[Ye+wn],hn=T[xn+qt];it+=qn*hn}}}m[A*he+y*Ae+g*Oe+me]=it}}return n.makeTensorInfo(f.shape,f.dtype,f.values)}var GF={kernelName:vh,backendName:"cpu",kernelFunc:jF};function qF(e){let{inputs:t,backend:n}=e,{x:r}=t,a=v.sizeFromShape(r.shape),s=n.data.get(r.dataId).values,i=We([a,a],r.dtype),o=i.values;for(let c=0;c<s.length;c++)o[c*a+c]=s[c];let l=[...r.shape,...r.shape];return n.makeTensorInfo(l,i.dtype,i.values)}var XF={kernelName:kh,backendName:"cpu",kernelFunc:qF},KF={kernelName:cu,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:r,filter:a}=e,{strides:s,pad:i,dilations:o}=n,l=t,c=l.data.get(r.dataId).values,u=r.shape.length,h=l.data.get(a.dataId).values,d=a.shape.length,{batchSize:p,inHeight:f,inWidth:m,inChannels:A,outHeight:y,outWidth:g,padInfo:w,strideHeight:x,strideWidth:_,filterHeight:I,filterWidth:T,dilationHeight:E,dilationWidth:N,outShape:F}=C.computeDilation2DInfo(r.shape,a.shape,s,i,"NHWC",o),$=v.sizeFromShape(F),D=F.length,P=v.getArrayFromDType(r.dtype,$);for(let H=0;H<p;++H)for(let V=0;V<y;++V){let K=V*x-w.top;for(let X=0;X<g;++X){let ee=X*_-w.left;for(let J=0;J<A;++J){let ae=Number.MIN_SAFE_INTEGER;for(let ue=0;ue<I;++ue){let ne=K+ue*E;if(ne>=0&&ne<f)for(let de=0;de<T;++de){let he=ee+de*N;if(he>=0&&he<m){let me=v.locToIndex([H,ne,he,J],u,v.computeStrides(r.shape)),Ae=v.locToIndex([ue,de,J],d,v.computeStrides(a.shape)),ke=c[me]+h[Ae];ke>ae&&(ae=ke)}}}let Y=v.locToIndex([H,V,X,J],D,v.computeStrides(F));P[Y]=ae}}}return{dataId:l.write(v.toTypedArray(P,r.dtype),F,r.dtype),shape:F,dtype:r.dtype}}},ZF={kernelName:Nh,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:r,filter:a,dy:s}=e,{strides:i,pad:o,dilations:l}=n,c=t,u=v.toNestedArray(r.shape,c.data.get(r.dataId).values),h=v.toNestedArray(a.shape,c.data.get(a.dataId).values),{batchSize:d,inHeight:p,inWidth:f,inChannels:m,outHeight:A,outWidth:y,padInfo:g,strideHeight:w,strideWidth:x,filterHeight:_,filterWidth:I,dilationHeight:T,dilationWidth:E,outShape:N}=C.computeDilation2DInfo(r.shape,a.shape,i,o,"NHWC",l);v.assert(s.rank===N.length,()=>`Error in ${Nh}, dy must have the same rank as output ${N.length}, but got ${s.rank}`);let F=v.toNestedArray(N,c.data.get(s.dataId).values),$=v.makeZerosNestedTypedArray(a.shape,a.dtype);for(let D=0;D<d;++D)for(let P=0;P<A;++P){let H=P*w-g.top;for(let V=0;V<y;++V){let K=V*x-g.left;for(let X=0;X<m;++X){let ee=Number.MIN_SAFE_INTEGER,J=0,ae=0;for(let Y=0;Y<_;++Y){let ue=H+Y*T;if(ue>=0&&ue<p)for(let ne=0;ne<I;++ne){let de=K+ne*E;if(de>=0&&de<f){let he=u[D][ue][de][X]+h[Y][ne][X];he>ee&&(ee=he,J=Y,ae=ne)}}}$[J][ae][X]+=F[D][P][V][X]}}}return{dataId:c.write(v.toTypedArray($,r.dtype),a.shape,a.dtype),shape:a.shape,dtype:a.dtype}}},JF={kernelName:Ih,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:r,filter:a,dy:s}=e,{strides:i,pad:o,dilations:l}=n,c=t,u=v.toNestedArray(r.shape,c.data.get(r.dataId).values),h=v.toNestedArray(a.shape,c.data.get(a.dataId).values),{batchSize:d,inHeight:p,inWidth:f,inChannels:m,outHeight:A,outWidth:y,padInfo:g,strideHeight:w,strideWidth:x,filterHeight:_,filterWidth:I,dilationHeight:T,dilationWidth:E,outShape:N}=C.computeDilation2DInfo(r.shape,a.shape,i,o,"NHWC",l);v.assert(s.rank===N.length,()=>`Error in ${Ih}, dy must have the same rank as output ${N.length}, but got ${s.rank}`);let F=v.toNestedArray(N,c.data.get(s.dataId).values),$=v.makeZerosNestedTypedArray(r.shape,r.dtype);for(let D=0;D<d;++D)for(let P=0;P<A;++P){let H=P*w-g.top;for(let V=0;V<y;++V){let K=V*x-g.left;for(let X=0;X<m;++X){let ee=Number.MIN_SAFE_INTEGER,J=H<0?0:H,ae=K<0?0:K;for(let Y=0;Y<_;++Y){let ue=H+Y*T;if(ue>=0&&ue<p)for(let ne=0;ne<I;++ne){let de=K+ne*E;if(de>=0&&de<f){let he=u[D][ue][de][X]+h[Y][ne][X];he>ee&&(ee=he,J=ue,ae=de)}}}$[D][J][ae][X]+=F[D][P][V][X]}}}return{dataId:c.write(v.toTypedArray($,r.dtype),r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}};function YF(e){let{inputs:t,backend:n}=e,{dy:r,y:a}=t;ve([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 c=i[l];c>=1?s[l]=o[l]:s[l]=o[l]*(c+1)}return n.makeTensorInfo(a.shape,"float32",s)}var QF={kernelName:Sh,backendName:"cpu",kernelFunc:YF},eM=Rt((e,t)=>e===t?1:0),Xx=Ht(Yi,eM,null,"bool"),tM={kernelName:Yi,backendName:"cpu",kernelFunc:Xx},nM=C.ERF_P,rM=C.ERF_A1,aM=C.ERF_A2,sM=C.ERF_A3,iM=C.ERF_A4,oM=C.ERF_A5,lM=st(Ji,e=>{let t=Math.sign(e),n=Math.abs(e),r=1/(1+nM*n);return t*(1-((((oM*r+iM)*r+sM)*r+aM)*r+rM)*r*Math.exp(-n*n))}),uM={kernelName:Ji,backendName:"cpu",kernelFunc:lM};function qd(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),yt({inputs:{x:a},backend:n,attrs:{shape:o}})}var cM={kernelName:Qi,backendName:"cpu",kernelFunc:qd},hM=Rt((e,t)=>e/t),fA=Ht(ss,hM),mA={kernelName:ss,backendName:"cpu",kernelFunc:fA};function Kx(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,c=[a,s],u=v.sizeFromShape(c),h=v.getTypedArrayFromDType("float32",u),d=v.getTypedArrayFromDType("float32",u);for(let A=0;A<a;A++){let y=ri({inputs:{x:o},backend:n,attrs:{begin:[A,0],size:[1,s]}}),g=ri({inputs:{x:l},backend:n,attrs:{begin:[A,0],size:[1,s]}}),w=Tn({inputs:{real:y,imag:g},backend:n}),{real:x,imag:_}=dM(w,t,n),I=C.mergeRealAndImagArrays(x,_);for(let T=0;T<s;T++){let E=C.getComplexWithIndex(I,T);h[A*s+T]=E.real,d[A*s+T]=E.imag}n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(w)}let p=n.makeTensorInfo(c,"float32",h),f=n.makeTensorInfo(c,"float32",d),m=Tn({inputs:{real:p,imag:f},backend:n});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),m}function dM(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(pM(r)){let o=AA(s,i,r,t,n),l=[e.shape[0],e.shape[1]];if(t){let c=n.makeTensorInfo(l,"float32",o.real),u=n.makeTensorInfo(l,"float32",o.imag),h=n.makeTensorInfo([],"float32",v.createScalarValue(r,"float32")),d=Pr({inputs:{x:h},backend:n}),p=mA.kernelFunc({inputs:{a:c,b:h},backend:n}),f=mA.kernelFunc({inputs:{a:u,b:d},backend:n}),m=n.data.get(p.dataId).values,A=n.data.get(f.dataId).values;return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),{real:m,imag:A}}return o}else{let o=C.mergeRealAndImagArrays(s,i),l=fM(o,r,t);return C.splitRealAndImagArrays(l)}}function pM(e){return(e&e-1)==0}function AA(e,t,n,r,a){if(n===1)return{real:e,imag:t};let s=C.mergeRealAndImagArrays(e,t),i=n/2,o=C.complexWithEvenIndex(s),l=o.real,c=o.imag,u=[l.length],h=a.makeTensorInfo(u,"float32",l),d=a.makeTensorInfo(u,"float32",c),p=Tn({inputs:{real:h,imag:d},backend:a}),f=C.complexWithOddIndex(s),m=f.real,A=f.imag,y=[m.length],g=a.makeTensorInfo(y,"float32",m),w=a.makeTensorInfo(y,"float32",A),x=Tn({inputs:{real:g,imag:w},backend:a}),_=AA(l,c,i,r,a),I=_.real,T=_.imag,E=[I.length],N=a.makeTensorInfo(E,"float32",I),F=a.makeTensorInfo(E,"float32",T),$=Tn({inputs:{real:N,imag:F},backend:a}),D=AA(m,A,i,r,a),P=D.real,H=D.imag,V=[P.length],K=a.makeTensorInfo(V,"float32",P),X=a.makeTensorInfo(V,"float32",H),ee=Tn({inputs:{real:K,imag:X},backend:a}),J=C.exponents(n,r),ae=[J.real.length],Y=a.makeTensorInfo(ae,"float32",J.real),ue=a.makeTensorInfo(ae,"float32",J.imag),ne=Tn({inputs:{real:Y,imag:ue},backend:a}),de=cA({inputs:{a:ne,b:ee},backend:a}),he=nc({inputs:{a:$,b:de},backend:a}),me=hA({inputs:{a:$,b:de},backend:a}),Ae=ni({inputs:{input:he},backend:a}),ke=ni({inputs:{input:me},backend:a}),Ee=dl({inputs:{input:he},backend:a}),Re=dl({inputs:{input:me},backend:a}),Oe=pl({inputs:[Ae,ke],backend:a,attrs:{axis:0}}),Ke=pl({inputs:[Ee,Re],backend:a,attrs:{axis:0}}),Ve=a.data.get(Oe.dataId).values,rt=a.data.get(Ke.dataId).values;return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(p),a.disposeIntermediateTensorInfo(g),a.disposeIntermediateTensorInfo(w),a.disposeIntermediateTensorInfo(x),a.disposeIntermediateTensorInfo(N),a.disposeIntermediateTensorInfo(F),a.disposeIntermediateTensorInfo($),a.disposeIntermediateTensorInfo(K),a.disposeIntermediateTensorInfo(X),a.disposeIntermediateTensorInfo(ee),a.disposeIntermediateTensorInfo(Y),a.disposeIntermediateTensorInfo(ue),a.disposeIntermediateTensorInfo(ne),a.disposeIntermediateTensorInfo(de),a.disposeIntermediateTensorInfo(he),a.disposeIntermediateTensorInfo(me),a.disposeIntermediateTensorInfo(Ae),a.disposeIntermediateTensorInfo(Ee),a.disposeIntermediateTensorInfo(ke),a.disposeIntermediateTensorInfo(Re),a.disposeIntermediateTensorInfo(Oe),a.disposeIntermediateTensorInfo(Ke),{real:Ve,imag:rt}}function fM(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=C.exponent(a*o,t,n),c=C.getComplexWithIndex(e,o);s+=c.real*l.real-c.imag*l.imag,i+=c.real*l.imag+c.imag*l.real}n&&(s/=t,i/=t),C.assignToTypedArray(r,s,i,a)}return r}function mM(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=yt({inputs:{x:r},backend:n,attrs:{shape:[i,s]}}),l=Kx(o,!1,n),c=yt({inputs:{x:l},backend:n,attrs:{shape:r.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(l),c}var AM={kernelName:Th,backendName:"cpu",kernelFunc:mM};function yA(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 yM(o,a,i),t.makeTensorInfo(r,i,o)}var gM={kernelName:hu,backendName:"cpu",kernelFunc:yA};function yM(e,t,n){e.fill(t)}var xM={kernelName:to,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,c]=r.shape,u=a.data.get(r.dataId).values;for(let h=0;h<i;h++){let d=h*l*o*c;for(let p=0;p<o;p++){let f=p*(l*c);for(let m=0;m<l;m++){let A=m*c;for(let y=0;y<c;y++){let g=[i,p,m,y][2],w=Math.round(l-g),x=d+f+A+y,_=u[x];if(w>=0&&w<l){let I=w*c,T=d+f+I+y;_=u[T]}s[x]=_}}}}return{dataId:a.write(s,r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}},wM=Rt((e,t)=>Math.floor(e/t)),_M=Ht(ls,wM,null,"int32"),bM={kernelName:ls,backendName:"cpu",kernelFunc:_M};function vM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dataFormat:u,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=Gx({inputs:{x:a,filter:s},backend:n,attrs:{strides:l,pad:c,dataFormat:u,dilations:h,dimRoundingMode:d}});if(i){let A=m;m=nc({inputs:{a:m,b:i},backend:n}),n.disposeIntermediateTensorInfo(A)}if(p){let A=m;m=dA(n,m,p,o,f),n.disposeIntermediateTensorInfo(A)}return m}var kM={kernelName:Ws,backendName:"cpu",kernelFunc:vM};function IM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dataFormat:u,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=qx({inputs:{x:a,filter:s},backend:n,attrs:{strides:l,pad:c,dataFormat:u,dilations:h,dimRoundingMode:d}});if(i){let A=m;m=nc({inputs:{a:m,b:i},backend:n}),n.disposeIntermediateTensorInfo(A)}if(p){let A=m;m=dA(n,m,p,o,f),n.disposeIntermediateTensorInfo(A)}return m}var NM={kernelName:Bs,backendName:"cpu",kernelFunc:IM};function SM(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,c,u,h]=C.prepareAndValidate(r,a);if(c===0)return n.makeTensorInfo(l,r.dtype,[]);let d=We([c,u],r.dtype),p=n.data.get(a.dataId).values,f=n.data.get(r.dataId).values;for(let m=0;m<c;m++){let A=[],y=0;for(let g=0;g<o;g++){let w=p[m*o+g];y+=w*h[g],A.push(w)}if(y<0||y>=s/u)throw new Error(`Invalid indices: ${A} does not index into ${r.shape}`);for(let g=0;g<u;g++)d.values[m*u+g]=f[y*u+g]}return n.makeTensorInfo(l,d.dtype,d.values)}var TM={kernelName:ro,backendName:"cpu",kernelFunc:SM};function EM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=r;ve([a,s],"gatherV2");let l=o;o==null&&(l=0);let c=v.sizeFromShape(s.shape),u=v.parseAxisParam(i,a.shape)[0],h=C.segment_util.collectGatherOpShapeInfo(a,s,u,l),d=yt({inputs:{x:a},backend:n,attrs:{shape:[h.batchSize,h.outerSize,h.dimSize,h.sliceSize]}}),p=yt({inputs:{x:s},backend:n,attrs:{shape:[h.batchSize,c/h.batchSize]}}),f=[h.batchSize,h.outerSize,c/h.batchSize,h.sliceSize],m=n.bufferSync(p),A=n.bufferSync(d),y=xx(A,m,f);return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),n.makeTensorInfo(h.outputShape,y.dtype,y.values)}var CM={kernelName:no,backendName:"cpu",kernelFunc:EM},RM=Rt((e,t)=>e>=t?1:0),FM=Ht(cs,RM,null,"bool"),MM={kernelName:cs,backendName:"cpu",kernelFunc:FM};function $M(e){let{inputs:t,backend:n}=e,{input:r}=t,a=v.sizeFromShape(r.shape),s=r.shape[r.shape.length-1],i=a/s,o=yt({inputs:{x:r},backend:n,attrs:{shape:[i,s]}}),l=Kx(o,!0,n),c=yt({inputs:{x:l},backend:n,attrs:{shape:r.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(l),c}var DM={kernelName:Eh,backendName:"cpu",kernelFunc:$M},OM=st(io,e=>Number.isFinite(e)?1:0,"bool"),zM={kernelName:io,backendName:"cpu",kernelFunc:OM},PM=st(oo,e=>Math.abs(e)===Infinity?1:0,"bool"),LM={kernelName:oo,backendName:"cpu",kernelFunc:PM},WM=st(lo,e=>Number.isNaN(e)?1:0,"bool"),BM={kernelName:lo,backendName:"cpu",kernelFunc:WM},VM=Rt((e,t)=>e<=t?1:0),UM=Ht(co,VM,null,"bool"),HM={kernelName:co,backendName:"cpu",kernelFunc:UM};function jM(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=bx(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var GM={kernelName:Rh,backendName:"cpu",kernelFunc:jM},qM=st(ho,e=>Math.log1p(e)),XM={kernelName:ho,backendName:"cpu",kernelFunc:qM},KM=Rt((e,t)=>e&&t),ZM=Ht(po,KM,null,"bool"),JM={kernelName:po,backendName:"cpu",kernelFunc:ZM},YM=st(du,e=>e?0:1,"bool"),QM={kernelName:du,backendName:"cpu",kernelFunc:YM},e$=Rt((e,t)=>e||t),t$=Ht(pu,e$,null,"bool"),n$={kernelName:pu,backendName:"cpu",kernelFunc:t$};function r$(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r;ve(a,"LRN");let c=a.shape[3],u=c-1,h=n.data.get(a.dataId).values,d=v.sizeFromShape(a.shape),p=new Float32Array(d);function f(m){let A=m%c,y=m-A+Math.max(0,A-s),g=m-A+Math.min(A+s,u),w=0;for(;y<=g;y++){let x=h[y];w+=x*x}return w}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 a$={kernelName:fu,backendName:"cpu",kernelFunc:r$};function s$(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:c,beta:u}=r;ve(i,"LRNGrad");let h=v.sizeFromShape(i.shape),d=i.shape[3],p=n.data.get(i.dataId).values,f=n.data.get(a.dataId).values,m=n.data.get(s.dataId).values,A=new Float32Array(h),y=h;for(let g=0;g<y;g++){let w=g%d,x=g-w+Math.max(0,w-o),_=g-w+Math.min(d,w+o+1),I=0;for(let T=x;T<_;T++)I+=Math.pow(f[T],2);I=c*I+l;for(let T=x;T<_;T++){let E=-2*c*u*f[T]*m[g]/I;g===T&&(E+=Math.pow(I,-u)),E*=p[g],A[T]+=E}}return n.makeTensorInfo(i.shape,a.dtype,A)}var i$={kernelName:Fh,backendName:"cpu",kernelFunc:s$};function Zx(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=r,o=n,l=a.shape,c=l.length,u=v.parseAxisParam(s,l),h=u,d=C.getAxesPermutation(h,c),p=o.data.get(a.dataId).values;if(d!=null){let x=new Array(c);for(let _=0;_<x.length;_++)x[_]=l[d[_]];p=oA(p,l,a.dtype,d,x),h=C.getInnerMostAxes(h.length,c),l=x}ve(a,"max"),C.assertAxesAreInnerMostDims("max",h,c);let[f,m]=C.computeOutAndReduceShapes(l,h),A=v.sizeFromShape(m),y=kx(p,A,f,a.dtype),g=o.write(y,f,a.dtype),w=f;return i&&(w=C.expandShapeToKeepDim(f,u)),{dataId:g,shape:w,dtype:a.dtype}}var o$={kernelName:ps,backendName:"cpu",kernelFunc:Zx};function l$(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;ve(a,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(C.eitherStridesOrDilationsAreOne(i,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=C.computePool2DInfo(a.shape,s,i,c,o,l),h;if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))h=Pr({inputs:{x:a},backend:n});else{let d=n.data.get(a.dataId).values,p=v.computeStrides(a.shape),f=pA(d,a.shape,a.dtype,p,u,"max");h=n.makeTensorInfo(u.outShape,a.dtype,f.values)}return h}var u$={kernelName:ms,backendName:"cpu",kernelFunc:l$};function c$(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:c}=r;ve(a,"maxPool3d");let u=C.computePool3DInfo(a.shape,s,i,1,o,l,c),h=n.data.get(a.dataId).values,d=jx(h,a.shape,a.dtype,v.computeStrides(a.shape),u,"max");return n.makeTensorInfo(d.shape,"float32",d.values)}var h$={kernelName:mu,backendName:"cpu",kernelFunc:c$};function d$(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:c}=r;ve([a,s],"maxPool3DGrad");let u=C.computePool3DInfo(s.shape,i,o,1,l,c),h=n.bufferSync(s),d=YR(h,u),p=u.strideDepth,f=u.strideHeight,m=u.strideWidth,A=u.dilationDepth,y=u.dilationHeight,g=u.dilationWidth,w=u.effectiveFilterDepth,x=u.effectiveFilterHeight,_=u.effectiveFilterWidth,I=w-1-u.padInfo.front,T=_-1-u.padInfo.left,E=x-1-u.padInfo.top,N=We(s.shape,"float32"),F=n.bufferSync(a);for(let $=0;$<u.batchSize;++$)for(let D=0;D<u.inChannels;++D)for(let P=0;P<u.inDepth;++P)for(let H=0;H<u.inHeight;++H)for(let V=0;V<u.inWidth;++V){let K=P-I,X=H-E,ee=V-T,J=0;for(let ae=0;ae<w;ae+=A){let Y=(K+ae)/p;if(!(Y<0||Y>=u.outDepth||Math.floor(Y)!==Y))for(let ue=0;ue<x;ue+=y){let ne=(X+ue)/f;if(!(ne<0||ne>=u.outHeight||Math.floor(ne)!==ne))for(let de=0;de<_;de+=g){let he=(ee+de)/m;if(he<0||he>=u.outWidth||Math.floor(he)!==he)continue;let me=w*x*_-1-d.get($,Y,ne,he,D),Ae=ae*x*_+ue*_+de,ke=me===Ae?1:0;ke!==0&&(J+=F.get($,Y,ne,he,D)*ke)}}}N.set(J,$,P,H,V,D)}return n.makeTensorInfo(N.shape,N.dtype,N.values)}var p$={kernelName:$h,backendName:"cpu",kernelFunc:d$};function f$(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;ve([s,i],"maxPoolGrad");let{filterSize:l,strides:c,pad:u,dimRoundingMode:h}=r,d=C.computePool2DInfo(o.shape,l,c,1,u,h),p=n.data.get(o.dataId).values,f=We(d.outShape,o.dtype,Hx(p,o.shape,o.dtype,d).values),m=d.strideHeight,A=d.strideWidth,y=d.dilationHeight,g=d.dilationWidth,w=d.effectiveFilterHeight,x=d.effectiveFilterWidth,_=x-1-d.padInfo.left,I=w-1-d.padInfo.top,T=We(o.shape,"float32"),E=n.data.get(a.dataId).values,N=We(a.shape,"float32",E);for(let F=0;F<d.batchSize;++F)for(let $=0;$<d.inChannels;++$)for(let D=0;D<d.inHeight;++D)for(let P=0;P<d.inWidth;++P){let H=D-I,V=P-_,K=0;for(let X=0;X<w;X+=y){let ee=(H+X)/m;if(!(ee<0||ee>=d.outHeight||Math.floor(ee)!==ee))for(let J=0;J<x;J+=g){let ae=(V+J)/A;if(ae<0||ae>=d.outWidth||Math.floor(ae)!==ae)continue;let Y=w*x-1-f.get(F,ee,ae,$),ue=X*x+J,ne=Y===ue?1:0;ne!==0&&(K+=N.get(F,ee,ae,$)*ne)}}T.set(K,F,D,P,$)}return n.makeTensorInfo(T.shape,T.dtype,T.values)}var m$={kernelName:Mh,backendName:"cpu",kernelFunc:f$};function A$(e,t,n,r,a){let s=v.computeStrides(t),i=pA(e,t,n,s,a,"max"),o=Hx(e,t,n,a,!0,r);return[i.values,o.values]}var y$={kernelName:Dh,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;ve(r,"MaxPoolWithArgmax");let c=l.data.get(r.dataId).values,u=C.computePool2DInfo(r.shape,a,s,[1,1],i),[h,d]=A$(c,r.shape,r.dtype,o,u),p=l.write(h,u.outShape,r.dtype),f=l.write(d,u.outShape,r.dtype);return[{dataId:p,shape:u.outShape,dtype:r.dtype},{dataId:f,shape:u.outShape,dtype:"int32"}]}};function Xd(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;ve(a,"sum");let o;a.dtype==="bool"?o=Ca({inputs:{x:a},backend:n,attrs:{dtype:"int32"}}):o=Pr({inputs:{x:a},backend:n});let l=o.shape.length,c=v.parseAxisParam(s,o.shape),u=C.getAxesPermutation(c,l),h=c,d=o;u!=null&&(d=sr({inputs:{x:o},backend:n,attrs:{perm:u}}),h=C.getInnerMostAxes(h.length,l)),C.assertAxesAreInnerMostDims("sum",h,d.shape.length);let[p,f]=C.computeOutAndReduceShapes(d.shape,h),m=C.upcastType(d.dtype,"int32"),A=Gd(n,p,m),y=v.sizeFromShape(f),g=n.data.get(A.dataId).values,w=n.data.get(d.dataId).values;for(let x=0;x<g.length;++x){let _=x*y,I=0;for(let T=0;T<y;++T)I+=w[_+T];g[x]=I}if(i){let x=C.expandShapeToKeepDim(A.shape,c),_=A;A=yt({inputs:{x:A},backend:n,attrs:{shape:x}}),n.disposeIntermediateTensorInfo(_)}return n.disposeIntermediateTensorInfo(o),u!=null&&n.disposeIntermediateTensorInfo(d),A}var g$={kernelName:Ms,backendName:"cpu",kernelFunc:Xd};function x$(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=v.parseAxisParam(s,a.shape),l=C.computeOutAndReduceShapes(a.shape,o)[1],c=v.sizeFromShape(l),u=[],h=n.makeTensorInfo([],"float32",new Float32Array([c]));u.push(h);let d=Ca({inputs:{x:a},backend:n,attrs:{dtype:"float32"}});u.push(d);let p=fA({inputs:{a:d,b:h},backend:n});u.push(p);let f=Xd({inputs:{x:p},backend:n,attrs:{axis:s,keepDims:i}});return u.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var w$={kernelName:As,backendName:"cpu",kernelFunc:x$};function _$(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;ve(a,"min");let o=v.parseAxisParam(s,a.shape),l=o,c=C.getAxesPermutation(l,a.shape.length),u=a;c!=null&&(u=sr({inputs:{x:a},backend:n,attrs:{perm:c}}),l=C.getInnerMostAxes(l.length,a.shape.length)),C.assertAxesAreInnerMostDims("min",l,u.shape.length);let[h,d]=C.computeOutAndReduceShapes(u.shape,l),p=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(h),u.dtype),m=n.data.get(u.dataId).values;for(let y=0;y<f.length;++y){let g=y*p,w=m[g];for(let x=0;x<p;++x){let _=m[g+x];_<w&&(w=_)}f[y]=w}c!=null&&n.disposeIntermediateTensorInfo(u);let A=n.makeTensorInfo(h,u.dtype,f);if(i){let y=C.expandShapeToKeepDim(h,o),g=yt({inputs:{x:A},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(A),g}return A}var b$={kernelName:ys,backendName:"cpu",kernelFunc:_$};function v$(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,mode:i}=r;ve(a,"mirrorPad");let o=s.map((g,w)=>g[0]+a.shape[w]+g[1]),l=s.map(g=>g[0]),c=s.map((g,w)=>g[0]+a.shape[w]),u=i==="reflect"?0:1,h=n.data.get(a.dataId).values,d=a.shape.length,p=v.computeStrides(a.shape),f=v.sizeFromShape(o),m=o.length,A=v.computeStrides(o),y=v.getTypedArrayFromDType(a.dtype,f);for(let g=0;g<f;g++){let w=v.indexToLoc(g,m,A);for(let _=0;_<m;_++)w[_]<l[_]?w[_]=l[_]*2-w[_]-u:w[_]>=c[_]&&(w[_]=(c[_]-1)*2-w[_]+u);w=w.map((_,I)=>_-l[I]);let x=v.locToIndex(w,d,p);y[g]=h[x]}return{dataId:n.write(y,o,a.dtype),shape:o,dtype:a.dtype}}var k$={kernelName:Au,backendName:"cpu",kernelFunc:v$},I$=Rt((e,t)=>{let n=e%t;return e<0&&t<0||e>=0&&t>=0?n:(n+t)%t}),N$=Ht(fo,I$),S$={kernelName:fo,backendName:"cpu",kernelFunc:N$},T$=Qo(K8());function Jx(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 ${o}`);let l=v.parseAxisParam([o],a.shape),c=Zx({inputs:{x:a},backend:n,attrs:{reductionIndices:l,keepDims:!1}}),u=C.expandShapeToKeepDim(c.shape,l),h=yt({inputs:{x:c},backend:n,attrs:{shape:u}}),d=hA({inputs:{a,b:h},backend:n}),p=zx({inputs:{x:d},backend:n}),f=Xd({inputs:{x:p},backend:n,attrs:{axis:l,keepDims:!1}}),m=yt({inputs:{x:f},backend:n,attrs:{shape:u}}),A=fA({inputs:{a:p,b:m},backend:n});return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),A}var E$={kernelName:$s,backendName:"cpu",kernelFunc:Jx};function C$(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r;ve(a,"multinomial");let l=o?a:Jx({inputs:{logits:a},backend:n,attrs:{dim:-1}}),c=l.shape[0],u=l.shape[1],h=n.data.get(l.dataId).values,d=[c,s],p=v.makeZerosTypedArray(v.sizeFromShape(d),"int32");for(let f=0;f<c;++f){let m=f*u,A=new Float32Array(u-1);A[0]=h[m];for(let w=1;w<A.length;++w)A[w]=A[w-1]+h[m+w];let y=T$.alea(i.toString()),g=f*s;for(let w=0;w<s;++w){let x=y();p[g+w]=A.length;for(let _=0;_<A.length;_++)if(x<A[_]){p[g+w]=_;break}}}return o||n.disposeIntermediateTensorInfo(l),n.makeTensorInfo(d,"int32",p)}var R$={kernelName:Oh,backendName:"cpu",kernelFunc:C$},F$=Rr.nonMaxSuppressionV3Impl;function M$(e){let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=r;ve(a,"NonMaxSuppression");let c=n.data.get(a.dataId).values,u=n.data.get(s.dataId).values,{selectedIndices:h}=F$(c,u,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var $$={kernelName:yo,backendName:"cpu",kernelFunc:M$},D$=Rr.nonMaxSuppressionV4Impl;function O$(e){let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:c}=r;ve(a,"NonMaxSuppressionPadded");let u=n.data.get(a.dataId).values,h=n.data.get(s.dataId).values,{selectedIndices:d,validOutputs:p}=D$(u,h,i,o,l,c);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var z$={kernelName:go,backendName:"cpu",kernelFunc:O$},P$=Rr.nonMaxSuppressionV5Impl;function L$(e){let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:c}=r;ve(a,"NonMaxSuppressionWithScore");let u=n.data.get(a.dataId).values,h=n.data.get(s.dataId).values,d=i,p=o,f=l,m=c,{selectedIndices:A,selectedScores:y}=P$(u,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var W$={kernelName:xo,backendName:"cpu",kernelFunc:L$};function B$(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r;ve(a,"oneHot");let l=v.sizeFromShape(a.shape),c=new Float32Array(l*s);c.fill(o);let u=n.data.get(a.dataId).values;for(let h=0;h<l;++h)u[h]>=0&&u[h]<s&&(c[h*s+u[h]]=i);return n.makeTensorInfo([...a.shape,s],"int32",c)}var V$={kernelName:ws,backendName:"cpu",kernelFunc:B$};function Kd(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=ni({inputs:{input:r},backend:n}),s=Kd({inputs:{x:a},backend:n}),i=dl({inputs:{input:r},backend:n}),o=Kd({inputs:{x:i},backend:n}),l=Tn({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return yA({backend:n,attrs:{shape:r.shape,value:0,dtype:r.dtype}})}var U$={kernelName:zo,backendName:"cpu",kernelFunc:Kd};function Yx(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=ni({inputs:{input:r},backend:n}),s=Yx({inputs:{x:a},backend:n}),i=dl({inputs:{input:r},backend:n}),o=Kd({inputs:{x:i},backend:n}),l=Tn({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return yA({backend:n,attrs:{shape:r.shape,value:1,dtype:r.dtype}})}var H$={kernelName:wo,backendName:"cpu",kernelFunc:Yx};function Qx(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return qd({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(u=>{v.assertShapesMatch(s,u.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===u.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(u=>{let h=qd({inputs:{input:u},backend:n,attrs:{dim:a}});return o.push(h),h}),c=pl({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(u=>n.disposeIntermediateTensorInfo(u)),c}var j$={kernelName:_o,backendName:"cpu",kernelFunc:Qx};function G$(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r;ve(a,"pad");let o=s.map((y,g)=>y[0]+a.shape[g]+y[1]),l=s.map(y=>y[0]),c=n.data.get(a.dataId).values,u=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<u;y++){let g=v.indexToLoc(y,h,d).map((x,_)=>x+l[_]),w=v.locToIndex(g,f,m);A[w]=c[y]}return{dataId:n.write(A,o,a.dtype),shape:o,dtype:a.dtype}}var ew={kernelName:_s,backendName:"cpu",kernelFunc:G$},q$=Rt((e,t)=>Math.pow(e,t)),X$=Ht(bs,q$),K$={kernelName:bs,backendName:"cpu",kernelFunc:X$};function Z$(e){let{backend:t,attrs:n}=e,{start:r,stop:a,dtype:s,step:i}=n,o=lA(r,a,i,s);return t.makeTensorInfo([o.length],s,o)}var J$={kernelName:yu,backendName:"cpu",kernelFunc:Z$},Y$=st(vo,e=>1/e),Q$={kernelName:vo,backendName:"cpu",kernelFunc:Y$};function eD(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r;ve(a,"resizeBilinear");let l=v.computeStrides(a.shape),[c,u]=o,[h,d,p,f]=a.shape,m=n.data.get(a.dataId).values,A=new Float32Array(v.sizeFromShape([h,c,u,f])),y=[s&&c>1?d-1:d,s&&u>1?p-1:p],g=[s&&c>1?c-1:c,s&&u>1?u-1:u],w=0,x=y[0]/g[0],_=y[1]/g[1];for(let I=0;I<h;I++)for(let T=0;T<c;T++){let E;i?E=x*(T+.5)-.5:E=x*T;let N=Math.max(0,Math.floor(E)),F=E-N,$=Math.min(d-1,Math.ceil(E)),D=I*l[0]+N*l[1],P=I*l[0]+$*l[1];for(let H=0;H<u;H++){let V;i?V=_*(H+.5)-.5:V=_*H;let K=Math.max(0,Math.floor(V)),X=V-K,ee=Math.min(p-1,Math.ceil(V)),J=D+K*l[2],ae=P+K*l[2],Y=D+ee*l[2],ue=P+ee*l[2];for(let ne=0;ne<f;ne++){let de=m[J+ne],he=m[ae+ne],me=m[Y+ne],Ae=m[ue+ne],ke=de+(me-de)*X,Ee=he+(Ae-he)*X,Re=ke+(Ee-ke)*F;A[w++]=Re}}}return n.makeTensorInfo([h,c,u,f],"float32",A)}var tD={kernelName:Is,backendName:"cpu",kernelFunc:eD};function nD(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r;ve([s,a],"resizeBilinearGrad");let o=v.computeStrides(a.shape),[l,c,u,h]=a.shape,[,d,p]=s.shape,f=new Float32Array(l*c*u*h),m=[i&&d>1?c-1:c,i&&p>1?u-1:u],A=[i&&d>1?d-1:d,i&&p>1?p-1:p],y=m[0]/A[0],g=m[1]/A[1],w=n.data.get(s.dataId).values,x=0;for(let _=0;_<l;_++){let I=_*o[0];for(let T=0;T<d;T++){let E=T*y,N=Math.floor(E),F=Math.min(Math.ceil(E),c-1),$=I+N*o[1],D=I+F*o[1],P=E-N,H=1-P;for(let V=0;V<p;V++){let K=V*g,X=Math.floor(K),ee=Math.min(Math.ceil(K),u-1),J=K-X,ae=1-J,Y=$+X*o[2],ue=$+ee*o[2],ne=D+X*o[2],de=D+ee*o[2],he=H*ae,me=H*J,Ae=P*ae,ke=P*J;for(let Ee=0;Ee<h;Ee++){let Re=w[x++];f[Y+Ee]+=Re*he,f[ue+Ee]+=Re*me,f[ne+Ee]+=Re*Ae,f[de+Ee]+=Re*ke}}}}return n.makeTensorInfo([l,u,c,h],"float32",f)}var rD={kernelName:Lh,backendName:"cpu",kernelFunc:nD};function aD(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r;ve(a,"resizeNearestNeighbor");let l=v.computeStrides(a.shape),[c,u]=o,[h,d,p,f]=a.shape,m=n.data.get(a.dataId).values,A=new Float32Array(h*c*u*f),y=[s&&c>1?d-1:d,s&&u>1?p-1:p],g=[s&&c>1?c-1:c,s&&u>1?u-1:u],w=y[0]/g[0],x=y[1]/g[1],_=0;for(let I=0;I<h;I++){let T=I*l[0];for(let E=0;E<c;E++){let N=i?w*(E+.5):w*E,F=Math.min(d-1,s?Math.round(N):Math.floor(N));i&&(F=Math.max(0,F));let $=T+F*l[1];for(let D=0;D<u;D++){let P=i?x*(D+.5):x*D,H=Math.min(p-1,s?Math.round(P):Math.floor(P));i&&(H=Math.max(0,H));let V=$+H*l[2];for(let K=0;K<f;K++){let X=m[V+K];A[_++]=X}}}}return n.makeTensorInfo([h,c,u,f],a.dtype,A)}var sD={kernelName:gu,backendName:"cpu",kernelFunc:aD};function iD(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r;ve([s,a],"resizeNearestNeighborGrad");let o=v.computeStrides(a.shape),l=v.computeStrides(s.shape),[c,u,h,d]=a.shape,[,p,f]=s.shape,m=new Float32Array(c*u*h*d),A=n.data.get(s.dataId).values,y=[i&&p>1?u-1:u,i&&f>1?h-1:h],g=[i&&p>1?p-1:p,i&&f>1?f-1:f],w=y[0]/g[0],x=y[1]/g[1],_=1/w,I=1/x,T=Math.ceil(_)*2+2,E=Math.ceil(I)*2+2;for(let N=0;N<c;N++){let F=N*o[0];for(let $=0;$<u;$++){let D=F+$*o[1],P=Math.floor($*_),H=Math.floor(P-T/2);for(let V=0;V<h;V++){let K=D+V*o[2],X=Math.floor(V*I),ee=Math.floor(X-E/2);for(let J=0;J<d;J++){let ae=0;for(let Y=0;Y<T;Y++){let ue=Y+H;if(ue<0||ue>=p)continue;let ne=F+ue*l[1],de=ue*w,he=Math.min(u-1,i?Math.round(de):Math.floor(de));if($===he)for(let me=0;me<E;me++){let Ae=me+ee;if(Ae<0||Ae>=f)continue;let ke=ne+Ae*l[2],Ee=Ae*x,Re=Math.min(h-1,i?Math.round(Ee):Math.floor(Ee));V===Re&&(ae+=A[ke+J])}}m[K+J]=ae}}}}return n.makeTensorInfo(a.shape,a.dtype,m)}var oD={kernelName:Ph,backendName:"cpu",kernelFunc:iD};function lD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dims:s}=r;ve(a,"reverse");let i=a.shape.length,o=v.parseAxisParam(s,a.shape);if(i===0)return Pr({inputs:{x:a},backend:n});let l=new Mt(a.shape,a.dtype),c=n.bufferSync(a);for(let u=0;u<l.size;u++){let h=l.indexToLoc(u),d=h.slice();o.forEach(p=>d[p]=a.shape[p]-1-d[p]),l.set(c.get(...d),...h)}return n.makeTensorInfo(l.shape,l.dtype,l.values)}var uD={kernelName:Ss,backendName:"cpu",kernelFunc:lD},cD={kernelName:Po,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)),[c,u,h,d]=r.shape,[p,f]=C.getImageCenter(i,u,h),m=255,A=Math.sin(a),y=Math.cos(a),g=o.data.get(r.dataId).values;for(let w=0;w<c;w++){let x=w*h*u*d;for(let _=0;_<u;_++){let I=_*(h*d);for(let T=0;T<h;T++){let E=T*d;for(let N=0;N<d;N++){let F=[c,_,T,N],$=F[2],D=F[1],P=($-p)*y-(D-f)*A,H=($-p)*A+(D-f)*y;P=Math.round(P+p),H=Math.round(H+f);let V=s;if(typeof s!="number"&&(N===3?V=m:V=s[N]),P>=0&&P<h&&H>=0&&H<u){let X=H*(h*d),ee=P*d,J=x+X+ee+N;V=g[J]}let K=x+I+E+N;l[K]=V}}}}return{dataId:o.write(l,r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}},hD=st(Ts,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}),dD={kernelName:Ts,backendName:"cpu",kernelFunc:hD};function tw(e,t,n,r,a,s,i,o,l,c){let u=[r/a,a],h=e.values,d=t.values;if(r===0)return We(n,t.dtype);let p=We(u,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++)c?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 pD(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a,updates:s}=t,{shape:i}=r,{sliceRank:o,numUpdates:l,sliceSize:c,strides:u,outputSize:h}=C.calculateShapes(s,a,i),d=!0,p=n.bufferSync(a),f=n.bufferSync(s),m=tw(p,f,i,h,c,l,o,u,0,d);return n.makeTensorInfo(i,m.dtype,m.values)}var fD={kernelName:Io,backendName:"cpu",kernelFunc:pD};function mD(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t;ve([r,a,s],"select");let i=r.shape.length,o=n.data.get(r.dataId).values,l=n.data.get(a.dataId).values,c=n.data.get(s.dataId).values,u=Qn(a.dtype,s.dtype),h=v.makeZerosTypedArray(v.sizeFromShape(a.shape),u),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++]=c[f];return n.makeTensorInfo(a.shape,u,h)}var AD={kernelName:No,backendName:"cpu",kernelFunc:mD},yD=C.SELU_SCALEALPHA,gD=C.SELU_SCALE,xD=st(So,e=>e>=0?gD*e:yD*(Math.exp(e)-1)),wD={kernelName:So,backendName:"cpu",kernelFunc:xD},_D=st(Rs,e=>1/(1+Math.exp(-e))),bD={kernelName:Rs,backendName:"cpu",kernelFunc:_D},vD=st(Co,e=>e<0?-1:e>0?1:0),kD={kernelName:Co,backendName:"cpu",kernelFunc:vD},ID=st(Cs,e=>Math.sin(e)),ND={kernelName:Cs,backendName:"cpu",kernelFunc:ID},SD=st(Eo,e=>Math.sinh(e)),TD={kernelName:Eo,backendName:"cpu",kernelFunc:SD},ED=11920928955078125e-23,nw=Math.log(ED)+2,CD=st(Ro,e=>{let t=e>-nw,n=e<nw,r=Math.exp(e),a;return n?a=r:t?a=e:a=Math.log(1+r),a}),RD={kernelName:Ro,backendName:"cpu",kernelFunc:CD};function FD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,paddings:i}=r;ve([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 c=ew.kernelFunc({inputs:{x:a},backend:n,attrs:{paddings:l,constantValue:0}}),u=C.getReshaped(c.shape,s,o,!1),h=C.getPermuted(u.length,s.length,!1),d=C.getReshapedPermuted(c.shape,s,o,!1),p=yt({inputs:{x:c},backend:n,attrs:{shape:u}}),f=sr({inputs:{x:p},backend:n,attrs:{perm:h}}),m=yt({inputs:{x:f},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),m}var MD={kernelName:xu,backendName:"cpu",kernelFunc:FD};function $D(e){let{inputs:t,backend:n,attrs:r}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=r,{sliceRank:l,numUpdates:c,sliceSize:u,strides:h,outputSize:d}=C.calculateShapes(s,a,o),p=!1,f=n.bufferSync(a),m=n.bufferSync(s),A=n.data.get(i.dataId).values[0],y=tw(f,m,o,d,u,c,l,h,A,p);return n.makeTensorInfo(o,y.dtype,y.values)}var DD={kernelName:Wh,backendName:"cpu",kernelFunc:$D};function OD(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=C.prepareSplitSize(a,s,o),c=new Array(a.shape.length).fill(0),u=a.shape.slice();return l.map(h=>{let d=[...u];d[o]=h;let p=ri({inputs:{x:a},backend:n,attrs:{begin:c,size:d}});return c[o]+=h,p})}var zD={kernelName:Fo,backendName:"cpu",kernelFunc:OD},PD=st(Fs,e=>Math.sqrt(e)),LD={kernelName:Fs,backendName:"cpu",kernelFunc:PD},WD={kernelName:wu,backendName:"cpu",kernelFunc:({inputs:e,backend:t})=>{let{x:n}=e,r=t;ve(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}}},BD=st(ya,(e,t)=>{let n=t;return isNaN(e)?NaN:e>0?1:n.alpha}),VD={kernelName:ya,backendName:"cpu",kernelFunc:BD};function UD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:c,ellipsisMask:u,newAxisMask:h,shrinkAxisMask:d}=r;ve(a,"stridedSlice");let{nonStrided:p,$begin:f,$strides:m,size:A,newShape:y,outShape:g}=rn.sliceInfo(a.shape,s,i,o,l,c,u,h,d),w=yt({inputs:{x:a},backend:n,attrs:{shape:y}}),x;if(p){let I=ri({inputs:{x:w},backend:n,attrs:{begin:f,size:A}});x=yt({inputs:{x:I},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(I)}else if(g.some(I=>I===0))x=n.makeTensorInfo(g,a.dtype,[]);else{let I=n.bufferSync(w),T=Fx(g,I,m,f);x=n.makeTensorInfo(T.shape,T.dtype,T.values)}let _=yt({inputs:{x},backend:n,attrs:{shape:g}});return n.disposeIntermediateTensorInfo(w),n.disposeIntermediateTensorInfo(x),_}var HD={kernelName:Mo,backendName:"cpu",kernelFunc:UD},jD=st($o,e=>Math.tan(e)),GD={kernelName:$o,backendName:"cpu",kernelFunc:jD},qD=st(zs,e=>Math.tanh(e)),XD={kernelName:zs,backendName:"cpu",kernelFunc:qD};function KD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reps:s}=r;ve(a,"tile");let i=$x(n.bufferSync(a),s);return n.makeTensorInfo(i.shape,i.dtype,i.values)}var ZD={kernelName:Aa,backendName:"cpu",kernelFunc:KD};function JD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{k:s,sorted:i}=r;ve(a,"topk");let o=n.data.get(a.dataId).values,[l,c]=Dx(o,a.shape,a.dtype,s,i);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(c.shape,c.dtype,c.values)]}var YD={kernelName:Do,backendName:"cpu",kernelFunc:JD};function QD(e){let{inputs:t,attrs:n,backend:r}=e,{axis:a}=n,{x:s}=t;ve(s,"unique");let i=r.data.get(s.dataId).values,{outputValues:o,outputShape:l,indices:c}=Ox(i,a,s.shape,s.dtype);return[r.makeTensorInfo(l,s.dtype,o),r.makeTensorInfo([c.length],"int32",c)]}var eO={kernelName:Bh,backendName:"cpu",kernelFunc:QD};function tO(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),c=0;for(let p=0;p<i;p++)p!==s&&(l[c++]=a.shape[p]);let u=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++){u[s]=p;let f=ri({inputs:{x:a},backend:n,attrs:{begin:u,size:h}});d[p]=yt({inputs:{x:f},backend:n,attrs:{shape:l}}),n.disposeIntermediateTensorInfo(f)}return d}var nO={kernelName:Oo,backendName:"cpu",kernelFunc:tO};function rO(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,segmentIds:s}=t,{numSegments:i}=r;ve(a,"unsortedSegmentSum");let o=a.shape.length,l=s.shape.length,c=[],u=[],h=o-l,d=s;for(let f=0;f<h;++f){let m=qd({inputs:{input:d},backend:n,attrs:{dim:f+1}});d=m,u.push(m)}for(let f=0;f<i;++f){let m=v.createScalarValue(f,"int32"),A=n.makeTensorInfo([],"int32",m),y=Xx({inputs:{a:A,b:d},backend:n}),g=Ca({inputs:{x:y},backend:n,attrs:{dtype:"float32"}}),w=cA({inputs:{a:g,b:a},backend:n}),x=Xd({inputs:{x:w},backend:n,attrs:{axis:0,keepDims:!1}});c.push(x),u.push(A),u.push(y),u.push(g),u.push(w),u.push(x)}let p=Qx({inputs:c,backend:n,attrs:{axis:0}});return u.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var aO={kernelName:_u,backendName:"cpu",kernelFunc:rO},sO=[NR,RC,TR,CR,zC,FR,$R,OR,PR,WR,VR,HR,GR,KR,JR,eF,nF,aF,iF,kR,lF,cF,dF,DC,LC,fF,FC,AF,gF,_F,vF,xF,SF,EF,IF,RF,MF,DF,zF,LF,BF,VF,HF,GF,XF,KF,JF,ZF,mA,yR,QF,tM,uM,WC,cM,VC,AM,gM,xM,HC,bM,kM,NM,TM,CM,GC,MM,MC,DM,yF,zM,LM,BM,gR,XC,HM,GM,ZC,XM,JM,QM,n$,a$,i$,YC,u$,h$,p$,m$,y$,o$,w$,b$,eR,k$,S$,R$,nR,aR,$$,z$,W$,iR,V$,H$,j$,ew,K$,wR,uR,J$,$C,Q$,_R,bR,vR,tD,rD,sD,oD,uD,cD,dD,hR,fD,AD,wD,bD,kD,ND,TD,dR,E$,RD,MD,DD,zD,LD,WD,fR,VD,HD,AR,g$,GD,XD,ZD,YD,oR,eO,nO,aO,U$];for(let e of sO)Lo(e);var b0={};ze(b0,{assertNotComplex:()=>fl,bindCanvasToFramebuffer:()=>lO,bindColorTextureToFramebuffer:()=>Jd,bindTextureToProgramUniformSampler:()=>yw,bindTextureUnit:()=>fw,bindVertexBufferToProgramAttribute:()=>gA,callAndCheck:()=>_e,canBeRepresented:()=>rw,createFragmentShader:()=>iw,createFramebuffer:()=>pw,createProgram:()=>ow,createStaticIndexBuffer:()=>cw,createStaticVertexBuffer:()=>uw,createTexture:()=>hw,createVertexShader:()=>sw,getBatchDim:()=>ai,getExtensionOrThrow:()=>rc,getFramebufferErrorMessage:()=>gw,getMaxTexturesInShader:()=>_w,getNumChannels:()=>iO,getProgramUniformLocation:()=>Aw,getProgramUniformLocationOrThrow:()=>mw,getRowsCols:()=>si,getShapeAs3D:()=>Yd,getTextureShapeFromLogicalShape:()=>xw,getWebGLDisjointQueryTimerVersion:()=>bw,getWebGLErrorMessage:()=>aw,getWebGLMaxTextureSize:()=>ww,hasExtension:()=>Un,isCapableOfRenderingToFloatTexture:()=>vw,isDownloadFloatTextureEnabled:()=>kw,isReshapeFree:()=>sc,isWebGLFenceEnabled:()=>Iw,isWebGLVersionEnabled:()=>wA,linkProgram:()=>lw,resetMaxTextureSize:()=>uO,resetMaxTexturesInShader:()=>cO,unbindColorTextureFromFramebuffer:()=>xA,unbindTextureUnit:()=>oO,validateFramebuffer:()=>ac,validateProgram:()=>Zd,validateTextureSize:()=>dw});var ii={},_A={alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!0};function pm(e,t){ii[e]=t}function Lr(e){if(!(e in ii)){let n=hO(e);if(n!==null)ii[e]=n;else return console.log("Could not get context for WebGL version",e),null}let t=ii[e];return t.isContextLost()?(delete ii[e],Lr(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),ii[e])}function dO(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 hO(e){if(e!==1&&e!==2)throw new Error("Cannot get WebGL rendering context, WebGL is disabled.");let t=dO(e);return t.addEventListener("webglcontextlost",n=>{n.preventDefault(),delete ii[e]},!1),e===1?t.getContext("webgl",_A)||t.getContext("experimental-webgl",_A):t.getContext("webgl2",_A)}var ic;(function(e){e[e.DENSE=0]="DENSE",e[e.SHARED_BATCH=1]="SHARED_BATCH"})(ic||(ic={}));var Hn;(function(e){e[e.RENDER=0]="RENDER",e[e.UPLOAD=1]="UPLOAD",e[e.PIXELS=2]="PIXELS",e[e.DOWNLOAD=3]="DOWNLOAD"})(Hn||(Hn={}));var Kt;(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"})(Kt||(Kt={}));function oc(e,t){return[t,e]}function pO(e,t){return e*t}function lc(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 fO(e,t){let[n,r]=ml(e,t);return n*r*4}function bA(e,t){let n=e,r,a,s,i,o,l,c,u,h,d;return Q().getNumber("WEBGL_VERSION")===2?(r=n.R32F,a=n.R16F,s=n.RGBA16F,i=n.RGBA32F,o=n.RED,c=4,u=1,h=n.HALF_FLOAT,d=n.FLOAT):(r=e.RGBA,a=e.RGBA,s=e.RGBA,i=n.RGBA,o=e.RGBA,c=4,u=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:c,defaultNumChannels:u,textureTypeHalfFloat:h,textureTypeFloat:d}}function _e(e,t){let n=t();return Q().getBool("DEBUG")&&mO(e),n}function mO(e){let t=e.getError();if(t!==e.NO_ERROR)throw new Error("WebGL Error: "+aw(e,t))}var AO=596e-10,yO=65504;function rw(e){return!!(Q().getBool("WEBGL_RENDER_FLOAT32_ENABLED")||e===0||AO<Math.abs(e)&&Math.abs(e)<yO)}function aw(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 rc(e,t){return aa(e,()=>e.getExtension(t),'Extension "'+t+'" not supported on this browser.')}function sw(e,t){let n=aa(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 iw(e,t){let n=aa(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 gO(t,e.getShaderInfoLog(n)),new Error("Failed to compile fragment shader.");return n}var xO=/ERROR: [0-9]+:([0-9]+):/g;function gO(e,t){let n=xO.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),c=i.slice(r-1,r),u=i.slice(r);console.log(l.join(`
`)),console.log(t.split(`
`)[0]),console.log(`%c ${v.rightPad(c[0],o)}`,"border:1px solid red; background-color:#e3d2d2; color:#a61717"),console.log(u.join(`
`))}function ow(e){return aa(e,()=>e.createProgram(),"Unable to create WebGLProgram.")}function lw(e,t){if(_e(e,()=>e.linkProgram(t)),e.getProgramParameter(t,e.LINK_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Failed to link vertex and fragment shaders.")}function Zd(e,t){if(_e(e,()=>e.validateProgram(t)),e.getProgramParameter(t,e.VALIDATE_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Shader program validation failed.")}function uw(e,t){let n=aa(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return _e(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),_e(e,()=>e.bufferData(e.ARRAY_BUFFER,t,e.STATIC_DRAW)),n}function cw(e,t){let n=aa(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return _e(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,n)),_e(e,()=>e.bufferData(e.ELEMENT_ARRAY_BUFFER,t,e.STATIC_DRAW)),n}function iO(){return Q().getNumber("WEBGL_VERSION")===2?1:4}function hw(e){return aa(e,()=>e.createTexture(),"Unable to create WebGLTexture.")}function dw(e,t){let n=Q().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(e<=0||t<=0){let r=`[${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 pw(e){return aa(e,()=>e.createFramebuffer(),"Unable to create WebGLFramebuffer.")}function gA(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 fw(e,t,n){Nw(e,n),_e(e,()=>e.activeTexture(e.TEXTURE0+n)),_e(e,()=>e.bindTexture(e.TEXTURE_2D,t))}function oO(e,t){Nw(e,t),_e(e,()=>e.activeTexture(e.TEXTURE0+t)),_e(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function mw(e,t,n){return aa(e,()=>e.getUniformLocation(t,n),'uniform "'+n+'" not present in program.')}function Aw(e,t,n){return e.getUniformLocation(t,n)}function yw(e,t,n,r){_e(e,()=>fw(e,t,r)),_e(e,()=>e.uniform1i(n,r))}function lO(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 Jd(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 xA(e,t){_e(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,t)),_e(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,null,0))}function ac(e){let t=e.checkFramebufferStatus(e.FRAMEBUFFER);if(t!==e.FRAMEBUFFER_COMPLETE)throw new Error("Error binding framebuffer: "+gw(e,t))}function gw(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 ${t}`}}function aa(e,t,n){let r=_e(e,()=>t());if(r==null)throw new Error(n);return r}function Nw(e,t){let n=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,r=t+e.TEXTURE0;if(r<e.TEXTURE0||r>n){let a=`[gl.TEXTURE0, gl.TEXTURE${n}]`;throw new Error(`textureUnit must be in ${a}.`)}}function ai(e,t=2){return v.sizeFromShape(e.slice(0,e.length-t))}function si(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 Yd(e){let t=[1,1,1];return e.length===0||e.length===1&&e[0]===1||(t=[ai(e),...si(e)]),t}function xw(e,t=!1){let n=Q().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=ai(e),s=2,i=2;return e.length&&([s,i]=si(e)),r=a*(s/2)*(i/2),v.sizeToSquarishShape(r).map(o=>o*2)}return v.sizeToSquarishShape(r)}function Qd(e){return e%2==0}function sc(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||Qd(n)&&Qd(r)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&Qd(e[0])&&Qd(t[0])}var ep,tp;function ww(e){if(ep==null){let t=Lr(e);ep=t.getParameter(t.MAX_TEXTURE_SIZE)}return ep}function uO(){ep=null}function cO(){tp=null}function _w(e){if(tp==null){let t=Lr(e);tp=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,tp)}function bw(e){if(e===0)return 0;let t,n=Lr(e);return Un(n,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:Un(n,"EXT_disjoint_timer_query")?t=1:t=0,t}function Un(e,t){return e.getExtension(t)!=null}function wA(e){try{if(Lr(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function vw(e){if(e===0)return!1;let t=Lr(e);if(e===1){if(!Un(t,"OES_texture_float"))return!1}else if(!Un(t,"EXT_color_buffer_float"))return!1;return vA(t)}function kw(e){if(e===0)return!1;let t=Lr(e);if(e===1){if(!Un(t,"OES_texture_float")||!Un(t,"WEBGL_color_buffer_float"))return!1}else{if(Un(t,"EXT_color_buffer_float"))return vA(t);let n="EXT_color_buffer_half_float";if(Un(t,n)){let r=t.getExtension(n);return wO(t,r)}return!1}return vA(t)}function vA(e){let t=bA(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 wO(e,t){let n=bA(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 Iw(e){return e!==2?!1:Lr(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 $e=Q();$e.registerFlag("HAS_WEBGL",()=>$e.getNumber("WEBGL_VERSION")>0);$e.registerFlag("WEBGL_VERSION",()=>wA(2)?2:wA(1)?1:0);$e.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);$e.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>$e.get("WEBGL_VERSION")===2);$e.registerFlag("WEBGL_CPU_FORWARD",()=>!0);$e.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);$e.registerFlag("WEBGL_PACK",()=>$e.getBool("HAS_WEBGL"));$e.registerFlag("WEBGL_PACK_NORMALIZATION",()=>$e.getBool("WEBGL_PACK"));$e.registerFlag("WEBGL_PACK_CLIP",()=>$e.getBool("WEBGL_PACK"));$e.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>!1);$e.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>$e.getBool("WEBGL_PACK"));$e.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>$e.getBool("WEBGL_PACK"));$e.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>$e.getBool("WEBGL_PACK"));$e.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>$e.getBool("WEBGL_PACK"));$e.registerFlag("WEBGL_PACK_REDUCE",()=>$e.getBool("WEBGL_PACK"));$e.registerFlag("WEBGL_LAZILY_UNPACK",()=>$e.getBool("WEBGL_PACK"));$e.registerFlag("WEBGL_CONV_IM2COL",()=>$e.getBool("WEBGL_PACK"));$e.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>ww($e.getNumber("WEBGL_VERSION")));$e.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>_w($e.getNumber("WEBGL_VERSION")));$e.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=$e.getNumber("WEBGL_VERSION");return e===0?0:bw(e)});$e.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>$e.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!jh.isMobile());$e.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>vw($e.getNumber("WEBGL_VERSION")));$e.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>$e.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:$e.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));$e.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>kw($e.getNumber("WEBGL_VERSION")));$e.registerFlag("WEBGL_FENCE_API_ENABLED",()=>Iw($e.getNumber("WEBGL_VERSION")));$e.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>$e.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);$e.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}.`)});function on(){let e,t,n,r,a,s,i,o,l,c;return Q().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="",c=`
#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));
}
`,c=`
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:c}}function oi(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 kA(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 Sw=`
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;
}
`,_O=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=ic.DENSE;let t=lc(e),n=on();this.outputShape=e,this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${oi(["r","c","d"],e)}
return ivec3(r, c, d);
}
void main() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${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;
}
`}},bO=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=ic.DENSE;let t=lc(e),n=on();this.outputShape=e,this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${oi(["r","c","d"],e)}
return ivec3(r, c, d);
}
void main() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${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;
}
`}},vO=class{constructor(e){this.variableNames=["A"],this.outTexUsage=Hn.DOWNLOAD;let t=on();this.outputShape=e,this.userCode=`
${Sw}
void main() {
float x = getAAtOutCoords();
${t.output} = encode_float(x);
}
`}},kO=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Hn.DOWNLOAD;let t=on();this.outputShape=e,this.userCode=`
${Sw}
void main() {
ivec3 coords = getOutputCoords();
float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
${t.output} = encode_float(x);
}
`}},IO=class{constructor(e,t,n=!1){this.variableNames=["A"];let r=on(),[a,s]=t;this.outputShape=e;let i="result";n&&(i="floor(result * 255. + 0.5)"),this.userCode=`
${kA(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.);
}
`}},NO=class{constructor(e,t,n=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let r=on(),[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 c=0;c<=1;c++){let u=l*2+c;i+=`
localCoords = coords;
if(localCoords[2] + ${c} < ${e[2]}) {
localCoords[2] += ${c};
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 = ${r.texture2D}(A, uv);
if(offset == 0) {
result[${u}] = values[0];
} else if(offset == 1) {
result[${u}] = values[1];
} else if(offset == 2) {
result[${u}] = values[2];
} else {
result[${u}] = values[3];
}
}
}
`}this.userCode=`
${kA(e)}
void main() {
ivec3 coords = getOutputCoords();
vec4 result = vec4(0.);
int flatIndex, r, c, offset;
ivec3 localCoords;
vec2 uv;
vec4 values;
${i}
${r.output} = ${o};
}
`}},v0={};ze(v0,{bindVertexProgramAttributeStreams:()=>Ow,createBufferFromOutputTexture:()=>Lw,createFloat16MatrixTexture:()=>Fw,createFloat16PackedMatrixTexture:()=>Dw,createFloat32MatrixTexture:()=>Rw,createIndexBuffer:()=>Cw,createPackedMatrixTexture:()=>$w,createUnsignedBytesMatrixTexture:()=>Mw,createVertexBuffer:()=>Ew,createVertexShader:()=>Tw,downloadByteEncodedFloatMatrixFromOutputTexture:()=>Bw,downloadFloat32MatrixFromBuffer:()=>Ww,downloadMatrixFromPackedOutputTexture:()=>Uw,downloadPackedMatrixFromBuffer:()=>Vw,getInternalFormatForFloat16MatrixTexture:()=>NA,getInternalFormatForFloat16PackedMatrixTexture:()=>EA,getInternalFormatForFloat32MatrixTexture:()=>IA,getInternalFormatForPackedMatrixTexture:()=>TA,getInternalFormatForUnsignedBytesMatrixTexture:()=>SA,uploadDenseMatrixToTexture:()=>zw,uploadPixelDataToTexture:()=>Pw});function Tw(e){let t=on(),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 sw(e,n)}function Ew(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 uw(e,t)}function Cw(e){let t=new Uint16Array([0,1,2,2,1,3]);return cw(e,t)}function uc(e,t,n,r,a,s){dw(t,n);let i=hw(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 IA(e){return e.internalFormatFloat}function Rw(e,t,n,r){let[a,s]=oc(t,n);return uc(e,a,s,IA(r),r.textureFormatFloat,e.FLOAT)}function NA(e){return e.internalFormatHalfFloat}function Fw(e,t,n,r){let[a,s]=oc(t,n);return uc(e,a,s,NA(r),r.textureFormatFloat,r.textureTypeHalfFloat)}function SA(e){return e.downloadTextureFormat}function Mw(e,t,n,r){let[a,s]=oc(t,n);return uc(e,a,s,SA(r),e.RGBA,e.UNSIGNED_BYTE)}function TA(e){return e.internalFormatPackedFloat}function $w(e,t,n,r){let[a,s]=ml(t,n);return uc(e,a,s,TA(r),e.RGBA,e.FLOAT)}function EA(e){return e.internalFormatPackedHalfFloat}function Dw(e,t,n,r){let[a,s]=ml(t,n);return uc(e,a,s,EA(r),e.RGBA,r.textureTypeHalfFloat)}function Ow(e,t,n){let r=0,a=3*4,s=3*4+2*4;return _e(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),gA(e,t,"clipSpacePos",n,3,s,r)&&gA(e,t,"uv",n,2,s,a)}function zw(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 Pw(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 Lw(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 Ww(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 Bw(e,t,n,r){let[a,s]=oc(t,n),i=4,o=new Uint8Array(pO(t*n,i));return _e(e,()=>e.readPixels(0,0,a,s,r.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function Vw(e,t,n,r,a,s,i,o){let l=e,c=new Float32Array(fO(s,i));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,c),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),c}function Uw(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 fm=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=Q().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,pm(t,e)):this.gl=Lr(t);let n="WEBGL_color_buffer_float",r="EXT_color_buffer_half_float";if(Q().getNumber("WEBGL_VERSION")===1){let a="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=rc(this.gl,a),Un(this.gl,s))this.textureHalfFloatExtension=rc(this.gl,s);else if(Q().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(n),Un(this.gl,r))this.colorBufferHalfFloatExtension=rc(this.gl,r);else if(Q().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(n="EXT_color_buffer_float",Un(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(Un(this.gl,r))this.colorBufferHalfFloatExtension=this.gl.getExtension(r);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=Ew(this.gl),this.indexBuffer=Cw(this.gl),this.framebuffer=pw(this.gl),this.textureConfig=bA(this.gl,this.textureHalfFloatExtension)}get debug(){return Q().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),this.outputTexture!=null&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture. This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");let e=this.gl;_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(),Rw(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),Fw(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),Mw(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),Pw(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,r){this.throwIfDisposed(),zw(this.gl,e,t,n,r,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),Dw(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),$w(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(xA(this.gl,this.framebuffer),this.outputTexture=null),_e(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>Bw(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,r,a,s){return Vw(this.gl,e,t,n,r,a,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return Ww(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let r=Lw(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(Q().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 Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>Uw(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl,n=iw(t,e),r=Tw(t),a=ow(t);return _e(t,()=>t.attachShader(a,r)),_e(t,()=>t.attachShader(a,n)),lw(t,a),this.debug&&Zd(t,a),this.vertexAttrsAreBound||(this.setProgram(a),this.vertexAttrsAreBound=Ow(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&&Zd(this.gl,this.program),_e(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?mw(this.gl,e,t):Aw(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(),yw(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&&Zd(this.gl,this.program),ac(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=rc(this.gl,Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension}getQueryTimerExtensionWebGL2(){return this.getQueryTimerExtension()}getQueryTimerExtensionWebGL1(){return this.getQueryTimerExtension()}beginQuery(){if(Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,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(Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,n=this.getQueryTimerExtensionWebGL2();t.endQuery(n.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await v.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let n=this.gl;return n.getQueryParameter(e,n.QUERY_RESULT)/1e6}else{let n=this.getQueryTimerExtensionWebGL1();return n.getQueryObjectEXT(e,n.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let n=this.gl,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=SO(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(),Jd(this.gl,e,this.framebuffer),this.debug&&ac(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(Jd(this.gl,this.outputTexture,this.framebuffer),this.debug&&ac(this.gl)):xA(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;Jd(r,e,this.framebuffer),this.debug&&ac(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 SO(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{getBroadcastDims:Hw}=C;function OO(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=>TO(p,t,r)).join(`
`),o=t.texShape,l=on(),c=RO(l),u,h,d=$O(l);return t.isPacked?(u=EO(t.logicalShape,o),h=MO(l)):(u=CO(t.logicalShape,o),h=FO(l)),r&&(d+=DO),[d,c,h,s,u,i,n].join(`
`)}function Al(e){let t=e.shapeInfo.logicalShape;switch(t.length){case 0:return zO(e);case 1:return PO(e);case 2:return LO(e);case 3:return WO(e);case 4:return BO(e);case 5:return VO(e);case 6:return UO(e);default:throw new Error(`${t.length}-D input sampling is not yet supported`)}}function jw(e){switch(e.shapeInfo.logicalShape.length){case 0:return HO(e);case 1:return jO(e);case 2:return GO(e);case 3:return qO(e);default:return XO(e)}}function TO(e,t,n=!1){let r="";n?r+=jw(e):r+=Al(e);let a=e.shapeInfo.logicalShape,s=t.logicalShape;return a.length<=s.length&&(n?r+=KO(e,t):r+=ZO(e,t)),r}function EO(e,t){switch(e.length){case 0:return Gw();case 1:return JO(e,t);case 2:return ez(e,t);case 3:return YO(e,t);default:return QO(e,t)}}function CO(e,t){switch(e.length){case 0:return Gw();case 1:return tz(e,t);case 2:return iz(e,t);case 3:return nz(e,t);case 4:return rz(e,t);case 5:return az(e,t);case 6:return sz(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function RO(e){return`
float sampleTexture(sampler2D textureSampler, vec2 uv) {
return ${e.texture2D}(textureSampler, uv).r;
}
`}function FO(e){return`
void setOutput(float val) {
${e.output} = vec4(val, 0, 0, 0);
}
`}function MO(e){return`
void setOutput(vec4 val) {
${e.output} = val;
}
`}function $O(e){return`${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);
}
${oz}
${lz}
${uz}
`}var oz=`
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);
}
`,lz=`
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);
}
`,uz=`
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);
}
`,DO=`
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 Gw(){return`
int getOutputCoords() {
return 0;
}
`}function JO(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 tz(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 * ${t[1]} + resTexRC.y;
}
`}function YO(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),a=r*Math.ceil(e[1]/2);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${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, ${r}) * 2;
return ivec3(b, r, c);
}
`}function nz(e,t){let n=oi(["r","c","d"],e);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
return ivec3(r, c, d);
}
`}function QO(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),a=r*Math.ceil(e[e.length-2]/2),s=a,i="",o="b, r, c";for(let l=2;l<e.length-1;l++)s*=e[e.length-l-1],i=`
int b${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}(${o});
}
`}function rz(e,t){let n=oi(["r","c","d","d2"],e);return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
return ivec4(r, c, d, d2);
}
`}function az(e,t){let n=oi(["r","c","d","d2","d3"],e);return`
ivec5 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
ivec5 outShape = ivec5(r, c, d, d2, d3);
return outShape;
}
`}function sz(e,t){let n=oi(["r","c","d","d2","d3","d4"],e);return`
ivec6 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
ivec6 result = ivec6(r, c, d, d2, d3, d4);
return result;
}
`}function ez(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return`
ivec2 getOutputCoords() {
return 2 * ivec2(resultUV.yx * vec2(${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, ${r}) * 2;
return ivec2(r, c);
}
`}function iz(e,t){return v.arraysEqual(e,t)?`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(${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 * ${e[1]};
return ivec2(r, c);
}
`}function li(e){return`offset${e}`}function HO(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=on();return`
vec4 ${n}() {
return ${r.texture2D}(${t}, halfCR);
}
`}function zO(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=li(t);return`
float ${n}() {
vec2 uv = uvFromFlat(${s}, ${i}, ${o});
return sampleTexture(${t}, uv);
}
`}function jO(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=on();return`
vec4 ${n}(int index) {
vec2 uv = packedUVfrom1D(
${a[0]}, ${a[1]}, index);
return ${s.texture2D}(${t}, uv);
}
`}function PO(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`
float ${n}(int index) {
${yl(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=li(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 GO(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=on();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)],c=Math.ceil(t[1]/2);return`
vec4 ${r}(int row, int col) {
vec2 uv = packedUVfrom2D(${c}, ${l[0]}, ${l[1]}, row, col);
return ${o.texture2D}(${n}, uv);
}
`}function LO(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=gl(e,o),d=["row","col"];return`
${Al(h)}
float ${r}(int row, int col) {
return ${r}(${xl(d,i)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col) {
int index = round(dot(vec2(row, col), vec2(${t[1]}, 1)));
${yl(e)}
}
`;let l=a[0],c=a[1],u=li(n);return c===1?`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${u}), vec3(${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, ${u}), vec3(${t[1]}, 1, 1));
vec2 uv = vec2((index + 0.5) / ${c}.0, 0.5);
return sampleTexture(${n}, uv);
}
`:`
float ${r}(int row, int col) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${t[1]} + col + ${u};
vec2 uv = uvFromFlat(${l}, ${c}, index);
return sampleTexture(${n}, uv);
}
`}function qO(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=gl(e,h),f=["b","row","col"];return`
${jw(p)}
vec4 ${r}(int b, int row, int col) {
return ${r}(${xl(f,d)});
}
`}let i=s[0],o=s[1],l=Math.ceil(t[2]/2),c=l*Math.ceil(t[1]/2),u=on();return`
vec4 ${r}(int b, int row, int col) {
vec2 uv = packedUVfrom3D(
${i}, ${o}, ${c}, ${l}, b, row, col);
return ${u.texture2D}(${n}, uv);
}
`}function WO(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=gl(e,l),m=["row","col","depth"];return`
${Al(f)}
float ${r}(int row, int col, int depth) {
return ${r}(${xl(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)));
${yl(e)}
}
`;let c=e.shapeInfo.texShape,u=c[0],h=c[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, ${u}.0);
return sampleTexture(${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, ${u}.0);
return sampleTexture(${n}, uv);
}
`;let p=li(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 + ${p};
vec2 uv = uvFromFlat(${u}, ${h}, index);
return sampleTexture(${n}, uv);
}
`}function XO(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],c=Math.ceil(t[n-1]/2),u=c*Math.ceil(t[n-2]/2),h="int b, int row, int col",d=`b * ${u} + (row / 2) * ${c} + (col / 2)`;for(let f=2;f<n-1;f++)h=`int b${f}, `+h,u*=t[n-f-1],d=`b${f} * ${u} + `+d;let p=on();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 BO(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=gl(e,o),m=["row","col","depth","depth2"];return`
${Al(f)}
float ${r}(int row, int col, int depth, int depth2) {
return ${r}(${xl(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)));
${yl(e)}
}
`;let c=e.shapeInfo.flatOffset,u=e.shapeInfo.texShape,h=u[0],d=u[1];if(d===i&&c==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&&c==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=li(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 VO(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:c}=v.squeezeShape(t);if(l.length<t.length){let m=gl(e,l),A=["row","col","depth","depth2","depth3"];return`
${Al(m)}
float ${r}(int row, int col, int depth, int depth2, int depth3) {
return ${r}(${xl(A,c)});
}
`}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;
${yl(e)}
}
`;let u=e.shapeInfo.flatOffset,h=e.shapeInfo.texShape,d=h[0],p=h[1];if(p===o&&u==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&&u==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=li(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 UO(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=gl(e,a),y=["row","col","depth","depth2","depth3","depth4"];return`
${Al(A)}
float ${r}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
return ${r}(${xl(y,s)});
}
`}let i=t[5],o=t[4]*i,l=t[3]*o,c=t[2]*l,u=t[1]*c;if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int index = round(dot(
vec4(row, col, depth, depth2),
vec4(${u}, ${c}, ${l}, ${o})) +
dot(
vec2(depth3, depth4),
vec2(${i}, 1)));
${yl(e)}
}
`;let h=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,p=d[0],f=d[1];if(f===u&&h==null)return`
float ${r}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int texR = row;
float texC = dot(vec4(col, depth, depth2, depth3),
vec4(${c}, ${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=li(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 * ${u} + col * ${c} + depth * ${l} +
depth2 * ${o} + depth3 * ${i} + depth4 + ${m};
vec2 uv = uvFromFlat(${p}, ${f}, index);
return sampleTexture(${n}, uv);
}
`}function yl(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 ${t}[i];
}
}
`}function KO(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=Hw(e.shapeInfo.logicalShape,t.logicalShape),l=ht(i),c=i-s,u,h=["x","y","z","w","u","v"];s===0?u="":i<2&&o.length>=1?u="coords = 0;":u=o.map(A=>`coords.${h[A+c]} = 0;`).join(`
`);let d="";i<2&&s>0?d="coords":d=e.shapeInfo.logicalShape.map((A,y)=>`coords.${h[y+c]}`).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();
${u}
vec4 outputValue = get${r}(${d});
${p}
}
`}function ZO(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 c=ht(l),u=Hw(e.shapeInfo.logicalShape,t.logicalShape),h=l-o,d,p=["x","y","z","w","u","v"];o===0?d="":l<2&&u.length>=1?d="coords = 0;":d=u.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}() {
${c} coords = getOutputCoords();
${d}
return get${r}(${f});
}
`}function ht(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function gl(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function xl(e,t){return t.map(n=>e[n]).join(", ")}function cz(e,t,n,r){let a=t.userCode,s=n.map((p,f)=>{let m={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(m.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[f],shapeInfo:m}}),i=s.map(p=>p.shapeInfo),o={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},l=OO(s,o,a,t.packedInputs),c=e.createProgram(l),u=null,h=e.getUniformLocation(c,"NAN",!1);Q().getNumber("WEBGL_VERSION")===1&&(u=e.getUniformLocation(c,"INFINITY",!1));let d={};for(let p=0;p<t.variableNames.length;p++){let f=t.variableNames[p],m=!1;d[f]=e.getUniformLocation(c,f,m),d[`offset${f}`]=e.getUniformLocation(c,`offset${f}`,m)}return{program:t,source:l,webGLProgram:c,uniformLocations:d,inShapeInfos:i,outShapeInfo:o,infLoc:u,nanLoc:h}}function qw(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 ${l} must match`)})}function hz(e,t,n,r,a){qw(t.inShapeInfos,n),qw([t.outShapeInfo],[r]);let s=r.texData.texture,i=r.texData.texShape;r.texData.isPacked?e.setOutputPackedMatrixTexture(s,i[0],i[1]):e.setOutputMatrixTexture(s,i[0],i[1]),e.setProgram(t.webGLProgram),Q().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,Infinity),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((o,l)=>{let c=t.program.variableNames[l],u=t.uniformLocations[c],h=t.uniformLocations[`offset${c}`];if(u!=null){if(o.isUniform){if(v.sizeFromShape(o.shape)<2)e.gl.uniform1f(u,o.uniformValues[0]);else{let d=o.uniformValues;d instanceof Float32Array||(d=new Float32Array(d)),e.gl.uniform1fv(u,d)}return}o.texData.slice!=null&&h!=null&&e.gl.uniform1i(h,o.texData.slice.flatOffset),e.setInputMatrixTexture(o.texData.texture,u,l)}}),a!=null&&a(e,t.webGLProgram),e.executeProgram()}function dz(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}_${o}`});let a=e.userCode,s=e.constructor.name;return s+="_"+r+"_"+a,s}var{addImpl:pz,bincountImpl:Xw,bincountReduceImpl:fz,ceilImpl:mz,concatImpl:Az,expImpl:yz,expm1Impl:gz,floorImpl:xz,gatherV2Impl:wz,greaterImpl:_z,lessImpl:bz,linSpaceImpl:vz,logImpl:kz,maxImpl:Iz,maximumImpl:Nz,minimumImpl:Sz,multiplyImpl:Tz,negImpl:Ez,prodImpl:Cz,rangeImpl:Rz,rsqrtImpl:Fz,simpleAbsImpl:Kw,sliceImpl:Mz,stridedSliceImpl:$z,subImpl:Dz,tileImpl:Oz,topKImpl:zz,transposeImpl:CA,uniqueImpl:Pz}=dm;function Zw(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function ln(e,t){return t===1?[e]:Zw(e,t)}function Lz(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 Uz=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=ln("rc",t),r=ht(t),a=Wz(t,e,n),s=Bz(t,e[e.length-1],e[e.length-2],n),i=Vz(e,n);this.userCode=`
void main() {
${r} rc = getOutputCoords();
if(${a}) {
setOutput(vec4(0));
} else {
${s}
setOutput(vec4(${i}));
}
}
`}}};function Hz(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 Wz(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 Bz(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 Vz(e,t){let n=e.length,r=Hz(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 Jw=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=`
${jz(t)}
${kA(e)}
void main() {
ivec3 rc = getOutputCoords();
vec4 result = vec4(0.);
ivec3 thisRC;
int rows = ${e[1]};
int cols = ${e[2]};
${n}
setOutput(result);
}
`}};function jz(e){return`
ivec3 inputCoordsFromReshapedOutCoords(int index) {
${oi(["r","c","d"],e)}
return ivec3(r, c, d);
}
`}var Gz=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let r=Qw(t,n),a=e_(e,r,n);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);let s=Yw(e,r,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[a].shift();return this.usedTextures[a].push(o),o}let i;return r===Kt.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):r===Kt.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):r===Kt.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):r===Kt.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):r===Kt.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,r){if(this.freeTextures==null)return;let a=Qw(n,r),s=e_(t,a,r);s in this.freeTextures||(this.freeTextures[s]=[]);let i=Yw(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,r),o=Q().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],c=l.indexOf(e);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${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 qz(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 Yw(e,t,n,r,a){let s=Xz(t,r),i;if(a){let[l,c]=ml(e[0],e[1]);i=l*c}else{let[l,c]=oc(e[0],e[1]);i=l*c}let o=qz(n,s);return i*o}function Xz(e,t){switch(e){case Kt.PACKED_2X2_FLOAT32:return TA(t);case Kt.PACKED_2X2_FLOAT16:return EA(t);case Kt.UNPACKED_FLOAT32:return IA(t);case Kt.UNPACKED_FLOAT16:return NA(t);case Kt.PACKED_4X1_UNSIGNED_BYTE:return SA(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function Kz(e){return Q().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?Kt.PACKED_2X2_FLOAT32:Kt.UNPACKED_FLOAT32:e?Kt.PACKED_2X2_FLOAT16:Kt.UNPACKED_FLOAT16}function Qw(e,t){if(e===Hn.UPLOAD)return Kt.PACKED_2X2_FLOAT32;if(e===Hn.RENDER||e==null)return Kz(t);if(e===Hn.DOWNLOAD||e===Hn.PIXELS)return Kt.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function e_(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var Ra=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);
}
`}},Ar="if (isnan(x)) return x;",Zz="return x;",t_="return abs(x);",Jz="return (x >= 0.0) ? x : (exp(x) - 1.0);",Yz=Ar+`
return (x < 0.0) ? 0.0 : x;
`,Qz=Ar+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,np="return x;",eP="return x;",tP=`
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;
`,nP=`
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;
`,rP=`
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;
`,wl=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
vec4 unaryOperation(vec4 x) {
${t}
}
void main() {
vec4 x = getAAtOutCoords();
vec4 y = unaryOperation(x);
setOutput(y);
}
`}},aP=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,n=ln("rc",t),r=ht(t),a=Lz(t,n),s=n.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
void main() {
${r} rc = getOutputCoords();
vec4 packedInput = getA(${a});
setOutput(getChannel(packedInput, ${i}));
}
`}},sP=Rr.whereImpl,iP=1e-7,oP=1e-4,RA={};function lP(e){return e in RA||(RA[e]={}),RA[e]}var uP=128,cP=600;function hP(){return Q().global.screen==null?1024:Q().global.screen.height*Q().global.screen.width*window.devicePixelRatio*cP/1024/1024}var mm=class extends au{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.warnedAboutMemory=!1,this.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!Q().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Lr(Q().getNumber("WEBGL_VERSION"));this.binaryCache=lP(Q().getNumber("WEBGL_VERSION")),this.gpgpu=new fm(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 Gz(this.gpgpu),this.numMBBeforeWarning=hP(),this.texData=new hh(this,Ln())}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,n){if((Q().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||Q().getBool("DEBUG"))&&this.checkNumericalProblems(e),n==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let r={};return this.texData.set(r,{shape:t,dtype:n,values:e,usage:Hn.UPLOAD,refCount:1,complexParentRefCount:0}),r}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--}}decComplexRef(e){if(this.texData.has(e)){let t=this.texData.get(e);t.complexParentRefCount>0&&t.refCount--}}move(e,t,n,r){if(Q().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:Hn.UPLOAD,refCount:1,complexParentRefCount:0})}disposeIntermediateTensorInfo(e){let t=e.dataId;if(this.texData.has(t)){let n=this.texData.get(t);n.refCount--,n.refCount<1&&this.disposeData(t)}}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 wl(i,np):h=new Ra(i,np);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,c;l&&(c=v.now());let u;if(r==="complex64"){let h=this.readSync(a.real.dataId),d=this.readSync(a.imag.dataId);u=C.mergeRealAndImagArrays(h,d)}else u=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-c),this.convertAndCacheOnCPU(e,u)}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 wl(r,np):p=new Ra(r,np);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(!Q().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&Q().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,c;if(s!=="complex64"&&Q().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(e);let p=this.texData.get(c.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...lc(r))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let u;if(s==="complex64"){let p=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),f=p[0],m=p[1];u=C.mergeRealAndImagArrays(f,m)}else if(l==null)u=this.getValuesFromTexture(e);else{let p=v.sizeFromShape(r);u=this.gpgpu.downloadFloat32MatrixFromBuffer(l,p)}c!=null&&this.disposeIntermediateTensorInfo(c);let h=this.convertAndCacheOnCPU(e,u),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),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 We(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!rw(n))throw Q().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:r}=this.texData.get(e),a=v.sizeFromShape(t);if(Q().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let h=this.decode(e),d=this.texData.get(h.dataId),p=this.gpgpu.downloadMatrixFromPackedTexture(d.texture,...lc(t)).subarray(0,a);return this.disposeIntermediateTensorInfo(h),p}let s=Q().getBool("WEBGL_PACK")&&r===!0,i=s?Yd(t):t,o=s?new kO(i):new vO(i),l=this.runWebGLProgram(o,[{shape:i,dtype:n,dataId:e}],"float32"),c=this.texData.get(l.dataId),u=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture,c.texShape[0],c.texShape[1]).subarray(0,a);return this.disposeIntermediateTensorInfo(l),u}async time(e){let t=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,e();let a=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,r&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(a);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,c)=>({name:s[c],ms:l})).map(l=>`${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 Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e){if(this.pendingDisposal.has(e))return;if(this.pendingRead.has(e)){this.pendingDisposal.add(e),this.pendingDeletes++;return}if(!this.texData.has(e))return;if(this.texData.get(e).complexParentRefCount>0){this.texData.get(e).refCount--;return}this.releaseGPUData(e);let{complexTensorInfos:t}=this.texData.get(e);t!=null&&(this.texData.get(t.real.dataId).complexParentRefCount--,this.disposeIntermediateTensorInfo(t.real),this.texData.get(t.imag.dataId).complexParentRefCount--,this.disposeIntermediateTensorInfo(t.imag)),this.texData.delete(e)}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 c=this.texData.get(e);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}getCPUBackend(){return Q().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=Ln().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=uP){let n=this.getCPUBackend();return!Q().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){C.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return sP(e.shape,t)}packedUnaryOp(e,t,n){let r=new wl(e.shape,t);return this.compileAndRun(r,[e],n)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let n=Kw(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,n)}if(Q().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,t_,e.dtype);let t=new Ra(e.shape,t_);return this.compileAndRun(t,[e])}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 Ln().makeTensorFromDataId(r,e,t,this)}unpackTensor(e){let t=new aP(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new Uz(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[ai(e.shape),...si(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},a=[ai(t),...si(t)],s=new Jw(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=Yd(r),i;n?i=new bO(s):i=new _O(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===ic.DENSE){let f=lc(e.outputShape);i.texShape=f.map(m=>m*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(f=>{if(f.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let m=this.texData.get(f.dataId);if(m.texture==null){if(!e.packedInputs&&v.sizeFromShape(f.shape)<=Q().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:f.shape,texData:null,isUniform:!0,uniformValues:m.values};e.packedInputs&&(m.isPacked=!0,m.shape=f.shape)}else if(!!m.isPacked!=!!e.packedInputs)f=m.isPacked?this.unpackTensor(f):this.packTensor(f),o.push(f),m=this.texData.get(f.dataId);else if(m.isPacked&&!sc(m.shape,f.shape)){let A=f,y=f.shape;f.shape=m.shape,f=this.packedReshape(f,y),o.push(f),m=this.texData.get(f.dataId),A.shape=y}return this.uploadToGPU(f.dataId),{shape:f.shape,texData:m,isUniform:!1}});this.uploadToGPU(s.dataId);let c={shape:s.shape,texData:i,isUniform:!1},u=dz(e,l,c),h=this.getAndSaveBinary(u,()=>cz(this.gpgpu,e,l,c)),d=this.activeTimers!=null,p;if(d&&(p=this.startTimer()),hz(this.gpgpu,h,l,c,r),o.forEach(f=>this.disposeIntermediateTensorInfo(f)),d&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)})),!Q().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&a===!1){let f=this.unpackTensor(s);return this.disposeIntermediateTensorInfo(s),f}return s}compileAndRun(e,t,n,r,a=!1){n=n||t[0].dtype;let s=this.runWebGLProgram(e,t,n,r,a);return Ln().makeTensorFromDataId(s.dataId,s.shape,s.dtype)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(Q().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(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=U(()=>{if(!Q().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=Q().getBool("DEBUG");Q().set("DEBUG",!1);let t=this.abs(Se(1e-8)).dataSync()[0];if(Q().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?iP:oP}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,c;l&&(c=v.now());let u=t.texShape;if(u==null&&(u=xw(n,o),t.texShape=u),a!=null){let h=Yd(n),d,p=u[1],f=u[0],m=a instanceof Uint8Array;o?([p,f]=ml(u[0],u[1]),d=new NO(h,[f,p],m)):d=new IO(h,[f,p],m);let A=this.makeTensorInfo([f,p],r);m?this.texData.get(A.dataId).usage=Hn.PIXELS:this.texData.get(A.dataId).usage=Hn.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(A.dataId),p,f,a);let y=!0,g=this.runWebGLProgram(d,[A],r,null,y),w=this.texData.get(g.dataId);t.texture=w.texture,t.texShape=w.texShape,t.isPacked=w.isPacked,t.usage=w.usage,this.disposeIntermediateTensorInfo(A),this.texData.delete(g.dataId),t.values=null,l&&(this.uploadWaitMs+=v.now()-c)}else{let h=this.acquireTexture(u,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=dP(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)}};function dP(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 k0="3.0.0";function I0(){Q().set("WEBGL_FORCE_F16_TEXTURES",!0)}jh.isBrowser()&&Iu("webgl",()=>new mm,2);var m8={forceHalfFloat:I0},n_=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`,_l=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=C.assertAndGetBroadcastShape(t,n),this.userCode=`
float binaryOperation(float a, float b) {
${e}
}
void main() {
float a = getAAtOutCoords();
float b = getBAtOutCoords();
setOutput(binaryOperation(a, b));
}
`}},rp=`
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;
`,cc=class{constructor(e,t,n,r=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=C.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=`
${ht(a)} coords = getOutputCoords();
`,a===1)s+=`
result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`;else{let i=ln("coords",a);s+=`
bool nextRowOutOfBounds =
(${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 En(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 pP={kernelName:so,backendName:"webgl",kernelFunc:En};function Fa(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=En({inputs:{x:r},backend:n}),l=n.texData.get(o.dataId);l.complexParentRefCount++;let c=En({inputs:{x:a},backend:n}),u=n.texData.get(c.dataId);return u.complexParentRefCount++,i.complexTensorInfos={real:o,imag:c},s}var fP={kernelName:yh,backendName:"webgl",kernelFunc:Fa},r_="return (a < 0.) ? b * a : a;",a_=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function mP(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{alpha:s}=r,i=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new cc(a_,a.shape,i.shape):new _l(r_,a.shape,i.shape),l=n.runWebGLProgram(o,[a,i],a.dtype);return n.disposeIntermediateTensorInfo(i),l}var AP={kernelName:hs,backendName:"webgl",kernelFunc:mP},s_="return (a < 0.) ? b * a : a;",i_=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function yP(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t,s=Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new cc(i_,r.shape,a.shape):new _l(s_,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)}var gP={kernelName:vs,backendName:"webgl",kernelFunc:yP},o_="if (isnan(x)) return x;",xP=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`,wP=`
result.r = isNaN.r > 0. ? NAN : result.r;
result.g = isNaN.g > 0. ? NAN : result.g;
result.b = isNaN.b > 0. ? NAN : result.b;
result.a = isNaN.a > 0. ? NAN : result.a;
`;function Je({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype: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 c=Q().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,u;return c?u=new wl(i.shape,t):u=new Ra(i.shape,e),o.runWebGLProgram(u,[i],l)}}function Zt({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:r=!1,cpuKernelImpl:a,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:c}=i,u=o;if(r&&l.dtype==="complex64"){let f=u.texData.get(l.dataId),m=u.texData.get(c.dataId),[A,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(w=>{let[x,_]=w,I={dataId:x.dataId,dtype:x.dtype,shape:l.shape},T={dataId:_.dataId,dtype:_.dtype,shape:c.shape},E=new _l(e,l.shape,c.shape);return u.runWebGLProgram(E,[I,T],Qn(x.dtype,_.dtype))}),g=Fa({inputs:{real:A,imag:y},backend:u});return u.disposeIntermediateTensorInfo(A),u.disposeIntermediateTensorInfo(y),g}let h=s||Qn(l.dtype,c.dtype);if(u.shouldExecuteOnCPU([l,c])&&a!=null){let f=u.texData.get(l.dataId),m=u.texData.get(c.dataId),[A,y]=a(l.shape,c.shape,f.values,m.values,h),g=u.makeTensorInfo(y,h),w=u.texData.get(g.dataId);return w.values=A,g}let d=Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return d?p=new cc(t,l.shape,c.shape,n):p=new _l(e,l.shape,c.shape),u.runWebGLProgram(p,[l,c],h)}}function ap(e,t=!1){if(e==="linear")return t?eP:Zz;if(e==="relu")return t?nP:Yz;if(e==="elu")return t?tP:Jz;if(e==="relu6")return t?rP:Qz;if(e==="prelu")return t?i_:s_;if(e==="leakyrelu")return t?a_:r_;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var l_=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 c=r?e[1]:e[2],u=Math.ceil(c/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",w="rc.x";e[0]<t[0]?g=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(w=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
${m}
const float sharedDimension = ${u}.0;
vec4 dot2x2ARowBCol(ivec3 rc) {
vec4 result = vec4(0);
for (int i = 0; i < ${u}; i++) {
int batchA = ${g};
int batchB = ${w};
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);
}
`}},u_={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},c_=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=C.assertAndGetBroadcastShape(t,n),this.userCode=`
float binaryOpComplex(
float areal, float aimag, float breal, float bimag) {
${e}
}
void main() {
float areal = getARealAtOutCoords();
float aimag = getAImagAtOutCoords();
float breal = getBRealAtOutCoords();
float bimag = getBImagAtOutCoords();
setOutput(binaryOpComplex(areal, aimag, breal, bimag));
}
`}},h_="return a * b;";function d_(e){let{inputs:t,backend:n}=e,{a:r,b:a}=t,s=C.upcastType(r.dtype,a.dtype);if(r.dtype==="complex64"){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),c=new c_(u_.REAL,r.shape,a.shape),u=new c_(u_.IMAG,r.shape,a.shape),h=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:r.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:r.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:a.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:a.shape}],d=n.runWebGLProgram(c,h,"float32"),p=n.runWebGLProgram(u,h,"float32"),f=Fa({inputs:{real:d,imag:p},backend:n});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}if(n.shouldExecuteOnCPU([r,a])){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),[c,u]=Tz(r.shape,a.shape,o.values,l.values,s),h=n.makeTensorInfo(u,s),d=n.texData.get(h.dataId);return d.values=c,h}let i;return Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new cc(h_,r.shape,a.shape):i=new _l(h_,r.shape,a.shape),n.runWebGLProgram(i,[r,a],s)}var _P={kernelName:xs,backendName:"webgl",kernelFunc:d_};function bP(e,t,n){let r=[ai(e.shape),...si(e.shape)],a={dtype:e.dtype,shape:r,dataId:e.dataId},s=[ai(t),...si(t)],i=new Jw(s,r),o=!0,l=n.runWebGLProgram(i,[a],e.dtype,null,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function ge(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{shape:s}=r,i=n,o=v.sizeFromShape(a.shape),l=v.inferFromImplicitShape(s,o),c=v.sizeFromShape(l);v.assert(o===c,()=>`The new shape (${l}) has ${c} elements and the old shape (${a.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let u=i.texData.get(a.dataId);return u.isPacked&&!sc(a.shape,l)&&!(u.texture!==null&&sc(u.shape,l))?bP(a,l,i):(i.incRef(a.dataId),{dataId:a.dataId,shape:l,dtype:a.dtype})}var vP={kernelName:ko,backendName:"webgl",kernelFunc:ge},p_=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 u=1/t;l=`sumValue += dot(values * ${v.isInt(u)?u.toPrecision(2):u}, ones);`}let c="";a%n>0&&(c=`
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) {
${c}
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);
${l}
}
setOutput(sumValue);
}
`}},kP=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${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 c=Math.floor(n/4)*4,u=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 < ${c}; 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 + ${c};
if (${u===1}) {
${d} values = ${d}(
getValue(batch, inIdx),
initializationValue,
initializationValue,
initializationValue
);
${h}
} else if (${u===2}) {
${d} values = ${d}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
initializationValue,
initializationValue
);
${h}
} else if (${u===3}) {
${d} values = ${d}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
initializationValue
);
${h}
}
setOutput(${l});
}
`}};function IP(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=C.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}function ui(e,t,n,r){let a=IP(e.shape),s=e;for(let i=0;i<a.length;i++){let{inSize:o,windowSize:l,outSize:c}=a[i],u,h;n==="mean"?u=i===0?new p_({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c},o):new p_({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c}):u=new kP({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c},n),h=s,s=r.runWebGLProgram(u,[s],t),h.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(h)}return s}var SP=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=ht(this.rank),a=NP(t);this.userCode=`
void main() {
${r} resRC = getOutputCoords();
setOutput(getA(${a}));
}
`}};function NP(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 TP=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(e.length);for(let c=0;c<n.length;c++)n[c]=e[t[c]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let r=ht(this.rank),a=Zw("rc",this.rank),s=new Array(this.rank);for(let c=0;c<t.length;c++)s[t[c]]=a[c];let i=`vec2(${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] = ${l};
}
}
setOutput(result);
}
`}};function sp(e,t,n){let r=Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new TP(e.shape,t):new SP(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function EP(e,t,n,r){let a=t,s=e.shape.length,i=v.parseAxisParam(a,e.shape),o=i,l=C.getAxesPermutation(o,s),c=l!=null,u=e;c&&(u=sp(e,l,r),o=C.getInnerMostAxes(o.length,s)),C.assertAxesAreInnerMostDims("sum",o,s);let[h,d]=C.computeOutAndReduceShapes(u.shape,o),p=h;n&&(p=C.expandShapeToKeepDim(h,i));let f=v.sizeFromShape(d),m=v.sizeFromShape(e.shape)/f,A=ge({inputs:{x:u},attrs:{shape:[m,f]},backend:r}),y=Hh(e.dtype),g=ui(A,y,"sum",r),w=ge({inputs:{x:g},attrs:{shape:p},backend:r});return r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(g),c&&r.disposeIntermediateTensorInfo(u),w}function FA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;return EP(a,s,i,n)}var CP={kernelName:Ms,backendName:"webgl",kernelFunc:FA};function mn(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{perm:s}=r,i=n,o=a.shape.length,l=new Array(o);for(let u=0;u<l.length;u++)l[u]=a.shape[s[u]];let c;if(i.shouldExecuteOnCPU([a])){let u=i.texData.get(a.dataId).values,h=CA(u,a.shape,a.dtype,s,l);c=i.makeTensorInfo(l,a.dtype);let d=i.texData.get(c.dataId);d.values=h}else c=sp(a,s,i);return c}var RP={kernelName:Ps,backendName:"webgl",kernelFunc:mn},f_=1e3;function ip({a:e,b:t,transposeA:n,transposeB:r,backend:a,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let c=e.shape.length,u=t.shape.length,h=n?e.shape[c-2]:e.shape[c-1],d=r?t.shape[u-1]:t.shape[u-2],p=n?e.shape[c-1]:e.shape[c-2],f=r?t.shape[u-2]:t.shape[u-1],m=e.shape.slice(0,-2),A=t.shape.slice(0,-2),y=v.sizeFromShape(m),g=v.sizeFromShape(A),w=y===g||y===1||g===1;v.assert(c>=2&&u>=2&&w,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${m}) and (${A}).`);let x=(y>g?e.shape.slice(0,-2):t.shape.slice(0,-2)).concat([p,f]);v.assert(h===d,()=>`Error in matMul: inner shapes (${h}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${r} must match.`);let _=n?[y,h,p]:[y,p,h],I=r?[g,f,d]:[g,d,f],T=ge({inputs:{x:e},backend:a,attrs:{shape:_}}),E=ge({inputs:{x:t},backend:a,attrs:{shape:I}}),N=[T,E],F=Math.max(y,g),$=n?T.shape[1]:T.shape[2],D=s!=null,P=i!=null,H=l==="leakyrelu",V=l!=null?ap(l,!0):null,K=D||P||H||V!=null,X;if((p===1||f===1)&&$>f_&&K===!1){let J=T,ae=E;n&&(J=mn({inputs:{x:T},backend:a,attrs:{perm:[0,2,1]}}),N.push(J)),r&&(ae=mn({inputs:{x:E},backend:a,attrs:{perm:[0,2,1]}}),N.push(ae));let Y=f!==1,ue=f===1,ne=J;Y&&(ne=ge({inputs:{x:J},backend:a,attrs:{shape:[F,$,1]}}),N.push(ne));let de=f===1?2:1,he=ae;ue&&(he=ge({inputs:{x:ae},backend:a,attrs:{shape:[F,1,$]}}),N.push(he));let me=d_({inputs:{a:ne,b:he},backend:a});X=FA({inputs:{x:me},backend:a,attrs:{axis:de,keepDims:!0}}),N.push(me)}else{let J=Qn(e.dtype,t.dtype),ae=new l_(_,I,[F,p,f],n,r,D,V,P,H),Y=[T,E];if(s!=null&&Y.push(s),P&&Y.push(i),H){let ue=a.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));Y.push(ue),N.push(ue)}X=a.runWebGLProgram(ae,Y,J)}let ee=ge({inputs:{x:X},backend:a,attrs:{shape:x}});N.push(X);for(let J of N)a.disposeIntermediateTensorInfo(J);return ee}function FP(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:c,activation:u,leakyreluAlpha:h}=r;return ip({a,b:s,transposeA:l,transposeB:c,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:h,activation:u})}var MP={kernelName:Ls,backendName:"webgl",kernelFunc:FP},m_="return abs(x);";function $P(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])&&r.dtype!=="complex64"){let s=n.texData.get(r.dataId),i=Kw(s.values);return n.makeTensorInfo(r.shape,r.dtype,i)}let a;return Q().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new wl(r.shape,m_):a=new Ra(r.shape,m_),n.runWebGLProgram(a,[r],r.dtype)}var DP={kernelName:zi,backendName:"webgl",kernelFunc:$P},OP=Ar+`
if (abs(x) > 1.) {
return NAN;
}
return acos(x);
`,zP=Je({opSnippet:OP}),PP={kernelName:Pi,backendName:"webgl",kernelFunc:zP},LP=Ar+`
if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,WP=Je({opSnippet:LP}),BP={kernelName:Li,backendName:"webgl",kernelFunc:WP},A_="return a + b;",VP=Zt({opSnippet:A_,packedOpSnippet:A_,supportsComplex:!0,cpuKernelImpl:pz}),UP={kernelName:fa,backendName:"webgl",kernelFunc:VP},HP=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 = ${r};
setOutput(result);
}
`}},jP=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((a,s)=>`T${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 op(e){let{inputs:t,backend:n}=e,r=t;if(r.length===1)return En({inputs:{x:r[0]},backend:n});if(r.length>Q().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(r.length/2),l=op({inputs:r.slice(0,o),backend:n}),c=op({inputs:r.slice(o),backend:n});return op({inputs:[l,c],backend:n})}let a=r.map(o=>o.dtype).reduce((o,l)=>Qn(o,l)),s=r.map(o=>o.shape),i=Q().getBool("WEBGL_PACK")?new jP(r[0].shape,s):new HP(r[0].shape,s);return n.runWebGLProgram(i,r,a)}var GP={kernelName:Ka,backendName:"webgl",kernelFunc:op};function qP(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),c=l,u=C.getAxesPermutation(c,o),h=a;u!=null&&(h=mn({inputs:{x:a},backend:n,attrs:{perm:u}}),c=C.getInnerMostAxes(c.length,o)),C.assertAxesAreInnerMostDims("all",c,o);let[d,p]=C.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=ge({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=ui(m,m.dtype,"all",n),y;if(i){let g=C.expandShapeToKeepDim(d,l);y=ge({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ge({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var XP={kernelName:dh,backendName:"webgl",kernelFunc:qP};function KP(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),c=l,u=C.getAxesPermutation(c,o),h=a;u!=null&&(h=mn({inputs:{x:a},backend:n,attrs:{perm:u}}),c=C.getInnerMostAxes(c.length,o)),C.assertAxesAreInnerMostDims("any",c,o);let[d,p]=C.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=ge({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=ui(m,m.dtype,"any",n),y;if(i){let g=C.expandShapeToKeepDim(d,l);y=ge({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ge({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var ZP={kernelName:ph,backendName:"webgl",kernelFunc:KP},JP=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 ${i} bestValue) {
bestValue = candidate;
bestIndex = inIdx;
}
}
setOutput(float(bestIndex));
}
`}},YP=class{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${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=ht(o),c=ln("coords",o),u,h;if(s===1){h=o+1;let T=ht(h);u=`
${T} sourceLocR = ${T}(${c.join()}, 0);
++${c[o-1]};
${T} sourceLocG = ${T}(${c.join()}, 0);
++${c[o-2]};
${T} sourceLocA = ${T}(${c.join()}, 0);
--${c[o-1]};
${T} sourceLocB = ${T}(${c.join()}, 0);
--${c[o-2]};`}else h=o,u=`
${l} sourceLocR = coords;
++${c[o-1]};
${l} sourceLocG = coords;
++${c[o-2]};
${l} sourceLocA = coords;
--${c[o-1]};
${l} sourceLocB = coords;
--${c[o-2]};`;let d=["x","y","z","w","u","v"].slice(0,h),p="."+d[h-1],f=d.map(T=>"int "+T),m=ln("sourceLocR",h-1).concat("inIdx.r"),A=ln("sourceLocG",h-1).concat("inIdx.g"),y=ln("sourceLocB",h-1).concat("inIdx.b"),g=ln("sourceLocA",h-1).concat("inIdx.a"),w=n==="max"?"greaterThan":"lessThan",x=r?"":`
inIdx = round(vec4(getBestIndicesAChannel(${m.join()}),
getBestIndicesAChannel(${A.join()}),
getBestIndicesAChannel(${y.join()}),
getBestIndicesAChannel(${g.join()})));`,_=`vec4(
getAChannel(${m.join()}),
hasNextCol ? getAChannel(${A.join()}) : 0.,
hasNextRow ? getAChannel(${y.join()}) : 0.,
hasNextRow && hasNextCol ? getAChannel(${g.join()}) : 0.)`,I=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()}));
}
${I}
void main() {
${l} coords = getOutputCoords();
bool hasNextCol = ${c[o-1]} < ${i[o-1]-1};
bool hasNextRow = ${c[o-2]} < ${i[o-2]-1};
${u}
ivec4 srcIdx = ivec4(sourceLocR${p}, sourceLocG${p},
sourceLocB${p}, sourceLocA${p}) * ${t};
ivec4 inIdx = srcIdx;
vec4 bestIndex = vec4(inIdx);
vec4 bestValue = ${_};
for (int i = 0; i < ${t}; i++) {
inIdx = srcIdx;
${x}
vec4 candidate = ${_};
bvec4 nan = isnan(candidate);
bvec4 replace = bvec4(
vec4(${w}(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 y_(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=C.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new JP(o,n,r==null),c=[t];r!=null&&c.push(r);let u=e.runWebGLProgram(l,c,"int32");if(u.shape[1]===1)return u;let h=y_(e,t,n,u);return e.disposeIntermediateTensorInfo(u),h}function g_(e,t,n,r=null){let a=r!=null?r.shape:t.shape,s=a[a.length-1],i=C.computeOptimalWindowSize(s),o=new YP(a,i,n,r==null),l=r==null?[t]:[t,r],c=e.runWebGLProgram(o,l,"int32");if(c.shape.length===t.shape.length){let u=g_(e,t,n,c);return e.disposeIntermediateTensorInfo(c),u}return c}function x_(e,t,n,r){let a=[n];if(C.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),a,t.shape.length),!Q().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],[i,o]=C.computeOutAndReduceShapes(t.shape,a),l=v.sizeFromShape(o),c=ge({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});s.push(c);let u=y_(e,c,r);s.push(u);let h=ge({inputs:{x:u},backend:e,attrs:{shape:i}});return s.forEach(d=>e.disposeIntermediateTensorInfo(d)),h}return g_(e,t,r)}function QP(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=C.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=mn({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let u=x_(n,l,i[0],"max");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var eL={kernelName:Za,backendName:"webgl",kernelFunc:QP};function tL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=C.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=mn({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let u=x_(n,l,i[0],"min");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var nL={kernelName:su,backendName:"webgl",kernelFunc:tL},rL=Ar+`
if (abs(x) > 1.) {
return NAN;
}
return asin(x);
`,aL=Je({opSnippet:rL}),sL={kernelName:Wi,backendName:"webgl",kernelFunc:aL},iL=Ar+"return log(x + sqrt(x * x + 1.0));",oL=Je({opSnippet:iL}),lL={kernelName:Bi,backendName:"webgl",kernelFunc:oL},uL=Ar+`
return atan(x);
`,cL=Je({opSnippet:uL}),hL={kernelName:Vi,backendName:"webgl",kernelFunc:cL},dL=xP+`
return atan(a, b);
`,pL=`
vec4 result = atan(a, b);
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+wP+`
return result;
`,fL=Zt({opSnippet:dL,packedOpSnippet:pL}),mL={kernelName:Hi,backendName:"webgl",kernelFunc:fL},AL=Ar+`
if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,yL=Je({opSnippet:AL}),gL={kernelName:Ui,backendName:"webgl",kernelFunc:yL},hc=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,c=e.dilationWidth,u=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) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let T=">=";this.userCode=`
const ivec2 strides = ivec2(${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 < ${u};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${h};
wC += ${c}) {
int xC = xCCorner + wC;
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float value = getX(batch, xR, xC, d);
// If a min / max value has already been found, use it. If not,
// use the current value.
float currMinMaxValue = mix(
value, minMaxValue, minMaxValueFound);
if (value ${T} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${r?a?m:A:`wR * ${h} + wC`};
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let g="max",w=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(w="avgValue / count");let x=Math.floor(s/4)*4,_=s%4,I=`
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 < ${u};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${x}; wC += 4) {
int xC = xCCorner + wC * ${c};
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${c}, d),
getValue(batch, xR, xC + 2 * ${c}, d),
getValue(batch, xR, xC + 3 * ${c}, d)
);
${I}
}
int xC = xCCorner + ${x};
if (${_===1}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
initializationValue,
initializationValue,
initializationValue
);
${I}
} else if (${_===2}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${c}, d),
initializationValue,
initializationValue
);
${I}
} else if (${_===3}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${c}, d),
getValue(batch, xR, xC + 2 * ${c}, d),
initializationValue
);
${I}
}
}
setOutput(${w});
}
`}},MA=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,c=e.dilationDepth,u=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",w="0.0";if(g||(w="-1.0 / 1e-20"),n){let N=">=";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 += ${c}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${p};
wR += ${u}) {
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 ${N} 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 * ${f} + wC`};
}
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let x="max",_=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(_="avgValue / count");let I=Math.floor(s/4)*4,T=s%4,E=`
if (${g}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${x}(values, minMaxValue);
}
`;this.userCode=`
const ivec3 strides =
ivec3(${i}, ${o}, ${l});
const ivec3 pads = ivec3(${m}, ${A}, ${y});
const float initializationValue = ${w};
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 >= ${e.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xD, xR, xC, ch);
}
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
int xDCorner = xCorner.x;
int xRCorner = xCorner.y;
int xCCorner = xCorner.z;
// max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
// ? = to be determined
vec4 minMaxValue = vec4(${w});
float avgValue = 0.0;
count = 0.0;
for (int wD = 0; wD < ${d};
wD += ${c}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${p};
wR += ${u}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${I}; 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)
);
${E}
}
int xC = xCCorner + ${I};
if (${T===1}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
initializationValue,
initializationValue,
initializationValue
);
${E}
} else if (${T===2}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${h}, ch),
initializationValue,
initializationValue
);
${E}
} else if (${T===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
);
${E}
}
}
setOutput(${_});
}
}
`}};function xL(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,c=1;v.assert(C.eitherStridesOrDilationsAreOne(i,c),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=C.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return En({inputs:{x:a},backend:n});let h=new hc(u,"avg",!1);return n.runWebGLProgram(h,[a],"float32")}var wL={kernelName:Ja,backendName:"webgl",kernelFunc:xL};function _L(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:c}=r,u=[1,1,1],h=C.computePool3DInfo(a.shape,s,i,u,o,l,c),d=new MA(h,"avg",!1);return n.runWebGLProgram(d,[a],"float32")}var bL={kernelName:iu,backendName:"webgl",kernelFunc:_L},vL=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,c=o-1-e.padInfo.top,u=l-1-e.padInfo.left,h=1/(t*n);this.userCode=`
const ivec2 pads = ivec2(${c}, ${u});
const float avgMultiplier = float(${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 >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(b, idyR, idyC, d);
dotProd += dyValue * avgMultiplier;
}
}
setOutput(dotProd);
}
`}},kL=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.effectiveFilterDepth,h=e.effectiveFilterHeight,d=e.effectiveFilterWidth,p=u-1-e.padInfo.front,f=h-1-e.padInfo.top,m=d-1-e.padInfo.left,A=1/(t*n*r);this.userCode=`
const ivec3 pads = ivec3(${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 < ${u};
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 += ${c}) {
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 IL(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:c,dimRoundingMode:u}=r,h=[1,1,1],d=C.computePool3DInfo(i.shape,o,l,h,c,u),p=new kL(d);return n.runWebGLProgram(p,[a],i.dtype)}var NL={kernelName:mh,backendName:"webgl",kernelFunc:IL};function SL(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:c}=r,u=C.computePool2DInfo(i.shape,o,l,1,c),h=new vL(u);return n.runWebGLProgram(h,[a],i.dtype)}var TL={kernelName:fh,backendName:"webgl",kernelFunc:SL};function EL(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;return ip({a,b:s,transposeA:i,transposeB:o,backend:n})}var CL={kernelName:Ya,backendName:"webgl",kernelFunc:EL},RL=class{constructor(e,t,n,r,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,n);let i="0.0";r!=null&&(C.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(C.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)));
}
`}},FL=class{constructor(e,t,n,r,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";r!=null&&(C.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(C.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);
}
`}},ML=({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 c=[r,a,s],u=null;i!=null&&(u=i.shape,c.push(i));let h=null;o!=null&&(h=o.shape,c.push(o));let d=Q().getBool("WEBGL_PACK_NORMALIZATION")?new FL(r.shape,a.shape,s.shape,u,h,l):new RL(r.shape,a.shape,s.shape,u,h,l);return t.runWebGLProgram(d,c,c[0].dtype)},$L={kernelName:us,backendName:"webgl",kernelFunc:ML},OL=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ht(this.rank),n=`uniform int start[${this.rank}];`,r=DL(this.rank),a,s=e.map((i,o)=>`sourceLoc.${$A[o]} = start[${o}] + coords.${$A[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)}}},$A=["x","y","z","w","u","v"];function DL(e){if(e===1)return"sourceLoc";if(e<=6)return $A.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var zL=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=ht(this.rank),n=ln("coords",this.rank),r=ln("sourceLoc",this.rank),a=this.rank===1?"sourceLoc":`vec2(${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((c,u)=>`start[${u}]`).join()});`:e.map((c,u)=>`${r[u]} = ${n[u]} + start[${u}];`).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 PL(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.complexParentRefCount=0,i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=rn.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 dc(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,size:i}=r,[o,l]=rn.parseSliceParams(a,s,i);if(rn.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=Mz(h.values,o,l,a.shape,a.dtype);return n.makeTensorInfo(l,a.dtype,d)}let{isPacked:c}=n.texData.get(a.dataId),u=rn.isSliceContinous(a.shape,o,l);if(c||!u){let h=Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new zL(l):new OL(l),d=h.getCustomSetupFunc(o);return n.runWebGLProgram(h,[a],a.dtype,d)}return n.uploadToGPU(a.dataId),PL(a,o,l,n)}var LL={kernelName:To,backendName:"webgl",kernelFunc:dc},WL=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,w)=>g*w),l=C.getReshaped(a.shape,s,o),c=C.getPermuted(l.length,s.length),u=C.getReshapedPermuted(a.shape,s,o),h=C.getSliceBeginCoords(i,s.length),d=C.getSliceSize(u,i,s.length),p=[],f=ge({inputs:{x:a},backend:n,attrs:{shape:l}}),m=mn({inputs:{x:f},backend:n,attrs:{perm:c}}),A=ge({inputs:{x:m},backend:n,attrs:{shape:u}}),y=dc({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},BL={kernelName:ou,backendName:"webgl",kernelFunc:WL};function VL(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),c=Xw(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}var UL={kernelName:Ah,backendName:"webgl",kernelFunc:VL},HL="return float(a != b);",w_=Zt({opSnippet:HL,dtype:"bool"}),jL={kernelName:Ao,backendName:"webgl",kernelFunc:w_};function pc(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return En({inputs:{x:a.complexTensorInfos.real},backend:n})}var GL={kernelName:zh,backendName:"webgl",kernelFunc:pc},qL="return float(int(x));";function XL(e,t){let n=new Ra(e.shape,qL),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}function DA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dtype:s}=r;if(s==="complex64"){if(a.dtype==="complex64")return En({inputs:{x:a},backend:n});let i=Ct(a.shape),o=DA({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=Fa({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=pc({inputs:{input:a},backend:n}),o=DA({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=En({inputs:{x:a},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return XL(a,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=w_({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 KL={kernelName:Qa,backendName:"webgl",kernelFunc:DA},__="return ceil(x);",ZL=Je({opSnippet:__,packedOpSnippet:__,cpuKernelImpl:mz}),JL={kernelName:ji,backendName:"webgl",kernelFunc:ZL},YL=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)}}},QL=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 eW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=r,o;Q().getBool("WEBGL_PACK_CLIP")?o=new QL(a.shape):o=new YL(a.shape);let l=o.getCustomSetupFunc(s,i);return n.runWebGLProgram(o,[a],a.dtype,l)}var tW={kernelName:ma,backendName:"webgl",kernelFunc:eW},nW=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 b_(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function rW(e){let{inputs:t,backend:n}=e,{x:r}=t,a=n.texData.get(r.dataId),s=new nW(r.shape),i=[b_(r,a.complexTensorInfos.real),b_(r,a.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var aW={kernelName:lu,backendName:"webgl",kernelFunc:rW},sW=class{constructor(e){this.outputShape=[],this.outputShape=C.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let 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;
${n.join(`
`)}
}
`}},iW=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=C.computeOutShape(e,t);let n=this.outputShape,r=n.length,a=ht(r),s=ln("coords",r),i=["x","y","z","w","u","v"].slice(0,r);this.variableNames=e.map((f,m)=>`T${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],c=i.slice(-2),u=i.join(),h=`if (${l} < ${o[0]}) {
return getChannel(
getT0(${u}), vec2(${c.join()}));
}`;for(let f=1;f<o.length;f++){let m=o[f-1];h+=`
if (${l} < ${o[f]} && ${l} >= ${o[f-1]}) {
return getChannel(
getT${f}(${lp(i,l,m)}),
vec2(${lp(c,l,m)}));
}`}let d=o.length,p=o[o.length-1];h+=`
return getChannel(
getT${d}(${lp(i,l,p)}),
vec2(${lp(c,l,p)}));`,this.userCode=`
float getValue(${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 lp(e,t,n){let r=e.indexOf(t);return e.map((a,s)=>s===r?`${a} - ${n}`:a).join()}function up(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return En({inputs:{x:a.complexTensorInfos.imag},backend:n})}var oW={kernelName:Ch,backendName:"webgl",kernelFunc:up};function bl(e,t,n){let r=e[0].dtype;if(r==="complex64"){let c=e.map(f=>pc({inputs:{input:f},backend:n})),u=e.map(f=>up({inputs:{input:f},backend:n})),h=bl(c,t,n),d=bl(u,t,n),p=Fa({inputs:{real:h,imag:d},backend:n});return c.forEach(f=>n.disposeIntermediateTensorInfo(f)),u.forEach(f=>n.disposeIntermediateTensorInfo(f)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),p}if(r==="string"){let{tensors2D:c,outShape:u}=v_(e,t,n),h=c.map(A=>({vals:n.readSync(A.dataId),shape:A.shape})),d=c[0].shape[0]===1,p=Az(h,u,r,d),f=C.computeOutShape(e.map(A=>A.shape),t),m=n.makeTensorInfo(f,r,p);return c.forEach(A=>n.disposeIntermediateTensorInfo(A)),m}if(e.length>Q().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let c=Math.floor(e.length/2),u=bl(e.slice(0,c),t,n),h=bl(e.slice(c),t,n),d=bl([u,h],t,n);return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),d}if(Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let c=new iW(e.map(u=>u.shape),t);return n.runWebGLProgram(c,e,r)}let{tensors2D:a,outShape:s}=v_(e,t,n),i=new sW(a.map(c=>c.shape)),o=n.runWebGLProgram(i,a,r);a.forEach(c=>n.disposeIntermediateTensorInfo(c));let l=ge({inputs:{x:o},attrs:{shape:s},backend:n});return n.disposeIntermediateTensorInfo(o),l}function v_(e,t,n){let r=C.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>ge({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:r}}function k_(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=C.computeOutShape(t.map(c=>c.shape),s);if(v.sizeFromShape(i)===0)return n.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(c=>v.sizeFromShape(c.shape)>0);if(o.length===1)return En({inputs:{x:o[0]},backend:n});let l=o.map(c=>c.shape);return C.assertParamsConsistent(l,s),bl(o,s,n)}var lW={kernelName:Gi,backendName:"webgl",kernelFunc:k_},I_=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,c=e.dilationHeight,u=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,w="",x="";n&&(r?w=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${n}
}`:a?w=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${n}
}`:w=`
float activation(float x) {
${n}
}
`,x="result = activation(result);");let _=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${w}
const ivec2 strides = ivec2(${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 * ${c};
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 < ${p}; d1 += 4) {
vec4 wValues = vec4(
getW(wR, wC, d1, d2),
getW(wR, wC, d1 + 1, d2),
getW(wR, wC, d1 + 2, d2),
getW(wR, wC, d1 + 3, d2)
);
if (${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;
${_}
${x}
setOutput(result);
}
`}},uW=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.filterDepth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
const ivec3 strides = ivec3(${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 < ${u}; 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 * ${c};
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);
}
`}},cW=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:c,dilationHeight:u,dataFormat:h}=n,{left:d,top:p}=o,f=a*r,m=on(),A=h==="channelsLast",y=A?0:1,g=A?1:2,w="";for(let x=0;x<=1;x++)for(let _=0;_<=1;_++)w+=`
blockIndex = rc.y + ${_};
pos = rc.x + ${x};
if(blockIndex < ${e[1]} && pos < ${e[0]}) {
offsetY = int(blockIndex / (${l})) * ${i} - ${p};
d0 = offsetY + ${u} * (pos / ${f});
if(d0 < ${t[y]} && d0 >= 0) {
offsetX = int(mod(float(blockIndex), ${l}.) * ${s}. - ${d}.);
d1 = offsetX + ${c} * (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[${x*2+_}] = getChannel(
getA(d0, int(innerDims.x),
int(innerDims.y)), innerDims);
} else {
innerDims = vec2(d0, d1);
result[${x*2+_}] = 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;
${w}
${m.output} = result;
}
`}};function N_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,c=r.texData.get(e.dataId),u=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)&&u>f_,w=l[2]%2!=0&&!!c.isPacked;if(g||!Q().getBool("WEBGL_LAZILY_UNPACK")||!Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!w){let x=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],_=ge({inputs:{x:e},backend:r,attrs:{shape:[1,x,n.inChannels]}}),I=ge({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),T=ip({a:_,b:I,transposeA:f,transposeB:m,backend:r,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});A=ge({inputs:{x:T},backend:r,attrs:{shape:n.outShape}}),y.push(_),y.push(I),y.push(T)}else{let x=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),_={dataId:e.dataId,shape:[1,x,n.inChannels],dtype:e.dtype},I=c.shape;c.shape=c.shape.slice(),c.shape[c.shape.length-2]++,v.assert(sc(c.shape,_.shape),()=>`packed reshape ${c.shape} to ${_.shape} isn't free`);let T=ge({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(T);let E=ip({a:_,b:T,backend:r,transposeA:f,transposeB:m,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),N=r.texData.get(E.dataId);v.assert(N.isPacked,()=>"batchMatMul result is expected to be packed"),c.shape=I,N.shape=n.outShape,A=En({inputs:{x:E},backend:r}),A.shape=n.outShape,y.push(E)}for(let x of y)r.disposeIntermediateTensorInfo(x);return A}function S_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:c,inChannels:u,outWidth:h,outHeight:d,dataFormat:p}=n,f=p==="channelsLast",m=l*c*u,A=d*h,y=[m,A],g=!0,w=!1,x=[],_=ge({inputs:{x:e},backend:r,attrs:{shape:e.shape.slice(1)}}),I=ge({inputs:{x:t},backend:r,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});x.push(_),x.push(I);let T=new cW(y,_.shape,n),E=r.runWebGLProgram(T,[_],"float32"),N=ge({inputs:{x:E},backend:r,attrs:{shape:[1,y[0],y[1]]}});x.push(E),x.push(N);let F=a!=null,$=s!=null,D=o==="leakyrelu",P=o?ap(o,!0):null,H=new l_(N.shape,I.shape,[1,A,n.outChannels],g,w,F,P,$,D),V=[N,I];if(a&&V.push(a),$&&V.push(s),D){let J=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));V.push(J),x.push(J)}let K=r.runWebGLProgram(H,V,"float32"),X=f?[1,d,h,n.outChannels]:[1,n.outChannels,d,h],ee=ge({inputs:{x:K},backend:r,attrs:{shape:X}});x.push(K);for(let J of x)r.disposeIntermediateTensorInfo(J);return ee}function hW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:c,dimRoundingMode:u}=r,h=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(a.shape,s.shape,i,c,o,u,!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=N_({x:a,filter:s,convInfo:d,backend:n});else if(Q().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)p=S_({x:a,filter:s,convInfo:d,backend:n});else{let m=new I_(d);p=n.runWebGLProgram(m,[a,s],"float32")}let f=ge({inputs:{x:p},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(p),f}var dW={kernelName:es,backendName:"webgl",kernelFunc:hW},pW=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);
}
`}},fW=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,c=s?2:3,u=s?3:1;this.userCode=`
const ivec2 pads = ivec2(${i}, ${o});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d1 = coords[${u}];
ivec2 dyCorner = ivec2(coords[${l}], coords[${c}]) - 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);
}
`}},mW=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 >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yF, yR, yC, d2);
float xValue = getX(b, xF, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
}
setOutput(dotProd);
}
`}},AW=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,c=r-1-e.padInfo.left;this.userCode=`
const ivec3 pads = ivec3(${o}, ${l}, ${c});
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 yW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:c,filterShape:u}=r,h=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(a.shape,u,i,1,o,c,!1,h),p=new pW(d);return n.runWebGLProgram(p,[a,s],"float32")}var gW={kernelName:gh,backendName:"webgl",kernelFunc:yW};function xW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:c,dimRoundingMode:u}=r,h=C.convertConv2DDataFormat(c),d=C.computeConv2DInfo(i,s.shape,o,1,l,u,!1,h),p=new fW(d);return n.runWebGLProgram(p,[a,s],"float32")}var wW={kernelName:ts,backendName:"webgl",kernelFunc:xW};function _W(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=C.computeConv3DInfo(a.shape,s.shape,i,l,o),u=new uW(c);return n.runWebGLProgram(u,[a,s],"float32")}var bW={kernelName:uu,backendName:"webgl",kernelFunc:_W};function vW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r,c=C.computeConv3DInfo(a.shape,l,i,1,o),u=new mW(c);return n.runWebGLProgram(u,[a,s],"float32")}var kW={kernelName:xh,backendName:"webgl",kernelFunc:vW};function IW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r,c=C.computeConv3DInfo(l,s.shape,o,1,i),u=new AW(c);return n.runWebGLProgram(u,[a,s],"float32")}var NW={kernelName:wh,backendName:"webgl",kernelFunc:IW},SW=o_+`
return cos(x);
`,TW=Je({opSnippet:SW}),EW={kernelName:ns,backendName:"webgl",kernelFunc:TW},CW=`
float e2x = exp(-x);
return (e2x + 1.0 / e2x) / 2.0;
`,RW=Je({opSnippet:CW}),FW={kernelName:qi,backendName:"webgl",kernelFunc:RW},MW=class{constructor(e,t,n,r,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[c]=t,[u,h]=n;this.outputShape=[c,u,h,l];let d=r==="bilinear"?1:0,[p,f]=[`${i-1}.0`,`${o-1}.0`],[m,A,y]=u>1?[`${(i-1)/(u-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[g,w,x]=h>1?[`${(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 = ${w};
float in_y = ${y};
if( in_y < 0.0 || in_y > ${p} ) {
setOutput(float(${a}));
return;
}
float in_x = ${x};
if( in_x < 0.0 || in_x > ${f} ) {
setOutput(float(${a}));
return;
}
vec2 sourceFracIndexCR = vec2(in_x,in_y);
if(${d} == 1) {
// Compute the four integer indices.
ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));
float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);
vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);
float top = topLeft + (topRight - topLeft) * fracCR.x;
float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
float newValue = top + (bottom - top) * fracCR.y;
setOutput(newValue);
} else {
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestCR = ivec2(floor(
sourceFracIndexCR + vec2(0.5,0.5)));
float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
setOutput(newValue);
}
}
`}},$W=e=>{let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:c}=r,u=new MW(a.shape,s.shape,o,l,c);return n.runWebGLProgram(u,[a,s,i],"float32")},DW={kernelName:Xi,backendName:"webgl",kernelFunc:$W},C_=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let r=e.length,a=t?"0.0":`getX(${T_(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() {
${ht(r)} coords = getOutputCoords();
int end = ${E_(r,"coords")};
float val = ${a};
int pow2 = int(pow(2.0, index));
if (${i}) {
int idx = ${o};
${E_(r,"coords")} = idx;
val += getX(${T_(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 T_(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 ${e} is not yet supported`)}function E_(e,t){if(e===1)return`${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 ${e} is not yet supported`)}function OW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r,l=a.shape.length,c=C.getAxesPermutation([s],l),u=a;c!=null&&(u=mn({inputs:{x:a},backend:n,attrs:{perm:c}}));let h=C.getInnerMostAxes(1,l)[0];if(h!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${a.shape.length-1} but got axis=${s}`);let d=a.shape[h],p=En({inputs:{x:u},backend:n});for(let f=0;f<=Math.ceil(Math.log2(d))-1;f++){let m=new C_(u.shape,!1,o),A=m.getCustomSetupFunc(f),y=p;p=n.runWebGLProgram(m,[p],p.dtype,A),n.disposeIntermediateTensorInfo(y)}if(i){let f=new C_(u.shape,i,o),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(c!=null){let f=C.getUndoAxesPermutation(c),m=mn({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(u),m}return p}var zW={kernelName:rs,backendName:"webgl",kernelFunc:OW};function PW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.readSync(a.dataId),c=n.readSync(s.dataId),u=Xw(l,c,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}else if(a.shape.length===2){let l=n.bufferSync(a),c=n.bufferSync(s),u=fz(l,c,i,o);return n.makeTensorInfo(u.shape,s.dtype,u.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var LW={kernelName:_h,backendName:"webgl",kernelFunc:PW},WW=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 BW(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],c=i==="NHWC"?a.shape[2]:a.shape[3],u=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,d=c*s,p=u/(s*s),f=i==="NHWC"?[o,h,d,p]:[o,p,h,d],m=new WW(f,s,i);return n.runWebGLProgram(m,[a],a.dtype)}var VW={kernelName:Ki,backendName:"webgl",kernelFunc:BW},R_=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,c=e.strideHeight,u=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=`
${A}
const ivec2 strides = ivec2(${c}, ${u});
const ivec2 pads = ivec2(${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}
${y}
setOutput(result);
}
`}},F_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,c=e.strideHeight,u=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=f,A="int xR; int xC; int xCOffset;";for(let x=0;x<p;x++)for(let _=0;_<f;_++)A+=`
vec4 xTexelR${x}C${_*2} = vec4(0.);
vec4 wR${x}C${_} = vec4(0.);
vec4 xR${x}C${_} = vec4(0.);`;for(let x=0;x<p;x++)for(let _=0;_<m;_++){let I=_*2;if(A+=`
xR = xRCorner + ${x*h};
xC = xCCorner + ${I*d};
`,u===1){if(I<f&&(l%2==1?A+=`
xCOffset = xC + 1;
if(xR >= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) {
xTexelR${x}C${I} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if(xCOffset + 1 >= ${i}) {
xTexelR${x}C${I}.zw = vec2(0.);
}
} else {
xTexelR${x}C${I} = 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 >= ${i}) {
previous.zw = vec2(0.);
}
xR${x}C${I} = vec4(previous.zw, xTexelR${x}C${I}.xy);
} else {
xR${x}C${I} = vec4(0, 0, xTexelR${x}C${I}.xy);
}
`:A+=`
if(xR >= 0 && xR < ${s} && xC >= 0 && xC < ${i}) {
xTexelR${x}C${I} = getX(batch, xR, xC, d1);
} else {
xTexelR${x}C${I} = vec4(0.);
}
xR${x}C${I} = xTexelR${x}C${I};
`,I+1<f)){let T=l%2==0?v.nearestLargerEven(d):d;d%2==0&&l%2==1||d%2!=0&&l%2!=1?(A+=`
xCOffset = xC + ${l%2} + ${T};
if(xR >= 0 && xR < ${s} &&
xCOffset >= 0 && xCOffset < ${i}) {
xTexelR${x}C${I+2} = getX(batch, xR, xCOffset, d1);
}
`,d>1&&(A+=`
xCOffset -= 2;
if(xR >= 0 && xR < ${s} &&
xCOffset >= 0 && xCOffset < ${i}) {
xTexelR${x}C${I} = getX(batch, xR, xCOffset, d1);
} else {
xTexelR${x}C${I} = vec4(0.);
}
`),A+=`
xR${x}C${I+1} = vec4(
xTexelR${x}C${I}.zw, xTexelR${x}C${I+2}.xy);
`):A+=`
xCOffset = xC + ${T};
if(xR >= 0 && xR < ${s} &&
xCOffset >= 0 && xCOffset < ${i}) {
xTexelR${x}C${I+2} = getX(batch, xR, xCOffset, d1);
}
xR${x}C${I+1} = xTexelR${x}C${I+2};
`}}else I<f&&(A+=`
if(xR >= 0 && xR < ${s}) {
`,l%2==1?(A+=`
xCOffset = xC + 1 - ${u};
if(xCOffset >= 0 && xCOffset < ${i}) {
xTexelR${x}C${I} = getX(batch, xR, xCOffset, d1);
} else {
xTexelR${x}C${I} = vec4(0.);
}
if(xC + 1 >= 0 && xC + 1 < ${i}) {
xTexelR${x}C${I+2} = getX(batch, xR, xC + 1, d1);
} else {
xTexelR${x}C${I+2} = vec4(0.);
}
xR${x}C${I} = vec4(
xTexelR${x}C${I}.zw, xTexelR${x}C${I+2}.zw);
`,I+1<f&&(A+=`
vec4 final = vec4(0.);
xCOffset = xC + 1 + ${u};
if(xCOffset >= 0 && xCOffset < ${i}) {
final = getX(batch, xR, xCOffset, d1);
}
xR${x}C${I+1} = vec4(xTexelR${x}C${I+2}.xy, final.xy);
`)):(A+=`
if(xC >= 0 && xC < ${i}) {
xTexelR${x}C${I} = getX(batch, xR, xC, d1);
} else {
xTexelR${x}C${I} = vec4(0.);
}
xCOffset = xC + ${u};
if(xCOffset >= 0 && xCOffset < ${i}) {
xTexelR${x}C${I+2} = getX(batch, xR, xCOffset, d1);
} else {
xTexelR${x}C${I+2} = vec4(0.);
}
xR${x}C${I} = vec4(
xTexelR${x}C${I}.xy, xTexelR${x}C${I+2}.xy);
`,I+1<f&&(A+=`
xR${x}C${I+1} = vec4(
xTexelR${x}C${I}.zw, xTexelR${x}C${I+2}.zw);
`)),A+="}");I<f&&(A+=`
vec4 wTexelR${x}C${I} = getW(${x}, ${I}, d1, q);
wR${x}C${I} = vec4(wTexelR${x}C${I}.xz, wTexelR${x}C${I}.xz);
`,I+1<f&&(A+=`
vec4 wTexelR${x}C${I+1} = getW(${x}, ${I+1}, d1, q);
wR${x}C${I+1} =
vec4(wTexelR${x}C${I+1}.xz, wTexelR${x}C${I+1}.xz);`))}for(let x=0;x<p;x++)for(let _=0;_<f;_++)A+=`dotProd += xR${x}C${_} * wR${x}C${_};`;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 w=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${y}
const ivec2 strides = ivec2(${c}, ${u});
const ivec2 pads = ivec2(${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;
${w}
${g}
setOutput(result);
}
`}};function UW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:c}=r,u=l;u==null&&(u=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(i,u),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let h=C.computeConv2DInfo(a.shape,s.shape,i,u,o,c,!0),d;return Q().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?d=new F_(h):d=new R_(h),n.runWebGLProgram(d,[a,s],"float32")}var HW={kernelName:as,backendName:"webgl",kernelFunc:UW},jW=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 >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
setOutput(dotProd);
}
`}},GW=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
const ivec2 pads = ivec2(${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 * ${o} + dm;
float xValue = getDy(batch, idyR, idyC, d2);
float wValue = getW(wRPerm, wCPerm, d1, dm);
dotProd += xValue * wValue;
}
}
}
setOutput(dotProd);
}
`}};function qW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,filterShape:u}=r,h=C.computeConv2DInfo(a.shape,u,i,o,l,c,!0),d=new jW(h);return n.runWebGLProgram(d,[a,s],"float32")}var XW={kernelName:bh,backendName:"webgl",kernelFunc:qW};function KW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,inputShape:u}=r,h=C.computeConv2DInfo(u,s.shape,i,o,l,c,!0),d=new GW(h);return n.runWebGLProgram(d,[a,s],"float32")}var ZW={kernelName:vh,backendName:"webgl",kernelFunc:KW},JW=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
setOutput(val);
}
`}};function YW(e){let{inputs:t,backend:n}=e,{x:r}=t,a=[...r.shape,...r.shape],s=v.sizeFromShape(r.shape),i=ge({inputs:{x:r},backend:n,attrs:{shape:[s]}}),o=new JW(s),l=n.runWebGLProgram(o,[i],i.dtype),c=ge({inputs:{x:l},backend:n,attrs:{shape:a}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),c}var QW={kernelName:kh,backendName:"webgl",kernelFunc:YW},eB=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:r,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:c}=e,{top:u,left:h}=r;this.userCode=`
const ivec2 strides = ivec2(${a}, ${s});
const ivec2 pads = ivec2(${u}, ${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 * ${c};
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 tB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=C.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),u,h=new eB(c);u=n.runWebGLProgram(h,[a,s],"float32");let d=ge({inputs:{x:u},backend:n,attrs:{shape:c.outShape}});return n.disposeIntermediateTensorInfo(u),d}var nB={kernelName:cu,backendName:"webgl",kernelFunc:tB},rB="return (x >= 0.0) ? x : (exp(x) - 1.0);",aB=`
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;
`,sB=Je({opSnippet:rB,packedOpSnippet:aB}),iB={kernelName:Zi,backendName:"webgl",kernelFunc:sB},oB="return (b >= 1.0) ? a : a * (b + 1.0);",lB=`
vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,uB=e=>{let{inputs:t,backend:n}=e,{dy:r,y:a}=t,s=Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new cc(lB,r.shape,a.shape):new _l(oB,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)},cB={kernelName:Sh,backendName:"webgl",kernelFunc:uB},hB=`
return vec4(equal(a, b));
`,dB="return float(a == b);",pB=Zt({opSnippet:dB,packedOpSnippet:hB,dtype:"bool"}),fB={kernelName:Yi,backendName:"webgl",kernelFunc:pB},mB=`
// Error function is calculated approximately with elementary function.
// See "Handbook of Mathematical Functions with Formulas,
// Graphs, and Mathematical Tables", Abramowitz and Stegun.
float p = ${C.ERF_P};
float a1 = ${C.ERF_A1};
float a2 = ${C.ERF_A2};
float a3 = ${C.ERF_A3};
float a4 = ${C.ERF_A4};
float a5 = ${C.ERF_A5};
float sign = sign(x);
x = abs(x);
float t = 1.0 / (1.0 + p * x);
return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
`,AB=Je({opSnippet:mB}),yB={kernelName:Ji,backendName:"webgl",kernelFunc:AB},M_="return exp(x);",$_=Je({opSnippet:M_,packedOpSnippet:M_,cpuKernelImpl:yz}),gB={kernelName:is,backendName:"webgl",kernelFunc:$_};function OA(e){let{inputs:t,attrs:n,backend:r}=e,{dim:a}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),ge({inputs:{x:s},backend:r,attrs:{shape:o}})}var xB={kernelName:Qi,backendName:"webgl",kernelFunc:OA},D_="return exp(x) - 1.0;",wB=Je({opSnippet:D_,packedOpSnippet:D_,cpuKernelImpl:gz}),_B={kernelName:eo,backendName:"webgl",kernelFunc:wB},O_=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 z_(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=ge({inputs:{x:e},backend:n,attrs:{shape:[i,s]}}),l=o.shape,c=new O_("real",l,t),u=new O_("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(c,h,"float32"),p=n.runWebGLProgram(u,h,"float32"),f=Fa({inputs:{real:d,imag:p},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p);let m=ge({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(f),m}function bB(e){let{inputs:t,backend:n}=e,{input:r}=t;return z_(r,!1,n)}var vB={kernelName:Th,backendName:"webgl",kernelFunc:bB},kB=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 zA(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 kB(r,a),o=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[],s,o)}}var IB={kernelName:hu,backendName:"webgl",kernelFunc:zA},NB=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 < ${t}) {
outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
} else {
outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
}
setOutput(outputValue);
}
`}},SB={kernelName:to,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,r=t,a=new NB(n.shape);return r.runWebGLProgram(a,[n],n.dtype)}},P_="return floor(x);",TB=Je({opSnippet:P_,packedOpSnippet:P_,cpuKernelImpl:xz}),EB={kernelName:os,backendName:"webgl",kernelFunc:TB},CB=`
float s = sign(a) * sign(b);
int ia = round(a);
int ib = round(b);
if (ib != 0) {
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
return float(idiv(ia, ib, s));
} else {
return NAN;
}
`,RB=`
ivec4 ia = round(a);
ivec4 ib = round(b);
bvec4 cond = notEqual(ib, ivec4(0));
ivec4 result = ivec4(0);
vec4 s = sign(a) * sign(b);
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
if (cond[0]) {
result[0] = idiv(ia[0], ib[0], s[0]);
}
if (cond[1]) {
result[1] = idiv(ia[1], ib[1], s[1]);
}
if (cond[2]) {
result[2] = idiv(ia[2], ib[2], s[2]);
}
if (cond[3]) {
result[3] = idiv(ia[3], ib[3], s[3]);
}
return vec4(result);
`,FB=Zt({opSnippet:CB,packedOpSnippet:RB,dtype:"int32"}),MB={kernelName:ls,backendName:"webgl",kernelFunc:FB},$B=class{constructor(e){this.variableNames=["A"];let t=on(),[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 = ${t.texture2D}(A, uv);
float value;
if (depth == 0) {
value = values.r;
} else if (depth == 1) {
value = values.g;
} else if (depth == 2) {
value = values.b;
} else if (depth == 3) {
value = values.a;
}
setOutput(floor(value * 255.0 + 0.5));
}
`}},DB=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=on(),[n,r]=e;this.outputShape=e,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec4 result = vec4(0.);
for(int row=0; row<=1; row++) {
for(int col=0; col<=1; col++) {
texC = coords[1] + row;
depth = coords[2] + col;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${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;
}
`}},zB={kernelName:Vh,backendName:"webgl",kernelFunc:OB},vl;function OB(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=typeof ImageBitmap!="undefined"&&a instanceof ImageBitmap,[c,u]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],h=[u,c],d=[u,c,s];(o||i||l)&&(vl==null&&(vl=document.createElement("canvas").getContext("2d")),vl.canvas.width=c,vl.canvas.height=u,vl.drawImage(a,0,0,c,u),a=vl.canvas);let p=n.makeTensorInfo(h,"int32");n.texData.get(p.dataId).usage=Hn.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(p.dataId),a);let f=Q().getBool("WEBGL_PACK")?new DB(d):new $B(d),m=n.runWebGLProgram(f,[p],"int32");return n.disposeData(p.dataId),m}function PB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dataFormat:u,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=C.convertConv2DDataFormat(u),A=C.computeConv2DInfo(a.shape,s.shape,l,h,c,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=N_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else if(Q().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)y=S_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else{let x=i!=null,_=o!=null,I=p==="leakyrelu",T=p?ap(p,!1):null,E=new I_(A,x,T,_,I),N=[a,s];if(i&&N.push(i),o&&N.push(o),I){let F=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));N.push(F),g.push(F)}y=n.runWebGLProgram(E,N,"float32")}let w=ge({inputs:{x:y},backend:n,attrs:{shape:A.outShape}});return g.push(y),g.forEach(x=>n.disposeIntermediateTensorInfo(x)),w}var LB={kernelName:Ws,backendName:"webgl",kernelFunc:PB};function WB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dilations:u,dimRoundingMode:h,activation:d,leakyreluAlpha:p}=r,f=[],m=u;m==null&&(m=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let A=C.computeConv2DInfo(a.shape,s.shape,l,m,c,h,!0),y=Q().getBool("WEBGL_PACK_DEPTHWISECONV")&&A.strideWidth<=2&&A.outChannels/A.inChannels==1,g=d?ap(d,y):null,w=[a,s],x=i!=null,_=o!=null,I=d==="leakyrelu";if(x&&w.push(i),_&&w.push(o),I){let N=n.makeTensorInfo([],"float32",v.createScalarValue(p,"float32"));w.push(N),f.push(N)}let T;y?T=new F_(A,x,g,_,I):T=new R_(A,x,g,_,I);let E=n.runWebGLProgram(T,w,"float32");return f.forEach(N=>n.disposeIntermediateTensorInfo(N)),E}var BB={kernelName:Bs,backendName:"webgl",kernelFunc:WB},VB=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let r=ht(t.length),a=ht(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 UB(e){let{inputs:t,backend:n}=e,{params:r,indices:a}=t,s=a.shape,i=s[s.length-1],[o,l,c,u]=C.prepareAndValidate(r,a),h=ge({inputs:{x:a},backend:n,attrs:{shape:[l,i]}}),d=ge({inputs:{x:r},backend:n,attrs:{shape:[v.sizeFromShape(r.shape)/c,c]}}),p=new VB(i,u,[l,c]),f=n.runWebGLProgram(p,[d,h],d.dtype),m=ge({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),m}var HB={kernelName:ro,backendName:"webgl",kernelFunc:UB},GB=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=ht(this.rank),r=jB(e,2);this.userCode=`
void main() {
${n} resRC = getOutputCoords();
setOutput(getA(${r}));
}
`}};function jB(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 qB(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],c=C.segment_util.collectGatherOpShapeInfo(a,s,l,o),u=v.sizeFromShape(s.shape),h=[],d=ge({inputs:{x:a},backend:n,attrs:{shape:[c.batchSize,c.outerSize,c.dimSize,c.sliceSize]}}),p=ge({inputs:{x:s},backend:n,attrs:{shape:[c.batchSize,u/c.batchSize]}});h.push(d),h.push(p);let f=[c.batchSize,c.outerSize,u/c.batchSize,c.sliceSize];if(n.shouldExecuteOnCPU([a,s])||a.dtype==="string"){let g=n.bufferSync(p),w=n.bufferSync(d),x=wz(w,g,f);return h.forEach(_=>n.disposeIntermediateTensorInfo(_)),n.makeTensorInfo(c.outputShape,x.dtype,x.values)}let m=new GB(d.shape,f),A=n.runWebGLProgram(m,[d,p],d.dtype);h.push(A);let y=ge({inputs:{x:A},backend:n,attrs:{shape:c.outputShape}});return h.forEach(g=>n.disposeIntermediateTensorInfo(g)),y}var XB={kernelName:no,backendName:"webgl",kernelFunc:qB},KB="return float(a > b);",ZB=`
return vec4(greaterThan(a, b));
`,JB=Zt({opSnippet:KB,packedOpSnippet:ZB,cpuKernelImpl:_z,dtype:"bool"}),YB={kernelName:ao,backendName:"webgl",kernelFunc:JB},QB="return float(a >= b);",eV=`
return vec4(greaterThanEqual(a, b));
`,tV=Zt({opSnippet:QB,packedOpSnippet:eV,dtype:"bool"}),nV={kernelName:cs,backendName:"webgl",kernelFunc:tV};function rV(e){let{inputs:t,backend:n}=e,{input:r}=t;return z_(r,!0,n)}var aV={kernelName:Eh,backendName:"webgl",kernelFunc:rV},sV="return float(!isnan(x) && !isinf(x));",iV=Je({opSnippet:sV,dtype:"bool"}),oV={kernelName:io,backendName:"webgl",kernelFunc:iV},lV="return float(isinf(x));",uV=Je({opSnippet:lV,dtype:"bool"}),cV={kernelName:oo,backendName:"webgl",kernelFunc:uV},hV="return float(isnan(x));",dV=Je({opSnippet:hV,dtype:"bool"}),pV={kernelName:lo,backendName:"webgl",kernelFunc:dV},fV="return float(a < b);",mV=`
return vec4(lessThan(a, b));
`,AV=Zt({opSnippet:fV,packedOpSnippet:mV,cpuKernelImpl:bz,dtype:"bool"}),yV={kernelName:uo,backendName:"webgl",kernelFunc:AV},gV="return float(a <= b);",xV=`
return vec4(lessThanEqual(a, b));
`,wV=Zt({opSnippet:gV,packedOpSnippet:xV,dtype:"bool"}),_V={kernelName:co,backendName:"webgl",kernelFunc:wV};function bV(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=vz(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var vV={kernelName:Rh,backendName:"webgl",kernelFunc:bV},kV=`if (x < 0.0) return NAN;
return log(x);`,IV=`
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;
`,NV=Je({opSnippet:kV,packedOpSnippet:IV,cpuKernelImpl:kz}),SV={kernelName:ds,backendName:"webgl",kernelFunc:NV},TV="return log(1.0 + x);",EV=Je({opSnippet:TV}),CV={kernelName:ho,backendName:"webgl",kernelFunc:EV},RV="return float(a >= 1.0 && b >= 1.0);",FV=`
return vec4(
vec4(greaterThanEqual(a, vec4(1.0))) *
vec4(greaterThanEqual(b, vec4(1.0))));
`,MV=Zt({opSnippet:RV,packedOpSnippet:FV,dtype:"bool"}),$V={kernelName:po,backendName:"webgl",kernelFunc:MV},DV="return float(!(x >= 1.0));",OV=Je({opSnippet:DV}),zV={kernelName:du,backendName:"webgl",kernelFunc:OV},PV="return float(a >= 1.0 || b >= 1.0);",LV=`
return min(
vec4(greaterThanEqual(a, vec4(1.0))) +
vec4(greaterThanEqual(b, vec4(1.0))),
vec4(1.0));
`,WV=Zt({opSnippet:PV,packedOpSnippet:LV,dtype:"bool"}),BV={kernelName:pu,backendName:"webgl",kernelFunc:WV},VV=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 * ${o};
setOutput(val);
}
`}},UV=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${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);
}
`}},HV=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r,c=Q().getBool("WEBGL_PACK_NORMALIZATION")?new UV(a.shape,s,i,o,l):new VV(a.shape,s,i,o,l);return n.runWebGLProgram(c,[a],a.dtype)},jV={kernelName:fu,backendName:"webgl",kernelFunc:HV},GV=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);
}
`}},qV=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:c,beta:u}=r,h=new GV(a.shape,o,l,c,u);return n.runWebGLProgram(h,[a,s,i],a.dtype)},XV={kernelName:Fh,backendName:"webgl",kernelFunc:qV};function KV(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=ge({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=ui(i,e.dtype,"max",r),l=ge({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}function L_(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),c=l,u=C.getAxesPermutation(c,o),h=u!=null,d=n.shouldExecuteOnCPU([a]),p=a;if(h){if(d){let g=n.texData.get(p.dataId).values,w=new Array(o);for(let I=0;I<w.length;I++)w[I]=a.shape[u[I]];let x=CA(g,a.shape,a.dtype,u,w);p=n.makeTensorInfo(w,a.dtype);let _=n.texData.get(p.dataId);_.values=x}else p=sp(a,u,n);c=C.getInnerMostAxes(c.length,o)}C.assertAxesAreInnerMostDims("max",c,o);let[f,m]=C.computeOutAndReduceShapes(p.shape,c),A=f;i&&(A=C.expandShapeToKeepDim(f,l));let y;if(d){let g=n.texData.get(p.dataId).values,w=Iz(g,v.sizeFromShape(m),A,a.dtype);y=n.makeTensorInfo(A,a.dtype);let x=n.texData.get(y.dataId);x.values=w}else y=KV(p,m,A,n);return h&&n.disposeIntermediateTensorInfo(p),y}var ZV={kernelName:ps,backendName:"webgl",kernelFunc:L_},JV=n_+`
return max(a, b);
`,YV=`
vec4 result = vec4(max(a, b));
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+rp+`
return result;
`,QV=Zt({opSnippet:JV,packedOpSnippet:YV,cpuKernelImpl:Nz}),eU={kernelName:fs,backendName:"webgl",kernelFunc:QV};function tU(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,c=1;v.assert(C.eitherStridesOrDilationsAreOne(i,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=C.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return En({inputs:{x:a},backend:n});let h=new hc(u,"max",!1);return n.runWebGLProgram(h,[a],a.dtype)}var nU={kernelName:ms,backendName:"webgl",kernelFunc:tU};function rU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:c}=r,u=[1,1,1],h=C.computePool3DInfo(a.shape,s,i,u,o,c,l),d=new MA(h,"max",!1);return n.runWebGLProgram(d,[a],a.dtype)}var aU={kernelName:mu,backendName:"webgl",kernelFunc:rU},sU=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 * ${s} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
setOutput(dotProd);
}
`}},iU=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,c=e.effectiveFilterWidth,u=o-1-e.padInfo.front,h=l-1-e.padInfo.top,d=c-1-e.padInfo.left,p=o*l*c-1;this.userCode=`
const ivec3 pads = ivec3(${u}, ${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 < ${c};
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} * ${c} +
wR * ${c} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
}
setOutput(dotProd);
}
`}};function oU(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:c,dimRoundingMode:u}=r,h=[1,1,1],d=C.computePool3DInfo(i.shape,o,l,h,c,u),p=new MA(d,"max",!0),f=n.runWebGLProgram(p,[i],i.dtype),m=new iU(d),A=n.runWebGLProgram(m,[a,f],i.dtype);return n.disposeIntermediateTensorInfo(f),A}var lU={kernelName:$h,backendName:"webgl",kernelFunc:oU};function uU(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:c,pad:u,dimRoundingMode:h}=r,d=C.computePool2DInfo(o.shape,l,c,1,u,h),p=!0,f=new hc(d,"max",p),m=n.runWebGLProgram(f,[o],o.dtype),A=new sU(d),y=n.runWebGLProgram(A,[a,m],o.dtype);return n.disposeIntermediateTensorInfo(m),y}var cU={kernelName:Mh,backendName:"webgl",kernelFunc:uU};function hU(e,t,n,r){let a=new hc(n,"max",!1),s=r.runWebGLProgram(a,[e],"float32");a=new hc(n,"max",!0,!0,t);let i=r.runWebGLProgram(a,[e],"float32");return[s,i]}var dU={kernelName:Dh,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 c=[1,1];v.assert(C.eitherStridesOrDilationsAreOne(s,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${c}'`);let u=C.computePool2DInfo(r.shape,a,s,c,i),[h,d]=hU(r,o,u,l);return[h,d]}};function pU(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=ge({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=ui(i,"float32","mean",r),l=ge({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}var fU={kernelName:As,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),c=l,u=C.getAxesPermutation(c,o),h=u!=null,d=i.shouldExecuteOnCPU([r]),p=[],f=r;if(h){if(d){let w=i.texData.get(f.dataId).values,x=new Array(o);for(let T=0;T<x.length;T++)x[T]=r.shape[u[T]];let _=CA(w,r.shape,r.dtype,u,x);f=i.makeTensorInfo(x,r.dtype);let I=i.texData.get(f.dataId);I.values=_}else f=sp(r,u,i);p.push(f),c=C.getInnerMostAxes(c.length,o)}C.assertAxesAreInnerMostDims("sum",c,o);let[m,A]=C.computeOutAndReduceShapes(f.shape,c),y=m;a&&(y=C.expandShapeToKeepDim(m,l));let g=pU(f,A,y,i);for(let w of p)i.disposeIntermediateTensorInfo(w);return g}};function mU(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),c=l,u=C.getAxesPermutation(c,o),h=a;u!=null&&(h=mn({inputs:{x:a},backend:n,attrs:{perm:u}}),c=C.getInnerMostAxes(c.length,a.shape.length)),C.assertAxesAreInnerMostDims("min",c,o);let[d,p]=C.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=ge({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=ui(m,m.dtype,"min",n),y;if(i){let g=C.expandShapeToKeepDim(d,l);y=ge({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ge({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var AU={kernelName:ys,backendName:"webgl",kernelFunc:mU},yU=n_+`
return min(a, b);
`,gU=`
vec4 result = vec4(min(a, b));
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+rp+`
return result;
`,xU=Zt({opSnippet:yU,packedOpSnippet:gU,cpuKernelImpl:Sz}),wU={kernelName:gs,backendName:"webgl",kernelFunc:xU},_U=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((c,u)=>c[0]+e[u]+c[1]);let r=e.length,a=ht(r),s=t.map(c=>c[0]).join(","),i=t.map((c,u)=>c[0]+e[u]).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}));
}
`}},bU=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=ht(r),s=t.map(p=>p[0]).join(","),i=t.map((p,f)=>p[0]+e[f]).join(","),o=ln("rc",r),l=ln("source",r),c=`${o[r-1]} < ${this.outputShape[r-1]}`,u=r===1?"source":`vec2(${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()}), ${u});
${o[r-1]} += 1;
if(${c}) {
${p}
result[1] = getChannel(getX(${l.join()}), ${u});
}
`}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()}), ${u});
${o[r-1]} += 1;
if(${c}) {
${p}
result[1] = getChannel(getX(${l.join()}), ${u});
}
rc = outputLoc;
${o[r-2]} += 1;
if(${o[r-2]} < ${this.outputShape[r-2]}) {
${p}
result[2] = getChannel(getX(${l.join()}), ${u});
${o[r-1]} += 1;
if(${c}) {
${p}
result[3] = getChannel(getX(${l.join()}), ${u});
}
}
`}this.userCode=`
const ${a} start = ${a}(${s});
const ${a} end = ${a}(${i});
void main() {
${a} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${d}
setOutput(result);
}
`}},vU=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{paddings:a,mode:s}=n,i=Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new bU(r.shape,a,s):new _U(r.shape,a,s);return t.runWebGLProgram(i,[r],r.dtype)},kU={kernelName:Au,backendName:"webgl",kernelFunc:vU},IU=`if (b == 0.0) return NAN;
return mod(a, b);`,NU=`
vec4 result = mod(a, b);
vec4 isNaN = vec4(equal(b, vec4(0.0)));
`+rp+`
return result;
`,SU=Zt({opSnippet:IU,packedOpSnippet:NU}),TU={kernelName:fo,backendName:"webgl",kernelFunc:SU},EU=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)}}},CU=`
if (a == b) {
return 1.0;
};
return a / b;`,RU=`
// 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;
`,W_=Zt({opSnippet:CU,packedOpSnippet:RU,checkOutOfBounds:!0}),FU={kernelName:ss,backendName:"webgl",kernelFunc:W_},B_="return a - b;",V_=Zt({opSnippet:B_,packedOpSnippet:B_,supportsComplex:!0,cpuKernelImpl:Dz}),MU={kernelName:Os,backendName:"webgl",kernelFunc:V_};function U_(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{dim:s}=r,i=v.parseAxisParam([s],a.shape),o=L_({inputs:{x:a},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=C.expandShapeToKeepDim(o.shape,i),c=ge({inputs:{x:o},backend:n,attrs:{shape:l}}),u=V_({inputs:{a,b:c},backend:n}),h=$_({inputs:{x:u},backend:n}),d=FA({inputs:{x:h},backend:n,attrs:{axis:i,keepDims:!1}}),p=ge({inputs:{x:d},backend:n,attrs:{shape:l}}),f=W_({inputs:{a:h,b:p},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}var $U={kernelName:$s,backendName:"webgl",kernelFunc:U_};function DU(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r,l=o?a:U_({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),c=l.shape[0],u=l.shape[1],h=new EU(c,u,s),d=h.getCustomSetupFunc(i),p=n.runWebGLProgram(h,[l],"int32",d);return o||n.disposeIntermediateTensorInfo(l),p}var OU={kernelName:Oh,backendName:"webgl",kernelFunc:DU},H_="return -x;";function zU(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){let s=n.texData.get(r.dataId),[i,o]=Ez(s.values,r.shape,r.dtype);return n.makeTensorInfo(o,r.dtype,i)}let a;return Q().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new wl(r.shape,H_):a=new Ra(r.shape,H_),n.runWebGLProgram(a,[r],r.dtype)}var PU={kernelName:mo,backendName:"webgl",kernelFunc:zU},LU=Rr.nonMaxSuppressionV3Impl;function WU(e){C.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,c=n.readSync(a.dataId),u=n.readSync(s.dataId),{selectedIndices:h}=LU(c,u,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var BU={kernelName:yo,backendName:"webgl",kernelFunc:WU},VU=Rr.nonMaxSuppressionV4Impl;function UU(e){C.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:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),{selectedIndices:d,validOutputs:p}=VU(u,h,i,o,l,c);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var HU={kernelName:go,backendName:"webgl",kernelFunc:UU},jU=Rr.nonMaxSuppressionV5Impl;function GU(e){C.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:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),d=i,p=o,f=l,m=c,{selectedIndices:A,selectedScores:y}=jU(u,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var qU={kernelName:xo,backendName:"webgl",kernelFunc:GU},XU=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)));
}
`}},KU=e=>{let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=v.sizeFromShape(a.shape),c=new XU(l,s,i,o),u=ge({inputs:{x:a},backend:n,attrs:{shape:[l]}}),h=n.runWebGLProgram(c,[u],a.dtype);n.disposeIntermediateTensorInfo(u);let d=[...a.shape,s],p=ge({inputs:{x:h},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(h),p},ZU={kernelName:ws,backendName:"webgl",kernelFunc:KU};function cp(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="complex64"){let a=pc({inputs:{input:r},backend:n}),s=cp({inputs:{x:a},backend:n}),i=up({inputs:{input:r},backend:n}),o=cp({inputs:{x:i},backend:n}),l=Fa({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return zA({attrs:{shape:r.shape,dtype:r.dtype,value:r.dtype==="string"?"":0},backend:n})}var JU={kernelName:zo,backendName:"webgl",kernelFunc:cp};function j_(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=pc({inputs:{input:r},backend:n}),s=j_({inputs:{x:a},backend:n}),i=up({inputs:{input:r},backend:n}),o=cp({inputs:{x:i},backend:n}),l=Fa({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return zA({attrs:{shape:r.shape,dtype:r.dtype,value:1},backend:n})}var YU={kernelName:wo,backendName:"webgl",kernelFunc:j_};function QU(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return OA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(u=>{v.assertShapesMatch(s,u.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===u.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(u=>{let h=OA({inputs:{input:u},backend:n,attrs:{dim:a}});return o.push(h),h}),c=k_({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(u=>n.disposeIntermediateTensorInfo(u)),c}var eH={kernelName:_o,backendName:"webgl",kernelFunc:QU},tH=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((l,c)=>l[0]+e[c]+l[1]);let r=e.length,a=ht(r),s=t.map(l=>l[0]).join(","),i=t.map((l,c)=>l[0]+e[c]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);if(r===1){this.userCode=`
int start = ${s};
int end = ${i};
void main() {
int outC = getOutputCoords();
if (outC < start || outC >= end) {
setOutput(float(${n}));
} else {
setOutput(getX(outC - start));
}
}
`;return}this.userCode=`
${a} start = ${a}(${s});
${a} end = ${a}(${i});
void main() {
${a} outC = getOutputCoords();
if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
setOutput(float(${n}));
} else {
${a} coords = outC - start;
setOutput(getX(${o}));
}
}
`}},nH=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=ht(r),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=ln("rc",r),l=ln("source",r),c=`${o[r-1]} < ${this.outputShape[r-1]}`,u=r===1?"source":`vec2(${l.slice(-2).join()})`,h=[`${a} rc = outputLoc;`,`${o[r-1]} += 1;
if(${c}) {
`,r===1?"":`}
rc = outputLoc;
${o[r-2]} += 1;
if(${o[r-2]} < ${this.outputShape[r-2]}) {`,r===1?"":` ${o[r-1]} += 1;
if(${c}) {`],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[${f}] = float(${n});
} else {
${a} source = rc - start;
result[${f}] = getChannel(getX(${l.join()}), ${u});
}
`;p+=r===1?"} ":"}}",this.userCode=`
const ${a} start = ${a}(${s});
const ${a} end = ${a}(${i});
void main() {
${a} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${p}
setOutput(result);
}
`}},G_=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r,o=Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new nH(a.shape,s,i):new tH(a.shape,s,i);return n.runWebGLProgram(o,[a],a.dtype)},rH={kernelName:_s,backendName:"webgl",kernelFunc:G_},aH=`
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);
`,sH=`
// 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));
`+rp+`
return result;
`,iH=Zt({opSnippet:aH,packedOpSnippet:sH}),oH={kernelName:bs,backendName:"webgl",kernelFunc:iH};function lH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=[],c=v.parseAxisParam(s,a.shape),u=c,h=C.getAxesPermutation(u,o),d=a;h!=null&&(d=mn({inputs:{x:a},backend:n,attrs:{perm:h}}),u=C.getInnerMostAxes(u.length,o),l.push(d)),C.assertAxesAreInnerMostDims("prod",u,o);let p;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:A,outDtype:y}=Cz(d.shape,d.dtype,f,u);p=n.makeTensorInfo(A,y,m)}else{let[f,m]=C.computeOutAndReduceShapes(d.shape,u),A=v.sizeFromShape(m),y=ge({inputs:{x:d},backend:n,attrs:{shape:[-1,A]}}),g=Hh(a.dtype),w=ui(y,g,"prod",n);p=ge({inputs:{x:w},backend:n,attrs:{shape:f}}),l.push(y),l.push(w)}if(i){l.push(p);let f=C.expandShapeToKeepDim(p.shape,c);p=ge({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var uH={kernelName:bo,backendName:"webgl",kernelFunc:lH},q_=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=Rz(r,a,s,i);return t.makeTensorInfo([o.length],i,o)},cH={kernelName:yu,backendName:"webgl",kernelFunc:q_},hH="return 1.0 / x;",dH=Je({opSnippet:hH}),pH={kernelName:vo,backendName:"webgl",kernelFunc:dH},fH=Ar+`
return (x < 0.0) ? 0.0 : x;
`,mH=`
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;
`,AH=Je({opSnippet:fH,packedOpSnippet:mH}),yH={kernelName:ks,backendName:"webgl",kernelFunc:AH},gH=Ar+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,xH=`
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;
`,wH=Je({opSnippet:gH,packedOpSnippet:xH}),_H={kernelName:Ns,backendName:"webgl",kernelFunc:wH},bH=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 c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[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(
${c[0]/u[0]},
${c[1]/u[1]});
const vec2 inputShapeRC = vec2(${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);
}
`}},vH=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 c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[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(
${c[0]/u[0]},
${c[1]/u[1]},
${c[1]/u[1]});
const vec3 inputShapeRC = vec3(${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 kH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=Q().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new vH(a.shape,l,c,s,i):new bH(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],"float32")}var IH={kernelName:Is,backendName:"webgl",kernelFunc:kH},NH=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],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,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(${c});
const float widthScale = float(${u});
const float invHeightScale = float(${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 SH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new NH(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var TH={kernelName:Lh,backendName:"webgl",kernelFunc:SH},EH=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 c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[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(
${c[0]/u[0]},
${c[1]/u[1]});
const vec2 inputShapeRC = vec2(${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 + ${h})));
float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);
setOutput(newValue);
}
`}};function CH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=new EH(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],a.dtype)}var RH={kernelName:gu,backendName:"webgl",kernelFunc:CH},FH=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
int r = coords[1];
int c = coords[2];
float accumulator = 0.0;
const float heightScale = float(${c});
const float widthScale = float(${u});
const float invHeightScale = float(${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 MH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new FH(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var $H={kernelName:Ph,backendName:"webgl",kernelFunc:MH},DH=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${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=ht(n);this.userCode=`
void main() {
${s} coords = getOutputCoords();
setOutput(getX(${a}));
}
`}},OH=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-${n} tensor is not yet supported`);this.outputShape=e;let r=ln("rc",n),a=`${r[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${r[n-2]} + 1 < ${this.outputShape[n-2]}`,i=ht(n);n===1?this.userCode=`
void main(){
int rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = getChannel(getX(${e[0]} - rc - 1),
${e[0]} - rc - 1);
if(${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 = ${c(r.slice())};
if(${a}) {
result.a = ${u(r.slice())};
}
}
setOutput(result);
}
`;function o(p){return h(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",h(p)}function c(p){return p[n-2]="("+p[n-2]+" + 1)",h(p)}function u(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",h(p)}function h(p){let f=e.map((y,g)=>d(g,p)),m=f.join(","),A=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${A}))`}function d(p,f){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${f[p]} - 1`:`${f[p]}`}}};function zH(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 En({inputs:{x:a},backend:n});let l=Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new OH(a.shape,o):new DH(a.shape,o);return n.runWebGLProgram(l,[a],a.dtype)}var PH={kernelName:Ss,backendName:"webgl",kernelFunc:zH},LH=class{constructor(e,t,n,r){this.variableNames=["Image"],this.outputShape=[];let a=e[1],s=e[2],i=Math.sin(t).toFixed(3),o=Math.cos(t).toFixed(3);this.outputShape=e;let[l,c]=C.getImageCenter(r,a,s),u=l.toFixed(3),h=c.toFixed(3),d="";typeof n=="number"?d=`float outputValue = ${n.toFixed(2)};`:d=`
vec3 fill = vec3(${n.join(",")});
float outputValue = fill[coords[3]];`,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int x = coords[2];
int y = coords[1];
float coordXFloat = (float(x) - ${u}) * ${o} - (float(y) - ${h}) * ${i};
float coordYFloat = (float(x) - ${u}) * ${i} + (float(y) - ${h}) * ${o};
int coordX = int(round(coordXFloat + ${u}));
int coordY = int(round(coordYFloat + ${h}));
${d}
if(coordX >= 0 && coordX < ${s} && coordY >= 0 && coordY < ${a}) {
outputValue = getImage(coords[0], coordY, coordX, coords[3]);
}
setOutput(outputValue);
}
`}},WH={kernelName:Po,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,{radians:a,fillValue:s,center:i}=t,o=n,l=new LH(r.shape,a,s,i);return o.runWebGLProgram(l,[r],r.dtype)}},BH=`
// OpenGL ES does not support round function.
// The algorithm is based on banker's rounding.
float base = floor(x);
if ((x - base) < 0.5) {
return floor(x);
} else if ((x - base) > 0.5) {
return ceil(x);
} else {
if (mod(base, 2.0) == 0.0) {
return base;
} else {
return base + 1.0;
}
}
`,VH=Je({opSnippet:BH}),UH={kernelName:Ts,backendName:"webgl",kernelFunc:VH},HH="return inversesqrt(x);",jH=Je({opSnippet:HH,cpuKernelImpl:Fz}),GH={kernelName:Es,backendName:"webgl",kernelFunc:jH},X_=class{constructor(e,t,n,r,a,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=ht(a.length),l=ht(s.length),c="";n===1?c="i":n===2&&(c="i, j");let u=`getIndices(${c})`,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 < ${t}; j++) {
int index = round(${u});
flattenedIndex += index * ${p};
}
if (flattenedIndex == coords[0]) {
sum += ${d};
found = true;
}
}
setOutput(mix(getDefaultValue(), sum, float(found)));
}
`}};function qH(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a,updates:s}=t,{shape:i}=r,{sliceRank:o,numUpdates:l,sliceSize:c,strides:u,outputSize:h}=C.calculateShapes(s,a,i),d=[h/c,c];if(h===0)return n.makeTensorInfo(i,a.dtype);let p=ge({inputs:{x:a},backend:n,attrs:{shape:[l,o]}}),f=ge({inputs:{x:s},backend:n,attrs:{shape:[l,c]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),A=new X_(l,o,p.shape.length,f.shape.length,u,d),y=n.runWebGLProgram(A,[f,p,m],f.dtype),g=ge({inputs:{x:y},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),g}var XH={kernelName:Io,backendName:"webgl",kernelFunc:qH},KH=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let r,a;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)a="resRC",r="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let c=0;c<t.length;c++)l.push(`${i[c]}`),c<e&&o.push(`${i[c]}`);r=o.join(),a=l.join()}let s=ht(n);this.userCode=`
void main() {
${s} resRC = getOutputCoords();
float cVal = getC(${r});
if (cVal >= 1.0) {
setOutput(getA(${a}));
} else {
setOutput(getB(${a}));
}
}
`}};function ZH(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t,i=new KH(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(i,[r,a,s],Qn(a.dtype,s.dtype))}var JH={kernelName:No,backendName:"webgl",kernelFunc:ZH},YH=`
// Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
// see: https://arxiv.org/abs/1706.02515
float scaleAlpha = ${C.SELU_SCALEALPHA};
float scale = ${C.SELU_SCALE};
return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,QH=Je({opSnippet:YH}),ej={kernelName:So,backendName:"webgl",kernelFunc:QH},tj="return 1.0 / (1.0 + exp(-1.0 * x));",nj=Je({opSnippet:tj}),rj={kernelName:Rs,backendName:"webgl",kernelFunc:nj},aj=`
if (isnan(x)) { return 0.0; }
return sign(x);
`,sj=Je({opSnippet:aj}),ij={kernelName:Co,backendName:"webgl",kernelFunc:sj},oj=o_+`
return sin(x);
`,lj=Je({opSnippet:oj}),uj={kernelName:Cs,backendName:"webgl",kernelFunc:lj},cj=`
float e2x = exp(x);
return (e2x - 1.0 / e2x) / 2.0;
`,hj=Je({opSnippet:cj}),dj={kernelName:Eo,backendName:"webgl",kernelFunc:hj},pj=`
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;
`,fj=Je({opSnippet:pj}),mj={kernelName:Ro,backendName:"webgl",kernelFunc:fj},Aj=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 c=[],u=G_({inputs:{x:a},backend:n,attrs:{paddings:l,constantValue:0}}),h=C.getReshaped(u.shape,s,o,!1),d=C.getPermuted(h.length,s.length,!1),p=C.getReshapedPermuted(u.shape,s,o,!1),f=ge({inputs:{x:u},backend:n,attrs:{shape:h}}),m=mn({inputs:{x:f},backend:n,attrs:{perm:d}}),A=ge({inputs:{x:m},backend:n,attrs:{shape:p}});return c.push(u),c.push(f),c.push(m),c.forEach(y=>n.disposeIntermediateTensorInfo(y)),A},yj={kernelName:xu,backendName:"webgl",kernelFunc:Aj};function gj(e){let{inputs:t,backend:n,attrs:r}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=r,{sliceRank:l,numUpdates:c,strides:u,outputSize:h}=C.calculateShapes(s,a,o),d=!1,p=new X_(c,l,a.shape.length,s.shape.length,u,[h,1],d),f=n.runWebGLProgram(p,[s,a,i],s.dtype),m=ge({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(f),m}var xj={kernelName:Wh,backendName:"webgl",kernelFunc:gj};function wj(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=C.prepareSplitSize(a,s,o),c=a.shape.length,u=new Array(c).fill(0),h=a.shape.slice();return l.map(d=>{let p=[...h];p[o]=d;let f=dc({inputs:{x:a},backend:n,attrs:{begin:u,size:p}});return u[o]+=d,f})}var _j={kernelName:Fo,backendName:"webgl",kernelFunc:wj},bj="return sqrt(x);",vj=Je({opSnippet:bj}),kj={kernelName:Fs,backendName:"webgl",kernelFunc:vj},Ij="return x * x;",Nj=Je({opSnippet:Ij}),Sj={kernelName:wu,backendName:"webgl",kernelFunc:Nj},K_="return (a - b) * (a - b);",Tj=Zt({opSnippet:K_,packedOpSnippet:K_}),Ej={kernelName:Ds,backendName:"webgl",kernelFunc:Tj};function Cj({inputs:e,attrs:t,backend:n}){let{x:r}=e,a=Ar+`
return x > 0.0 ? 1.0 : float(${t.alpha});
`,s=new Ra(r.shape,a);return n.runWebGLProgram(s,[r],r.dtype)}var Rj={kernelName:ya,backendName:"webgl",kernelFunc:Cj},Fj=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let r=n.length,a=ht(n.length),s=ht(n.length),i="";if(r===1)i="coords * strides + begin";else{let o=0;i=n.map((l,c)=>(o++,n.length===1?`coords * strides[${c}] + begin[${c}]`:`coords[${o-1}] * strides[${c}] + begin[${c}]`)).join(",")}this.userCode=`
${a} begin = ${a}(${e});
${a} strides = ${a}(${t});
void main() {
${s} coords = getOutputCoords();
setOutput(getX(${i}));
}
`}};function Mj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:c,ellipsisMask:u,newAxisMask:h,shrinkAxisMask:d}=r,{nonStrided:p,$begin:f,$strides:m,size:A,newShape:y,outShape:g}=rn.sliceInfo(a.shape,s,i,o,l,c,u,h,d),w=ge({inputs:{x:a},backend:n,attrs:{shape:y}}),x;if(p){let I=dc({inputs:{x:w},backend:n,attrs:{begin:f,size:A}});x=ge({inputs:{x:I},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(I)}else if(g.some(I=>I===0))x=n.makeTensorInfo(g,a.dtype,[]);else if(n.shouldExecuteOnCPU([w])){let I=n.texData.get(w.dataId).values,T=We(w.shape,w.dtype,I),E=$z(g,T,m,f);x=n.makeTensorInfo(g,w.dtype,E.values)}else{let I=new Fj(f,m,g);x=n.runWebGLProgram(I,[w],w.dtype)}let _=ge({inputs:{x},backend:n,attrs:{shape:g}});return n.disposeIntermediateTensorInfo(w),n.disposeIntermediateTensorInfo(x),_}var $j={kernelName:Mo,backendName:"webgl",kernelFunc:Mj},Dj="return tan(x);",Oj=Je({opSnippet:Dj}),zj={kernelName:$o,backendName:"webgl",kernelFunc:Oj},Pj=`
float e2x = exp(-2.0 * abs(x));
return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,Lj=Je({opSnippet:Pj}),Wj={kernelName:zs,backendName:"webgl",kernelFunc:Lj},Vj=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=ht(this.rank),a=Bj(e);this.userCode=`
void main() {
${r} resRC = getOutputCoords();
setOutput(getA(${a}));
}
`}};function Bj(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 Z_(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(u=>v.decodeString(u)),l=We(a.shape,a.dtype,o),c=Oz(l,s);return n.makeTensorInfo(c.shape,c.dtype,c.values)}let i=new Vj(a.shape,s);return n.runWebGLProgram(i,[a],a.dtype)}var Uj={kernelName:Aa,backendName:"webgl",kernelFunc:Z_};function Hj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{k:s,sorted:i}=r,o=n.readSync(a.dataId),[l,c]=zz(o,a.shape,a.dtype,s,i);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(c.shape,c.dtype,c.values)]}var jj={kernelName:Do,backendName:"webgl",kernelFunc:Hj};function Gj(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:c}=Pz(i,a,s.shape,s.dtype);return[r.makeTensorInfo(l,s.dtype,o),r.makeTensorInfo([c.length],"int32",c)]}var qj={kernelName:Bh,backendName:"webgl",kernelFunc:Gj};function Xj(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],c=new Array(o-1),u=0;for(let m=0;m<o;m++)m!==s&&(c[u++]=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=dc({inputs:{x:i},backend:n,attrs:{begin:d,size:p}}),y=ge({inputs:{x:A},backend:n,attrs:{shape:c}});f[m]=y,h.push(A)}return h.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var Kj={kernelName:Oo,backendName:"webgl",kernelFunc:Xj},Zj=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",c=Math.floor(n/4)*4,u=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 < ${c}; 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 + ${c};
if (${u===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
);
${h}
} else if (${u===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
);
${h}
} else if (${u===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 Jj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,segmentIds:s}=t,{numSegments:i}=r,o=a.shape.length,l=[],c=0,u=C.getAxesPermutation([c],o),h=a;u!=null&&(h=mn({inputs:{x:a},backend:n,attrs:{perm:u}}),l.push(h),c=C.getInnerMostAxes(1,o)[0]);let d=C.segment_util.computeOutShape(h.shape,c,i),p=v.sizeFromShape([h.shape[c]]),f=ge({inputs:{x:h},backend:n,attrs:{shape:[-1,p]}});l.push(f);let m=Hh(a.dtype),A=(x,_,I,T,E)=>{let N=x.shape[0],F=x.shape[1],$=C.segment_util.segOpComputeOptimalWindowSize(F,E),D={windowSize:$,inSize:F,batchSize:N,numSegments:E},P=new Zj(D,_),H=n.compileAndRun(P,[x,I],T);if(l.push(H),H.shape[1]===E)return H;let V=q_({backend:n,attrs:{start:0,stop:E,step:1,dtype:"float32"}}),K=Z_({inputs:{x:V},backend:n,attrs:{reps:[F/$]}});return l.push(V),l.push(K),A(H,_,K,T,E)},y=A(f,"unsortedSegmentSum",s,m,i),g=ge({inputs:{x:y},backend:n,attrs:{shape:d}}),w=g;if(u!=null){l.push(g);let x=C.getUndoAxesPermutation(u);w=mn({inputs:{x:w},backend:n,attrs:{perm:x}})}return l.forEach(x=>n.disposeIntermediateTensorInfo(x)),w}var Yj={kernelName:_u,backendName:"webgl",kernelFunc:Jj},Qj=[jV,XV,MP,DP,PP,BP,UP,GP,XP,ZP,eL,nL,sL,lL,mL,hL,gL,bL,wL,NL,TL,CL,$L,BL,UL,KL,JL,tW,aW,fP,lW,gW,wW,dW,kW,NW,bW,EW,FW,DW,zW,LW,VW,XW,ZW,HW,QW,nB,iB,cB,fB,yB,gB,xB,_B,vB,IB,SB,EB,MB,zB,LB,BB,HB,XB,YB,nV,pP,aV,oW,oV,cV,pV,AP,yV,_V,vV,CV,SV,$V,zV,BV,ZV,aU,nU,lU,cU,dU,eU,fU,AU,wU,kU,TU,OU,_P,PU,BU,HU,qU,jL,ZU,YU,eH,rH,oH,gP,uH,cH,GL,FU,pH,_H,yH,vP,IH,TH,RH,$H,PH,WH,UH,GH,XH,JH,ej,rj,ij,uj,dj,LL,$U,mj,yj,xj,_j,kj,Sj,Ej,Rj,$j,MU,CP,zj,Wj,Uj,jj,RP,qj,Kj,Yj,JU];for(let e of Qj)Lo(e);var Cn;(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"})(Cn||(Cn={}));var fc;(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"})(fc||(fc={}));var J_;function eG(e){J_=e.wasm.cwrap(Ls,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function tG(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:c,activation:u,leakyreluAlpha:h}=r,d=n.dataIdMap.get(a.dataId).id,p=n.dataIdMap.get(s.dataId).id,f=0;if(i!=null){let E=n.dataIdMap.get(i.dataId);if(E.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${E.shape.length}.`);f=E.id}let m=o==null?0:n.dataIdMap.get(o.dataId).id,A=fc[u];if(A==null)throw new Error(`${u} activation not yet supported for FusedConv2D in the wasm backend.`);let y=l?a.shape[2]:a.shape[1],g=c?s.shape[1]:s.shape[2],w=a.shape[0],x=n.makeOutput([w,y,g],a.dtype),_=n.dataIdMap.get(x.dataId).id,I=new Uint8Array(new Int32Array(a.shape).buffer),T=new Uint8Array(new Int32Array(s.shape).buffer);return J_(d,I,a.shape.length,p,T,s.shape.length,l,c,A,f,m,h||0,_),x}var nG={kernelName:Ls,backendName:"wasm",setupFunc:eG,kernelFunc:tG};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),c=s.dataIdMap.get(l.dataId).id;return v.sizeFromShape(l.shape)===0||t(o,c),l}return{kernelName:e,backendName:"wasm",setupFunc:n,kernelFunc:r}}var rG=Rn(zi);function un(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:c,b:u}=l,h=o.dataIdMap.get(c.dataId).id,d=o.dataIdMap.get(u.dataId).id,p=n!=null?n:c.dtype,f=C.assertAndGetBroadcastShape(c.shape,u.shape),m=o.makeOutput(f,p);if(v.sizeFromShape(f)===0)return m;let A=new Uint8Array(new Int32Array(c.shape).buffer),y=new Uint8Array(new Int32Array(u.shape).buffer),g=o.dataIdMap.get(m.dataId).id,w=()=>r(h,A,c.shape.length,d,y,u.shape.length,Cn[c.dtype],g);if(t&&c.dtype==="float32")return w(),m;let x=C.getBroadcastDims(c.shape,f),_=C.getBroadcastDims(u.shape,f),I=x.every((E,N)=>E===N),T=_.every((E,N)=>E===N);if(I&&T)return w(),m;throw new Error(`Broadcasting along outer dims is not yet supported for ${c.dtype} ${e}.`)}return{kernelName:e,backendName:"wasm",setupFunc:a,kernelFunc:s}}var aG=!0,sG=un(fa,aG),Y_;function iG(e){Y_=e.wasm.cwrap(Ka,null,["array","number","number","number"])}function oG(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 Y_(s,a.length,Cn[r.dtype],i),r}var lG={kernelName:Ka,backendName:"wasm",setupFunc:iG,kernelFunc:oG};function hp(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 uG={kernelName:so,backendName:"wasm",kernelFunc:hp},Q_;function cG(e){Q_=e.wasm.cwrap(Ps,null,["number","array","number","number","number","array","number"])}function dp(e){let{inputs:t,backend:n,attrs:r}=e,[a,s]=dG(t.x.shape,r.perm),i=!0;for(let f=0;f<s.length;f++)s[f]!==f&&(i=!1);let o=hG(t.x.shape,r.perm),l={dataId:t.x.dataId,shape:a,dtype:t.x.dtype};if(i){let f=hp({inputs:t,backend:n});return f.shape=o,f}let c=n.makeOutput(o,l.dtype),u=n.dataIdMap.get(l.dataId).id,h=n.dataIdMap.get(c.dataId).id,d=new Uint8Array(new Int32Array(s).buffer),p=new Uint8Array(new Int32Array(l.shape).buffer);return Q_(u,p,l.shape.length,Cn[l.dtype],h,d,s.length),c}function hG(e,t){let n=new Array(e.length);for(let r=0;r<n.length;r++)n[r]=e[t[r]];return n}function dG(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 pG={kernelName:Ps,backendName:"wasm",kernelFunc:dp,setupFunc:cG};function kl(e,t,n){let r=e.shape,a=e.shape.length,s=v.parseAxisParam(t,r),i=s,o=C.getAxesPermutation(i,a),l=null,c=!1;if(o!=null){let u=new Array(a);for(let d=0;d<u.length;d++)u[d]=r[o[d]];i=C.getInnerMostAxes(i.length,a),l=dp({inputs:{x:e},attrs:{perm:o},backend:n});let h=n.dataIdMap.get(e.dataId).id;n.dataIdMap.get(l.dataId).id!==h&&(c=!0)}return{transposed:l,originalAxes:s,axes:i,inputWasTransposed:c}}var eb;function fG(e){eb=e.wasm.cwrap(Za,null,["number","number","number","number","number"])}function mG(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:c,axes:u,inputWasTransposed:h}=kl(s,a,t);if(h){let y=t.dataIdMap.get(c.dataId).id;y!==i&&(l=c,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[u[0]];return eb(o,Cn[l.dtype],m,A,f),h&&t.disposeData(c.dataId),p}var AG={kernelName:Za,backendName:"wasm",kernelFunc:mG,setupFunc:fG},tb;function yG(e){tb=e.wasm.cwrap(Ja,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function gG(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:c}=n,u=C.computePool2DInfo(a.shape,i,o,1,l,c),h=u.filterHeight,d=u.filterWidth,p=u.padInfo.top,f=u.padInfo.right,m=u.padInfo.bottom,A=u.padInfo.left,y=u.strideHeight,g=u.strideWidth,w=u.inChannels;if(u.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${u.dataFormat}'. Please use 'channelsLast'.`);if(u.dilationWidth!==1||u.dilationHeight!==1)throw new Error(`was backend only supports average pooling with dilation = [1, 1], got [${u.dilationHeight}, ${u.dilationWidth}].`);let x=r.makeOutput(u.outShape,"float32"),_=r.dataIdMap.get(x.dataId).id;return tb(s,a.shape[0],a.shape[1],a.shape[2],h,d,p,f,m,A,y,g,w,_),x}var xG={kernelName:Ja,backendName:"wasm",setupFunc:yG,kernelFunc:gG};function yr(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: ${r.shape}. New shape and old shape must have the same number of elements.`),{dataId:r.dataId,shape:i,dtype:r.dtype}}var wG={kernelName:ko,backendName:"wasm",kernelFunc:yr},nb;function _G(e){nb=e.wasm.cwrap(Ya,null,["number","array","number","number","array","number","number","number","number"])}function bG(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;if(a.dtype!=="float32"||s.dtype!=="float32")throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");let l=a.shape.length,c=s.shape.length,u=i?a.shape[l-2]:a.shape[l-1],h=o?s.shape[c-1]:s.shape[c-2],d=i?a.shape[l-1]:a.shape[l-2],p=o?s.shape[c-2]:s.shape[c-1],f=a.shape.slice(0,-2),m=s.shape.slice(0,-2),A=v.sizeFromShape(f),y=v.sizeFromShape(m),g=A===y||A===1||y===1;v.assert(l>=2&&c>=2&&g,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${f}) and (${m}).`);let w=(A>y?a.shape.slice(0,-2):s.shape.slice(0,-2)).concat([d,p]);v.assert(u===h,()=>`Error in matMul: inner shapes (${u}) and (${h}) of Tensors with shapes ${a.shape} and ${s.shape} and transposeA=${i} and transposeB=${o} must match.`);let x=i?[A,u,d]:[A,d,u],_=o?[y,p,h]:[y,h,p],I=yr({inputs:{x:a},backend:n,attrs:{shape:x}}),T=yr({inputs:{x:s},backend:n,attrs:{shape:_}}),E=n.dataIdMap.get(I.dataId).id,N=n.dataIdMap.get(T.dataId).id,F=i?I.shape[2]:I.shape[1],$=o?T.shape[1]:T.shape[2],D=Math.max(A,y),P=n.makeOutput([D,F,$],I.dtype),H=n.dataIdMap.get(P.dataId).id,V=new Uint8Array(new Int32Array(I.shape).buffer),K=new Uint8Array(new Int32Array(T.shape).buffer);return nb(E,V,I.shape.length,N,K,T.shape.length,i,o,H),P.shape=w,P}var vG={kernelName:Ya,backendName:"wasm",setupFunc:_G,kernelFunc:bG};function pp(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 kG={kernelName:Qa,backendName:"wasm",kernelFunc:pp},rb;function IG(e){rb=e.wasm.cwrap(ma,null,["number","number","number","number"])}function NG(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),c=n.dataIdMap.get(l.dataId).id;return rb(o,s,i,c),l}var SG={kernelName:ma,backendName:"wasm",setupFunc:IG,kernelFunc:NG};function ab(e){let{inputs:t,backend:n}=e,r=v.parseAxisParam(e.attrs.axis,t[0].shape)[0],a=C.computeOutShape(t.map(p=>p.shape),r),s=t.filter(p=>v.sizeFromShape(p.shape)>0);if(s.length===1)return hp({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(C.assertParamsConsistent(o,r),s[0].dtype==="string"){let p=s.map(w=>{let x=v.sizeFromShape(w.shape.slice(r));return yr({inputs:{x:w},backend:n,attrs:{shape:[-1,x]}})}),f=p.map(w=>({vals:n.readSync(w.dataId),shape:w.shape}));a=C.computeOutShape(p.map(w=>w.shape),1);let m=p[0].shape[0]===1,A=sA(f,a,t[0].dtype,m),y=C.computeOutShape(s.map(w=>w.shape),r);i.shape=y;let g=n.dataIdMap.get(i.dataId);return g.stringBytes=C.fromStringArrayToUint8(A),i}let l=v.sizeFromShape(s[0].shape.slice(0,r)),c=0,u=s.map(p=>{let f=v.sizeFromShape(p.shape.slice(r));return c+=f,f}),h=s.map(p=>n.typedArrayFromHeap(p)),d=n.typedArrayFromHeap(i);for(let p=0;p<l;p++){let f=p*c;for(let m=0;m<h.length;m++){let A=u[m],y=p*A,g=h[m].subarray(y,y+A);d.set(g,f),f+=A}}return i}var TG={kernelName:Gi,backendName:"wasm",kernelFunc:ab},sb;function EG(e){sb=e.wasm.cwrap(es,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function CG(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:c,pad:u,dimRoundingMode:h,dataFormat:d}=n,p=C.convertConv2DDataFormat(d),f=C.computeConv2DInfo(a.shape,s.shape,l,c,u,h,!1,p),m=f.filterHeight,A=f.filterWidth,y=f.padInfo.top,g=f.padInfo.right,w=f.padInfo.bottom,x=f.padInfo.left,_=f.dilationHeight,I=f.dilationWidth,T=f.strideHeight,E=f.strideWidth,N=f.inChannels,F=f.outChannels,$=f.padInfo.type==="SAME"?1:0;if(f.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${f.dataFormat}'. Please use 'channelsLast'.`);let D=r.makeOutput(f.outShape,"float32"),P=r.dataIdMap.get(D.dataId).id;return sb(i,a.shape[0],a.shape[1],a.shape[2],o,m,A,y,g,w,x,$,_,I,T,E,N,F,P),D}var RG={kernelName:es,backendName:"wasm",setupFunc:EG,kernelFunc:CG},ib;function FG(e){ib=e.wasm.cwrap(ts,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 MG(e){let{backend:t,inputs:n,attrs:r}=e,{dy:a,filter:s}=n,{strides:i,pad:o,dataFormat:l,dimRoundingMode:c,inputShape:u}=r,h=1,d=C.convertConv2DDataFormat(l),p=C.computeConv2DInfo(u,s.shape,i,h,o,c,!1,d),{batchSize:f,filterHeight:m,filterWidth:A,inChannels:y,inHeight:g,inWidth:w,outChannels:x,outHeight:_,outWidth:I,strideHeight:T,strideWidth:E}=p,N=m-1-p.padInfo.top,F=A-1-p.padInfo.left,$=p.dataFormat==="channelsLast",D=v.computeStrides(p.inShape),P=v.computeStrides(a.shape),[H,V,K]=v.computeStrides(s.shape),X=D[0],ee=$?D[1]:D[2],J=$?D[2]:1,ae=$?1:D[1],Y=P[0],ue=$?P[1]:P[2],ne=$?P[2]:1,de=$?1:P[1],he=t.makeOutput(p.inShape,"float32"),me=t.dataIdMap.get(he.dataId).id,Ae=t.dataIdMap.get(a.dataId).id,ke=t.dataIdMap.get(s.dataId).id;return ib(Ae,ke,f,m,A,g,w,y,_,I,x,T,E,N,F,H,V,K,X,ee,J,ae,Y,ue,ne,de,me),he}var $G={kernelName:ts,backendName:"wasm",setupFunc:FG,kernelFunc:MG},DG=Rn(ns),PA;(function(e){e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest"})(PA||(PA={}));var ob;function OG(e){ob=e.wasm.cwrap(Xi,null,["number","number","number","number","array","number","number","number","number","number"])}function zG(e){let{backend:t,inputs:n,attrs:r}=e,{method:a,extrapolationValue:s,cropSize:i}=r,{image:o,boxes:l,boxInd:c}=n,u=l.shape[0],[h,d]=i,p=[u,h,d,o.shape[3]],f=t.dataIdMap.get(o.dataId),m;o.dtype!=="float32"&&(m=pp({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(c.dataId).id,w=t.makeOutput(p,"float32"),x=t.dataIdMap.get(w.dataId).id,_=new Uint8Array(new Int32Array(o.shape).buffer);return ob(A,y,g,u,_,h,d,PA[a],s,x),m!=null&&t.disposeData(m.dataId),w}var PG={kernelName:Xi,backendName:"wasm",setupFunc:OG,kernelFunc:zG},lb;function LG(e){lb=e.wasm.cwrap(rs,null,["number","number","number","number","number","number"])}function WG(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 c=C.getAxesPermutation([s],l),u=a;c!==null&&(u=dp({inputs:{x:a},attrs:{perm:c},backend:n}));let h=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumsum",[h],l);let d=n.makeOutput(u.shape,u.dtype),p=u.shape[h],f=n.dataIdMap.get(u.dataId).id,m=n.dataIdMap.get(d.dataId).id;lb(f,i?1:0,o?1:0,p,m,Cn[a.dtype]);let A=d;if(c!==null){let y=C.getUndoAxesPermutation(c);A=dp({inputs:{x:d},attrs:{perm:y},backend:n}),n.disposeData(u.dataId),n.disposeData(d.dataId)}return A}var BG={kernelName:rs,backendName:"wasm",setupFunc:LG,kernelFunc:WG},ub;function VG(e){ub=e.wasm.cwrap(Ki,null,["number","number","number","array","number","array","array","number","number"])}function UG(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: ${s}`);let o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],c=i==="NHWC"?a.shape[2]:a.shape[3],u=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,d=c*s,p=u/(s*s),f=i==="NHWC"?[o,h,d,p]:[o,p,h,d],m=t.makeOutput(f,"float32"),A=t.dataIdMap.get(a.dataId).id,y=new Uint8Array(new Int32Array(v.computeStrides(a.shape)).buffer),g=new Uint8Array(new Int32Array(f).buffer),w=new Uint8Array(new Int32Array(v.computeStrides(f)).buffer),x=t.dataIdMap.get(m.dataId).id;return ub(A,s,i==="NHWC"?1:0,y,a.shape.length-1,g,w,f.length,x),m}var HG={kernelName:Ki,backendName:"wasm",setupFunc:VG,kernelFunc:UG},cb;function jG(e){cb=e.wasm.cwrap(as,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function GG(e){let{inputs:t,attrs:n,backend:r}=e,{x:a,filter:s}=t,i=r.dataIdMap.get(a.dataId).id,o=r.dataIdMap.get(s.dataId).id,{strides:l,dilations:c,pad:u,dimRoundingMode:h}=n,d=c==null?[1,1]:c,p=C.computeConv2DInfo(a.shape,s.shape,l,d,u,h,!0),f=p.filterHeight,m=p.filterWidth,A=p.padInfo.top,y=p.padInfo.right,g=p.padInfo.bottom,w=p.padInfo.left,x=p.dilationHeight,_=p.dilationWidth,I=p.strideHeight,T=p.strideWidth,E=p.inChannels,N=p.outChannels,F=p.padInfo.type==="SAME"?1:0;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${p.dataFormat}'. Please use 'channelsLast'.`);let $=r.makeOutput(p.outShape,"float32"),D=r.dataIdMap.get($.dataId).id;return cb(i,a.shape[0],a.shape[1],a.shape[2],o,f,m,A,y,g,w,F,x,_,I,T,E,N,D),$}var qG={kernelName:as,backendName:"wasm",setupFunc:jG,kernelFunc:GG},XG=!1,KG=un(Yi,XG,"bool"),ZG=Rn(is);function LA(e){let{inputs:t,attrs:n,backend:r}=e,{input:a}=t,{dim:s}=n,i=a.shape.length,o=a.shape.slice(),l=s;return s<0&&(v.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),yr({inputs:{x:a},backend:r,attrs:{shape:o}})}var JG={kernelName:Qi,backendName:"wasm",kernelFunc:LA};function YG(e){let{attrs:{shape:t,value:n,dtype:r},backend:a}=e,s=a.makeOutput(t,r);return a.typedArrayFromHeap(s).fill(n),s}var QG={kernelName:hu,backendName:"wasm",kernelFunc:YG},hb;function eq(e){hb=e.wasm.cwrap(to,null,["number","number","number","number","number","number"])}function tq(e){let{inputs:t,backend:n}=e,{image:r}=t,a=n.makeOutput(r.shape,r.dtype),s=n.dataIdMap.get(r.dataId).id,i=n.dataIdMap.get(a.dataId).id,[o,l,c,u]=r.shape;return hb(s,o,l,c,u,i),a}var nq={kernelName:to,backendName:"wasm",kernelFunc:tq,setupFunc:eq},rq=Rn(os),aq=!1,sq=un(ls,aq),db;function iq(e){db=e.wasm.cwrap(us,null,["number","number","number","number","number","number","number"])}function oq(e){let{backend:t,inputs:n,attrs:r}=e,{varianceEpsilon:a}=r,{x:s,mean:i,variance:o,offset:l,scale:c}=n,u=t.dataIdMap.get(s.dataId).id,h=t.dataIdMap.get(i.dataId).id,d=t.dataIdMap.get(o.dataId).id,p=l!=null?t.dataIdMap.get(l.dataId).id:0,f=c!=null?t.dataIdMap.get(c.dataId).id:0,m=t.makeOutput(s.shape,s.dtype);if(v.sizeFromShape(s.shape)===0)return m;let A=t.dataIdMap.get(m.dataId).id;return db(u,h,d,p,f,a,A),m}var lq={kernelName:us,backendName:"wasm",setupFunc:iq,kernelFunc:oq},pb;function uq(e){pb=e.wasm.cwrap(Ws,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function cq(e){let{inputs:t,attrs:n,backend:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dilations:u,dataFormat:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=n,m=C.computeConv2DInfo(a.shape,s.shape,l,u,c,d),A=fc[p];if(A==null)throw new Error(`${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,w=m.outChannels,x=0;if(i!=null){let ne=r.dataIdMap.get(i.dataId);if(ne.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${ne.shape.length}.`);if(ne.shape[0]!==w)throw new Error(`FusedConv2D bias shape (${ne.shape}) does not match the number of output channels (${w})`);x=ne.id}let _=m.filterHeight,I=m.filterWidth,T=m.padInfo.top,E=m.padInfo.right,N=m.padInfo.bottom,F=m.padInfo.left,$=m.dilationHeight,D=m.dilationWidth,P=m.strideHeight,H=m.strideWidth,V=m.inChannels,K=m.padInfo.type==="SAME"?1:0,X=m.batchSize,ee=m.inHeight,J=m.inWidth;if(h!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${h}'. Please use 'NHWC'.`);let ae=r.makeOutput(m.outShape,"float32"),Y=r.dataIdMap.get(ae.dataId).id,ue=o==null?0:r.dataIdMap.get(o.dataId).id;return pb(y,X,ee,J,g,_,I,x,T,E,N,F,K,$,D,P,H,V,w,A,ue,f||0,Y),ae}var hq={kernelName:Ws,backendName:"wasm",setupFunc:uq,kernelFunc:cq},fb;function dq(e){fb=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"])}function pq(e){let{inputs:t,attrs:n,backend:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dilations:u,dataFormat:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=n,m=C.computeConv2DInfo(a.shape,s.shape,l,u,c,d,!0),A=fc[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,w=m.outChannels,x=0;if(i!=null){let ne=r.dataIdMap.get(i.dataId);if(ne.shape.length!==1)throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${ne.shape.length}.`);if(ne.shape[0]!==w)throw new Error(`FusedDepthwiseConv2D bias shape (${ne.shape}) does not match the number of output channels (${w})`);x=ne.id}let _=m.filterHeight,I=m.filterWidth,T=m.padInfo.top,E=m.padInfo.right,N=m.padInfo.bottom,F=m.padInfo.left,$=m.dilationHeight,D=m.dilationWidth,P=m.strideHeight,H=m.strideWidth,V=m.inChannels,K=m.padInfo.type==="SAME"?1:0,X=m.batchSize,ee=m.inHeight,J=m.inWidth;if(h!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${h}'. Please use 'NHWC'.`);let ae=r.makeOutput(m.outShape,"float32"),Y=r.dataIdMap.get(ae.dataId).id,ue=o==null?0:r.dataIdMap.get(o.dataId).id;return fb(y,X,ee,J,g,_,I,x,T,E,N,F,K,$,D,P,H,V,w,A,ue,f||0,Y),ae}var fq={kernelName:Bs,backendName:"wasm",setupFunc:dq,kernelFunc:pq},mb;function mq(e){mb=e.wasm.cwrap(ro,null,["number","number","number","number","number","number","array","number"])}function Aq(e){let{backend:t,inputs:n}=e,{params:r,indices:a}=n,[s,i,o,l]=Tf.prepareAndValidate(r,a),c=t.makeOutput(s,r.dtype);if(i===0)return c;let u=a.shape,h=u[u.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(c.dataId).id;return mb(d,Cn[r.dtype],p,i,h,o,f,m),c}var yq={kernelName:ro,backendName:"wasm",setupFunc:mq,kernelFunc:Aq},Ab;function gq(e){Ab=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function xq(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],c=C.segment_util.collectGatherOpShapeInfo(a,s,l,o),u=yr({inputs:{x:a},attrs:{shape:[c.batchSize,c.outerSize,c.dimSize,c.sliceSize]},backend:t}),h=v.sizeFromShape(s.shape),d=yr({inputs:{x:s},attrs:{shape:[c.batchSize,h/c.batchSize]},backend:t}),p=[c.batchSize,c.outerSize,h/c.batchSize,c.sliceSize],f=t.makeOutput(p,a.dtype);if(v.sizeFromShape(a.shape)===0)return f;let m=u.shape.length-1,A=t.dataIdMap.get(u.dataId).id,y=t.dataIdMap.get(d.dataId).id,g=t.dataIdMap.get(f.dataId).id,w=new Uint8Array(new Int32Array(v.computeStrides(u.shape)).buffer),x=new Uint8Array(new Int32Array(v.computeStrides(p)).buffer);return Ab(A,Cn[a.dtype],w,m,y,c.batchSize,x,g),f.shape=c.outputShape,f}var wq={kernelName:no,backendName:"wasm",setupFunc:gq,kernelFunc:xq},_q=!1,bq=un(ao,_q,"bool"),vq=!1,kq=un(cs,vq,"bool"),yb;function Iq(e){yb=e.wasm.cwrap(hs,null,["number","number","number"])}function Nq(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;yb(a,n,i)}return s}var Sq={kernelName:hs,backendName:"wasm",setupFunc:Iq,kernelFunc:Nq},Tq=!1,Eq=un(uo,Tq,"bool"),Cq=!1,Rq=un(co,Cq,"bool"),Fq=Rn(ds),Mq=!1,$q=un(po,Mq,"bool"),gb;function Dq(e){gb=e.wasm.cwrap(ps,null,["number, number, number"])}function Oq(e){let{backend:t,inputs:n,attrs:r}=e,{reductionIndices:a,keepDims:s}=r,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:c,axes:u,originalAxes:h,inputWasTransposed:d}=kl(i,a,t);if(d){let g=t.dataIdMap.get(c.dataId).id;l=c,o=g}let p=l.shape.length;C.assertAxesAreInnerMostDims("max",u,p);let[f,m]=C.computeOutAndReduceShapes(l.shape,u),A=v.sizeFromShape(m),y=t.makeOutput(f,i.dtype);if(v.sizeFromShape(l.shape)!==0){let g=t.dataIdMap.get(y.dataId).id;gb(o,A,g)}if(d&&t.disposeData(c.dataId),s){let g=C.expandShapeToKeepDim(y.shape,h);y.shape=g}return y}var zq={kernelName:ps,backendName:"wasm",setupFunc:Dq,kernelFunc:Oq},Pq=!1,Lq=un(fs,Pq),xb;function Wq(e){xb=e.wasm.cwrap(ms,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Bq(e){let{inputs:t,attrs:n,backend:r}=e,a=t.x,s=r.dataIdMap.get(a.dataId).id,{filterSize:i,strides:o,pad:l,dimRoundingMode:c}=n,u=C.computePool2DInfo(a.shape,i,o,1,l,c),h=u.filterHeight,d=u.filterWidth,p=u.padInfo.top,f=u.padInfo.right,m=u.padInfo.bottom,A=u.padInfo.left,y=u.dilationHeight,g=u.dilationWidth,w=u.strideHeight,x=u.strideWidth,_=u.inChannels,I=u.outChannels;if(u.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${u.dataFormat}'. Please use 'channelsLast'.`);let T=r.makeOutput(u.outShape,"float32"),E=r.dataIdMap.get(T.dataId).id;return xb(s,a.shape[0],a.shape[1],a.shape[2],h,d,p,f,m,A,y,g,w,x,_,I,E),T}var Vq={kernelName:ms,backendName:"wasm",setupFunc:Wq,kernelFunc:Bq},wb;function Uq(e){wb=e.wasm.cwrap(As,null,["number, number, number"])}function Hq(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,c=i,{transposed:u,axes:h,originalAxes:d,inputWasTransposed:p}=kl(i,a,t),f=h;if(p){let x=t.dataIdMap.get(u.dataId).id;x!==o&&(c=u,l=x,f=C.getInnerMostAxes(f.length,c.shape.length))}C.assertAxesAreInnerMostDims("mean",f,c.shape.length);let[m,A]=C.computeOutAndReduceShapes(c.shape,f),y=v.sizeFromShape(A),g=c;c.dtype!=="float32"&&(g=pp({backend:t,inputs:{x:c},attrs:{dtype:"float32"}}),l=t.dataIdMap.get(g.dataId).id);let w=t.makeOutput(m,"float32");if(v.sizeFromShape(c.shape)!==0){let x=t.dataIdMap.get(w.dataId).id;wb(l,y,x)}if(p&&t.disposeData(u.dataId),s){let x=C.expandShapeToKeepDim(w.shape,d);w.shape=x}return c.dtype!=="float32"&&t.disposeData(g.dataId),w}var jq={kernelName:As,backendName:"wasm",setupFunc:Uq,kernelFunc:Hq},_b;function Gq(e){_b=e.wasm.cwrap(ys,null,["number, number, number"])}function qq(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,c=i,{transposed:u,axes:h,originalAxes:d,inputWasTransposed:p}=kl(i,a,t);if(p){let w=t.dataIdMap.get(u.dataId).id;w!==o&&(c=u,l=w)}let f=c.shape.length;C.assertAxesAreInnerMostDims("min",h,f);let[m,A]=C.computeOutAndReduceShapes(c.shape,h),y=v.sizeFromShape(A),g=t.makeOutput(m,c.dtype);if(v.sizeFromShape(c.shape)!==0){let w=t.dataIdMap.get(g.dataId).id;_b(l,y,w)}if(p&&t.disposeData(u.dataId),s){let w=C.expandShapeToKeepDim(g.shape,d);g.shape=w}return g}var Xq={kernelName:ys,backendName:"wasm",setupFunc:Gq,kernelFunc:qq},Kq=!1,Zq=un(gs,Kq),Jq=!0,Yq=un(xs,Jq),Qq=Rn(mo);function WA(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 bb;function eX(e){bb=e.wasm.cwrap(yo,"number",["number","number","number","number","number"])}function tX(e){let{backend:t,inputs:n,attrs:r}=e,{iouThreshold:a,maxOutputSize:s,scoreThreshold:i}=r,{boxes:o,scores:l}=n,c=t.dataIdMap.get(o.dataId).id,u=t.dataIdMap.get(l.dataId).id,h=bb(c,u,s,a,i),{pSelectedIndices:d,selectedSize:p,pSelectedScores:f,pValidOutputs:m}=WA(t,h);return t.wasm._free(f),t.wasm._free(m),t.makeOutput([p],"int32",d)}var nX={kernelName:yo,backendName:"wasm",setupFunc:eX,kernelFunc:tX},vb;function rX(e){vb=e.wasm.cwrap(go,"number",["number","number","number","number","number","bool"])}function aX(e){let{backend:t,inputs:n,attrs:r}=e,{iouThreshold:a,maxOutputSize:s,scoreThreshold:i,padToMaxOutputSize:o}=r,{boxes:l,scores:c}=n,u=t.dataIdMap.get(l.dataId).id,h=t.dataIdMap.get(c.dataId).id,d=vb(u,h,s,a,i,o),{pSelectedIndices:p,selectedSize:f,pSelectedScores:m,pValidOutputs:A}=WA(t,d);t.wasm._free(m);let y=t.makeOutput([f],"int32",p),g=t.makeOutput([],"int32",A);return[y,g]}var sX={kernelName:go,backendName:"wasm",setupFunc:rX,kernelFunc:aX},kb;function iX(e){kb=e.wasm.cwrap(xo,"number",["number","number","number","number","number","number"])}function oX(e){let{backend:t,inputs:n,attrs:r}=e,{iouThreshold:a,maxOutputSize:s,scoreThreshold:i,softNmsSigma:o}=r,{boxes:l,scores:c}=n,u=t.dataIdMap.get(l.dataId).id,h=t.dataIdMap.get(c.dataId).id,d=kb(u,h,s,a,i,o),{pSelectedIndices:p,selectedSize:f,pSelectedScores:m,pValidOutputs:A}=WA(t,d);t.wasm._free(A);let y=t.makeOutput([f],"int32",p),g=t.makeOutput([f],"float32",m);return[y,g]}var lX={kernelName:xo,backendName:"wasm",setupFunc:iX,kernelFunc:oX},uX=!1,cX=un(Ao,uX,"bool"),Ib;function hX(e){Ib=e.wasm.cwrap(ws,null,["number","number","number","number","number"])}function dX(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"),c=n.dataIdMap.get(l.dataId).id,u=n.dataIdMap.get(a.dataId).id;return Ib(u,s,i,o,c),l}var pX={kernelName:ws,backendName:"wasm",setupFunc:hX,kernelFunc:dX};function fX(e){let{inputs:{x:t},backend:n}=e,r=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(r).fill(1),r}var mX={kernelName:wo,backendName:"wasm",kernelFunc:fX};function AX(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return LA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(l=>{v.assertShapesMatch(s,l.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===l.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=t.map(l=>LA({inputs:{input:l},backend:n,attrs:{dim:a}}));return ab({inputs:o,backend:n,attrs:{axis:a}})}var yX={kernelName:_o,backendName:"wasm",kernelFunc:AX},Nb;function gX(e){Nb=e.wasm.cwrap(_s,null,["number","array","number","number","array","array","number","number"])}function xX(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,c=new Uint8Array(new Int32Array(t.shape).buffer),u=r.map(f=>f[0]),h=r.map(f=>f[1]),d=new Uint8Array(new Int32Array(u).buffer),p=new Uint8Array(new Int32Array(h).buffer);return Nb(i,c,t.shape.length,Cn[t.dtype],d,p,a,l),o}var wX={kernelName:_s,backendName:"wasm",kernelFunc:xX,setupFunc:gX},_X=!1,bX=un(bs,_X),Sb;function vX(e){Sb=e.wasm.cwrap(vs,null,["number","number","number"])}function kX(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 Sb(s,i,l),o}var IX={kernelName:vs,backendName:"wasm",setupFunc:vX,kernelFunc:kX},Tb;function NX(e){Tb=e.wasm.cwrap(bo,null,["number","number","number","number"])}function SX(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,c=i,{transposed:u,axes:h,originalAxes:d,inputWasTransposed:p}=kl(i,a,t),f=h;if(p){let w=t.dataIdMap.get(u.dataId).id;w!==o&&(c=u,l=w,f=C.getInnerMostAxes(f.length,c.shape.length))}C.assertAxesAreInnerMostDims("prod",f,c.shape.length);let[m,A]=C.computeOutAndReduceShapes(c.shape,f),y=v.sizeFromShape(A),g=t.makeOutput(m,c.dtype);if(v.sizeFromShape(c.shape)!==0){let w=t.dataIdMap.get(g.dataId).id;Tb(l,y,Cn[g.dtype],w)}if(p&&t.disposeData(u.dataId),s){let w=C.expandShapeToKeepDim(g.shape,d);g.shape=w}return g}var TX={kernelName:bo,backendName:"wasm",setupFunc:NX,kernelFunc:SX},EX=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=lA(r,a,s,i),l=t.makeOutput([o.length],i);return t.typedArrayFromHeap(l).set(o),l},CX={kernelName:yu,backendName:"wasm",kernelFunc:EX},RX=!0,FX=un(ss,RX),MX=Rn(ks),$X=Rn(Ns),Eb;function DX(e){Eb=e.wasm.cwrap(Is,null,["number","number","number","number","number","number","number","number","number","number"])}function OX(e){let{backend:t,inputs:n,attrs:r}=e,{images:a}=n,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,[u,h,d,p]=a.shape,f=[u,l,c,p],m=t.dataIdMap.get(a.dataId),A;m.dtype!=="float32"&&(A=pp({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 w=t.dataIdMap.get(g.dataId).id;return Eb(y,u,h,d,p,l,c,s?1:0,i?1:0,w),A!=null&&t.disposeData(A.dataId),g}var zX={kernelName:Is,backendName:"wasm",setupFunc:DX,kernelFunc:OX},Cb;function PX(e){Cb=e.wasm.cwrap(Ss,null,["number","array","number","array","number","number"])}function LX(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 hp({inputs:{x:a},backend:n});let o=n.makeOutput(a.shape,a.dtype),l=n.dataIdMap.get(a.dataId).id,c=n.dataIdMap.get(o.dataId).id,u=new Uint8Array(new Int32Array(i).buffer),h=new Uint8Array(new Int32Array(a.shape).buffer);return Cb(l,u,i.length,h,a.shape.length,c),yr({inputs:{x:o},attrs:{shape:a.shape},backend:n})}var WX={kernelName:Ss,backendName:"wasm",kernelFunc:LX,setupFunc:PX},Rb;function BX(e){Rb=e.wasm.cwrap(Po,null,["number","number","number","number","number","number","number","number","array","number","number"])}function VX(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),c=n.dataIdMap.get(a.dataId).id,u=n.dataIdMap.get(l.dataId).id,[h,d,p,f]=a.shape,[m,A]=C.getImageCenter(o,d,p),y=i===0,g=255,w=typeof i=="number"?[i,i,i,y?0:g]:[...i,g],x=new Uint8Array(new Int32Array(w).buffer);return Rb(c,h,d,p,f,s,m,A,x,w.length,u),l}var UX={kernelName:Po,backendName:"wasm",kernelFunc:VX,setupFunc:BX},HX=Rn(Ts),jX=Rn(Es),Fb;function GX(e){Fb=e.wasm.cwrap(Io,null,["number","number","number","number","number","number","array","number","number"])}function qX(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:c,sliceSize:u,strides:h,outputSize:d}=Ef.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 Fb(p,f,Cn[s.dtype],l,c,u,m,d,A),o}var XX={kernelName:Io,backendName:"wasm",setupFunc:GX,kernelFunc:qX},Mb;function KX(e){Mb=e.wasm.cwrap("SelectV2",null,["number","number","number","number","number"])}function ZX(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,c=n.makeOutput(a.shape,a.dtype),u=n.dataIdMap.get(c.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 Mb(i,o,l,p,u),c}var JX={kernelName:No,backendName:"wasm",kernelFunc:ZX,setupFunc:KX},$b;function YX(e){$b=e.wasm.cwrap(Rs,null,["number","number"])}function QX(e){let{backend:t,inputs:{x:n}}=e,r=t.dataIdMap.get(n.dataId).id,a=t.makeOutput(n.shape,n.dtype),s=t.dataIdMap.get(a.dataId).id;return v.sizeFromShape(a.shape)===0||$b(r,s),a}var eK={kernelName:"Sigmoid",backendName:"wasm",setupFunc:YX,kernelFunc:QX},tK=Rn(Cs);function fp(e){let{inputs:{x:t},attrs:{begin:n,size:r},backend:a}=e,[s,i]=rn.parseSliceParams(t,n,r),o=rn.isSliceContinous(t.shape,s,i),l=a.readSync(t.dataId),c=a.makeOutput(i,t.dtype),u=v.computeStrides(t.shape),h=a.dataIdMap.get(c.dataId);if(o){let f=rn.computeFlatOffset(s,u);return t.dtype==="string"?h.stringBytes=l.slice(f,f+v.sizeFromShape(i)):a.typedArrayFromHeap(c).set(l.subarray(f,f+v.sizeFromShape(i))),c}if(t.dtype==="string"){let f=jd(l,s,i,t.shape,t.dtype);return h.stringBytes=f,c}let d=a.typedArrayFromHeap(c),p=t.shape.length;if(p===2)nK(l,u[0],d,s,i);else if(p===3)rK(l,u[0],u[1],d,s,i);else if(p===4)aK(l,u[0],u[1],u[2],d,s,i);else{let f=jd(l,s,i,t.shape,t.dtype);d.set(f)}return c}function nK(e,t,n,r,a){let s=0,i=r[0],o=r[1],l=i+a[0];for(let c=i;c<l;c++){let u=c*t+o;n.set(e.subarray(u,u+a[1]),s),s+=a[1]}}function rK(e,t,n,r,a,s){let i=0,o=a[0],l=a[1],c=a[2],u=o+s[0],h=l+s[1];for(let d=o;d<u;d++)for(let p=l;p<h;p++){let f=d*t+p*n+c;r.set(e.subarray(f,f+s[2]),i),i+=s[2]}}function aK(e,t,n,r,a,s,i){let o=0,l=s[0],c=s[1],u=s[2],h=l+i[0],d=c+i[1],p=u+i[2],f=s[3];for(let m=l;m<h;m++)for(let A=c;A<d;A++)for(let y=u;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 sK={kernelName:To,backendName:"wasm",kernelFunc:fp},Db;function iK(e){Db=e.wasm.cwrap($s,null,["number","number","number","number"])}function oK(e){let{backend:t,inputs:{logits:n},attrs:{dim:r}}=e,a=t.dataIdMap.get(n.dataId).id,s=t.makeOutput(n.shape,n.dtype),i=t.dataIdMap.get(s.dataId).id,o=n.shape[r],l=v.sizeFromShape(n.shape)/o;return v.sizeFromShape(s.shape)===0||Db(a,i,o,l),s}var lK={kernelName:$s,backendName:"wasm",setupFunc:iK,kernelFunc:oK};function uK(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=C.prepareSplitSize(a,s,o),c=new Array(a.shape.length).fill(0),u=a.shape.slice();return l.map(h=>{let d=[...u];d[o]=h;let p=fp({inputs:{x:a},attrs:{begin:c,size:d},backend:r});return c[o]+=h,p})}var cK={kernelName:Fo,backendName:"wasm",kernelFunc:uK},hK=Rn(Fs),dK=Rn(wu),pK=!0,fK=un(Ds,pK),Ob;function mK(e){Ob=e.wasm.cwrap(ya,null,["number","number","number"])}function AK(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 Ob(i,a,l),o}var yK={kernelName:ya,backendName:"wasm",setupFunc:mK,kernelFunc:AK},zb;function gK(e){zb=e.wasm.cwrap(Mo,null,["number","array","number","array","array","array","array","array","number","number"])}function xK(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:c,ellipsisMask:u,newAxisMask:h,shrinkAxisMask:d}=r,p=C.slice_util.maskToAxes(u);if(p.length>1)throw new Error("Multiple ellipses in slice is not allowed.");if(u!==0&&h!==0)throw new Error("Using both ellipsisMask and newAxisMask is not yet supported.");if(u!==0&&d!==0)throw new Error("Using both ellipsisMask and shrinkAxisMask is not yet supported.");let f=a.shape.length-s.length,m=C.slice_util.maskToAxes(h),A=a.shape.slice();m.forEach(N=>{s[N]=0,i[N]=1,A.splice(N,0,1)});let y=yr({inputs:{x:a},attrs:{shape:A},backend:t}),{begin:g,end:w,strides:x}=C.slice_util.getNormalizedAxes(y.shape,p,f,s,i,o,l,c,u);s=g,i=w,o=x;let _=C.slice_util.maskToAxes(d);_.forEach(N=>{i[N]=s[N]+1,o[N]=1});let I=C.slice_util.computeOutShape(s,i,o),T=I.filter((N,F)=>_.indexOf(F)===-1);if(o.every(N=>N===1)){let N=fp({inputs:{x:a},attrs:{begin:s,size:I},backend:t});return yr({inputs:{x:N},attrs:{shape:T},backend:t})}let E=t.makeOutput(T,"float32");if(!T.some(N=>N===0)){let N=t.dataIdMap.get(y.dataId).id,F=new Uint8Array(new Int32Array(v.computeStrides(y.shape)).buffer),$=new Uint8Array(new Int32Array(s).buffer),D=new Uint8Array(new Int32Array(i).buffer),P=new Uint8Array(new Int32Array(o).buffer),H=new Uint8Array(new Int32Array(T).buffer),V=new Uint8Array(new Int32Array(v.computeStrides(T)).buffer),K=t.dataIdMap.get(E.dataId).id;zb(N,F,y.shape.length,$,D,P,H,V,T.length,K)}return yr({inputs:{x:E},attrs:{shape:T},backend:t})}var wK={kernelName:Mo,backendName:"wasm",setupFunc:gK,kernelFunc:xK},_K=!0,bK=un(Os,_K),Pb;function vK(e){Pb=e.wasm.cwrap(Ms,null,["number, number, number"])}function kK(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,c=i,{transposed:u,axes:h,originalAxes:d,inputWasTransposed:p}=kl(i,a,t),f=h;if(p){let w=t.dataIdMap.get(u.dataId).id;w!==o&&(c=u,l=w,f=C.getInnerMostAxes(f.length,c.shape.length))}C.assertAxesAreInnerMostDims("sum",f,c.shape.length);let[m,A]=C.computeOutAndReduceShapes(c.shape,f),y=v.sizeFromShape(A),g=t.makeOutput(m,c.dtype);if(v.sizeFromShape(c.shape)!==0){let w=t.dataIdMap.get(g.dataId).id;Pb(l,y,w)}if(p&&t.disposeData(u.dataId),s){let w=C.expandShapeToKeepDim(g.shape,d);g.shape=w}return g}var IK={kernelName:Ms,backendName:"wasm",setupFunc:vK,kernelFunc:kK},NK=Rn(zs),Lb;function SK(e){Lb=e.wasm.cwrap(Aa,null,["number","array","number","array","number","number"])}function TK(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),c=new Uint8Array(new Int32Array(o).buffer),u=n.makeOutput(o,a.dtype),h=n.dataIdMap.get(u.dataId).id;return Lb(s,l,a.shape.length,c,o.length,Cn[u.dtype],h),u}var EK={kernelName:Aa,backendName:"wasm",setupFunc:SK,kernelFunc:TK},Wb;function CK(e){Wb=e.wasm.cwrap(Do,null,["number","array","number","number","number","bool","number","number"])}var RK=({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 c=t.makeOutput(l,r.dtype),u=t.dataIdMap.get(c.dataId).id,h=t.makeOutput(l,"int32"),d=t.dataIdMap.get(h.dataId).id;return Wb(i,o,r.shape.length,Cn[r.dtype],a,s,u,d),[c,h]},FK={kernelName:Do,backendName:"wasm",setupFunc:CK,kernelFunc:RK};function MK(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),c=0;for(let p=0;p<o;p++)p!==s&&(l[c++]=a.shape[p]);let u=new Array(i),h=new Array(o).fill(0),d=a.shape.slice();d[s]=1;for(let p=0;p<u.length;p++)h[s]=p,u[p]=fp({inputs:{x:a},attrs:{begin:h,size:d},backend:n});return u.map(({dataId:p,dtype:f})=>({dataId:p,dtype:f,shape:l}))}var $K={kernelName:Oo,backendName:"wasm",kernelFunc:MK};function DK(e){let{inputs:{x:t},backend:n}=e,r=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(r).fill(0),r}var OK={kernelName:zo,backendName:"wasm",kernelFunc:DK},zK=[rG,sG,lG,AG,xG,vG,kG,SG,TG,RG,$G,DG,PG,BG,HG,qG,KG,ZG,JG,QG,nq,rq,sq,nG,lq,hq,fq,yq,wq,bq,kq,uG,Sq,Eq,Rq,Fq,$q,zq,Lq,Vq,jq,Xq,Zq,Yq,Qq,nX,sX,lX,cX,pX,mX,yX,wX,bX,IX,TX,CX,FX,MX,$X,wG,zX,WX,UX,jX,HX,XX,JX,eK,tK,sK,lK,cK,hK,dK,fK,yK,wK,bK,IK,NK,EK,FK,pG,$K,OK];for(let e of zK)Lo(e);var BA=Q();BA.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])));BA.registerFlag("WASM_HAS_MULTITHREAD_SUPPORT",async()=>{if(BA.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 Bb=Qo(Y8()),PK='var threadInfoStruct=0;var selfThreadId=0;var parentThreadId=0;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:selfThreadId})}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};this.onmessage=function(e){try{if(e.data.cmd==="load"){Module["DYNAMIC_BASE"]=e.data.DYNAMIC_BASE;Module["DYNAMICTOP_PTR"]=e.data.DYNAMICTOP_PTR;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)}Module=WasmBackendModuleThreadedSimd(Module);postMessage({"cmd":"loaded"})}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;threadInfoStruct=e.data.threadInfoStruct;Module["__register_pthread_ptr"](threadInfoStruct,0,0);selfThreadId=e.data.selfThreadId;parentThreadId=e.data.parentThreadId;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["dynCall_ii"](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"){Atomics.store(Module["HEAPU32"],threadInfoStruct+4>>2,ex instanceof Module["ExitStatus"]?ex.status:-2);Atomics.store(Module["HEAPU32"],threadInfoStruct+0>>2,1);Module["_emscripten_futex_wake"](threadInfoStruct+0,2147483647);if(!(ex instanceof Module["ExitStatus"]))throw ex}}}else if(e.data.cmd==="cancel"){if(threadInfoStruct){Module["PThread"].threadCancel()}}else if(e.data.target==="setimmediate"){}else if(e.data.cmd==="processThreadQueue"){if(threadInfoStruct){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.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");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()}}}}',LK=Qo(Q8()),N0=class extends au{constructor(e){super();this.wasm=e,this.dataIdNextNumber=1,this.wasm.tfjs.init(),this.dataIdMap=new hh(this,Ln())}write(e,t,n){let r={};return this.move(r,e,t,n),r}numDataIds(){return this.dataIdMap.numDataIds()}async time(e){let t=v.now();return e(),{kernelMs:v.now()-t}}move(e,t,n,r){let a=this.dataIdNextNumber++;if(r==="string"){let l=t;this.dataIdMap.set(e,{id:a,stringBytes:l,shape:n,dtype:r,memoryOffset:null});return}let s=v.sizeFromShape(n),i=s*v.bytesPerElement(r),o=this.wasm._malloc(i);this.dataIdMap.set(e,{id:a,memoryOffset:o,shape:n,dtype:r}),this.wasm.tfjs.registerTensor(a,s,o),t!=null&&this.wasm.HEAPU8.set(new Uint8Array(t.buffer,t.byteOffset,i),o)}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 WK(s.buffer,n)}disposeData(e){let t=this.dataIdMap.get(e);this.wasm._free(t.memoryOffset),this.wasm.tfjs.disposeData(t.id),this.dataIdMap.delete(e)}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{r={};let a=this.dataIdNextNumber++;this.dataIdMap.set(r,{id:a,memoryOffset:n,shape:e,dtype:t});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 ${t}`)}}};function BK(e){return(t,n)=>(v.fetch(e,{credentials:"same-origin"}).then(r=>{r.ok||t.env.a(`failed to load wasm binary file at '${e}'`),r.arrayBuffer().then(a=>{WebAssembly.instantiate(a,t).then(s=>{n(s.instance)})})}),{})}function Vb(e,t,n){if(mp!=null)return mp;let r="tfjs-backend-wasm.wasm";return e&&t?r="tfjs-backend-wasm-threaded-simd.wasm":e&&(r="tfjs-backend-wasm-simd.wasm"),mc!=null&&mc[r]!=null?mc[r]:n+r}async function VK(){let[e,t]=await Promise.all([Q().getAsync("WASM_HAS_SIMD_SUPPORT"),Q().getAsync("WASM_HAS_MULTITHREAD_SUPPORT")]);return new Promise((n,r)=>{let a={};a.locateFile=(l,c)=>{if(l.endsWith(".worker.js")){let u=PK,h=new Blob([u],{type:"application/javascript"});return URL.createObjectURL(h)}return l.endsWith(".wasm")?Vb(e,t,Ac!=null?Ac:c):c+l},VA&&(a.instantiateWasm=BK(Vb(e,t,Ac!=null?Ac:"")));let s;t&&e&&mp==null?(s=Bb.default(a),s.mainScriptUrlOrBlob=new Blob(["var WasmBackendModuleThreadedSimd = "+Bb.default.toString()],{type:"text/javascript"})):s=LK.default(a);let i=null;s.tfjs={init:s.cwrap("init",null,[]),registerTensor:s.cwrap("register_tensor",null,["number","number","number"]),disposeData:s.cwrap("dispose_data",i,["number"]),dispose:s.cwrap("dispose",i,[])};let o=!1;s.onRuntimeInitialized=()=>{o=!0,yc=!1,n({wasm:s})},s.onAbort=()=>{o||yc||(yc=!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"}))}})}function WK(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 UK=["tfjs-backend-wasm.wasm","tfjs-backend-wasm-simd.wasm","tfjs-backend-wasm-threaded-simd.wasm"],mp=null,Ac=null,mc={},yc=!1,VA=!1;function A8(e,t=!1){if(Cf("setWasmPath has been deprecated in favor of setWasmPaths and will be removed in a future release."),yc)throw new Error("The WASM backend was already initialized. Make sure you call `setWasmPath()` before you call `tf.setBackend()` or `tf.ready()`");mp=e,VA=t}function S0(e,t=!1){if(yc)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")Ac=e;else{mc=e;let n=UK.filter(r=>mc[r]==null);if(n.length>0)throw new Error(`There were no entries found for the following binaries: ${n.join(",")}. Please either call setWasmPaths with a map providing a path for each binary, or with a string indicating the directory where all the binaries can be found.`)}VA=t}var T0="3.0.0",HK=2;Iu("wasm",async()=>{let{wasm:e}=await VK();return new N0(e)},HK);Z().prototype.abs=function(){return this.throwIfDisposed(),$t(this)};Z().prototype.acos=function(){return this.throwIfDisposed(),Ff(this)};Z().prototype.acosh=function(){return this.throwIfDisposed(),Mf(this)};Z().prototype.add=function(e){return this.throwIfDisposed(),oe(this,e)};Z().prototype.all=function(e,t){return this.throwIfDisposed(),Zh(this,e,t)};Z().prototype.any=function(e,t){return this.throwIfDisposed(),Nu(this,e,t)};Z().prototype.argMax=function(e){return this.throwIfDisposed(),Su(this,e)};Z().prototype.argMin=function(e){return this.throwIfDisposed(),$f(this,e)};Z().prototype.asScalar=function(){return this.throwIfDisposed(),M(this.size===1,()=>"The array must have only 1 element."),q(this,[])};Z().prototype.asType=function(e){return this.throwIfDisposed(),ye(this,e)};Z().prototype.as1D=function(){return this.throwIfDisposed(),q(this,[this.size])};Z().prototype.as2D=function(e,t){return this.throwIfDisposed(),q(this,[e,t])};Z().prototype.as3D=function(e,t,n){return this.throwIfDisposed(),q(this,[e,t,n])};Z().prototype.as4D=function(e,t,n,r){return this.throwIfDisposed(),q(this,[e,t,n,r])};Z().prototype.as5D=function(e,t,n,r,a){return this.throwIfDisposed(),q(this,[e,t,n,r,a])};Z().prototype.asin=function(){return this.throwIfDisposed(),Df(this)};Z().prototype.asinh=function(){return this.throwIfDisposed(),Of(this)};Z().prototype.atan=function(){return this.throwIfDisposed(),zf(this)};Z().prototype.atan2=function(e){return this.throwIfDisposed(),Pf(this,e)};Z().prototype.atanh=function(){return this.throwIfDisposed(),Lf(this)};Z().prototype.avgPool=function(e,t,n,r){return this.throwIfDisposed(),Tu(this,e,t,n,r)};Z().prototype.batchToSpaceND=function(e,t){return this.throwIfDisposed(),Eu(this,e,t)};Z().prototype.batchNorm=function(e,t,n,r,a){return this.throwIfDisposed(),Vs(this,e,t,n,r,a)};Z().prototype.broadcastTo=function(e){return this.throwIfDisposed(),Cu(this,e)};Z().prototype.cast=function(e){return this.throwIfDisposed(),ye(this,e)};Z().prototype.ceil=function(){return this.throwIfDisposed(),Bf(this)};Z().prototype.clipByValue=function(e,t){return this.throwIfDisposed(),pn(this,e,t)};Z().prototype.concat=function(e,t){return this.throwIfDisposed(),e instanceof Qe&&(e=[e]),ct([this,...e],t)};Z().prototype.conv1d=function(e,t,n,r,a,s){return this.throwIfDisposed(),Yh(this,e,t,n,r,a,s)};Z().prototype.conv2dTranspose=function(e,t,n,r,a){return this.throwIfDisposed(),Qh(this,e,t,n,r,a)};Z().prototype.conv2d=function(e,t,n,r,a,s){return this.throwIfDisposed(),Zr(this,e,t,n,r,a,s)};Z().prototype.cos=function(){return this.throwIfDisposed(),Ru(this)};Z().prototype.cosh=function(){return this.throwIfDisposed(),ed(this)};Z().prototype.cumsum=function(e,t,n){return this.throwIfDisposed(),td(this,e,t,n)};Z().prototype.depthToSpace=function(e,t){return this.throwIfDisposed(),Uf(this,e,t)};Z().prototype.depthwiseConv2d=function(e,t,n,r,a,s){return this.throwIfDisposed(),Uo(this,e,t,n,r,a,s)};Z().prototype.dilation2d=function(e,t,n,r,a){return this.throwIfDisposed(),Hf(this,e,t,n,r,a)};Z().prototype.divNoNan=function(e){return this.throwIfDisposed(),jf(this,e)};Z().prototype.div=function(e){return this.throwIfDisposed(),Ne(this,e)};Z().prototype.dot=function(e){return this.throwIfDisposed(),t0(this,e)};Z().prototype.elu=function(){return this.throwIfDisposed(),Ho(this)};Z().prototype.equal=function(e){return this.throwIfDisposed(),xa(this,e)};Z().prototype.erf=function(){return this.throwIfDisposed(),Gf(this)};Z().prototype.exp=function(){return this.throwIfDisposed(),Wn(this)};Z().prototype.expandDims=function(e){return this.throwIfDisposed(),vn(this,e)};Z().prototype.expm1=function(){return this.throwIfDisposed(),qf(this)};Z().prototype.fft=function(){return this.throwIfDisposed(),Bu(this)};Z().prototype.flatten=function(){return this.throwIfDisposed(),q(this,[this.size])};Z().prototype.floor=function(){return this.throwIfDisposed(),jo(this)};Z().prototype.floorDiv=function(e){return this.throwIfDisposed(),Xh(this,e)};Z().prototype.gather=function(e,t){return this.throwIfDisposed(),Us(this,e,t)};Z().prototype.greaterEqual=function(e){return this.throwIfDisposed(),_a(this,e)};Z().prototype.greater=function(e){return this.throwIfDisposed(),tr(this,e)};Z().prototype.ifft=function(){return this.throwIfDisposed(),Zo(this)};Z().prototype.irfft=function(){return this.throwIfDisposed(),yd(this)};Z().prototype.isFinite=function(){return this.throwIfDisposed(),n0(this)};Z().prototype.isInf=function(){return this.throwIfDisposed(),r0(this)};Z().prototype.isNaN=function(){return this.throwIfDisposed(),a0(this)};Z().prototype.leakyRelu=function(e){return this.throwIfDisposed(),Mu(this,e)};Z().prototype.lessEqual=function(e){return this.throwIfDisposed(),Hs(this,e)};Z().prototype.less=function(e){return this.throwIfDisposed(),rd(this,e)};Z().prototype.localResponseNormalization=function(e,t,n,r){return this.throwIfDisposed(),Kf(this,e,t,n,r)};Z().prototype.logSigmoid=function(){return this.throwIfDisposed(),o0(this)};Z().prototype.logSoftmax=function(e){return this.throwIfDisposed(),sd(this,e)};Z().prototype.logSumExp=function(e,t){return this.throwIfDisposed(),Zf(this,e,t)};Z().prototype.log=function(){return this.throwIfDisposed(),kn(this)};Z().prototype.log1p=function(){return this.throwIfDisposed(),ad(this)};Z().prototype.logicalAnd=function(e){return this.throwIfDisposed(),nr(this,e)};Z().prototype.logicalNot=function(){return this.throwIfDisposed(),$u(this)};Z().prototype.logicalOr=function(e){return this.throwIfDisposed(),id(this,e)};Z().prototype.logicalXor=function(e){return this.throwIfDisposed(),l0(this,e)};Z().prototype.matMul=function(e,t,n){return this.throwIfDisposed(),qe(this,e,t,n)};Z().prototype.maxPool=function(e,t,n,r){return this.throwIfDisposed(),Du(this,e,t,n,r)};Z().prototype.max=function(e,t){return this.throwIfDisposed(),Bn(this,e,t)};Z().prototype.maximum=function(e){return this.throwIfDisposed(),Tr(this,e)};Z().prototype.mean=function(e,t){return this.throwIfDisposed(),bt(this,e,t)};Z().prototype.min=function(e,t){return this.throwIfDisposed(),qo(this,e,t)};Z().prototype.minimum=function(e){return this.throwIfDisposed(),Xo(this,e)};Z().prototype.mirrorPad=function(e,t){return this.throwIfDisposed(),Yf(this,e,t)};Z().prototype.mod=function(e){return this.throwIfDisposed(),Qf(this,e)};Z().prototype.mul=function(e){return this.throwIfDisposed(),W(this,e)};Z().prototype.neg=function(){return this.throwIfDisposed(),_t(this)};Z().prototype.norm=function(e,t,n){return this.throwIfDisposed(),_d(this,e,t,n)};Z().prototype.notEqual=function(e){return this.throwIfDisposed(),js(this,e)};Z().prototype.oneHot=function(e,t=1,n=0){return this.throwIfDisposed(),Wo(this,e,t,n)};Z().prototype.onesLike=function(){return this.throwIfDisposed(),In(this)};Z().prototype.pad=function(e,t){return this.throwIfDisposed(),Jr(this,e,t)};Z().prototype.pool=function(e,t,n,r,a){return this.throwIfDisposed(),h0(this,e,t,n,r,a)};Z().prototype.pow=function(e){return this.throwIfDisposed(),Yr(this,e)};Z().prototype.prelu=function(e){return this.throwIfDisposed(),zu(this,e)};Z().prototype.prod=function(e,t){return this.throwIfDisposed(),ld(this,e,t)};Z().prototype.reciprocal=function(){return this.throwIfDisposed(),em(this)};Z().prototype.relu=function(){return this.throwIfDisposed(),Cr(this)};Z().prototype.relu6=function(){return this.throwIfDisposed(),cd(this)};Z().prototype.reshapeAs=function(e){return this.throwIfDisposed(),q(this,e.shape)};Z().prototype.reshape=function(e){return this.throwIfDisposed(),q(this,e)};Z().prototype.resizeBilinear=function(e,t,n){return this.throwIfDisposed(),ix(this,e,t,n)};Z().prototype.resizeNearestNeighbor=function(e,t,n){return this.throwIfDisposed(),ox(this,e,t,n)};Z().prototype.reverse=function(e){return this.throwIfDisposed(),Nn(this,e)};Z().prototype.rfft=function(){return this.throwIfDisposed(),Vu(this)};Z().prototype.round=function(){return this.throwIfDisposed(),tm(this)};Z().prototype.rsqrt=function(){return this.throwIfDisposed(),hd(this)};Z().prototype.selu=function(){return this.throwIfDisposed(),dd(this)};Z().prototype.separableConv2d=function(e,t,n,r,a,s){return this.throwIfDisposed(),nm(this,e,t,n,r,a,s)};Z().prototype.sigmoid=function(){return this.throwIfDisposed(),er(this)};Z().prototype.sign=function(){return this.throwIfDisposed(),rm(this)};Z().prototype.sin=function(){return this.throwIfDisposed(),pd(this)};Z().prototype.sinh=function(){return this.throwIfDisposed(),fd(this)};Z().prototype.slice=function(e,t){return this.throwIfDisposed(),Me(this,e,t)};Z().prototype.softmax=function(e){return this.throwIfDisposed(),Wu(this,e)};Z().prototype.softplus=function(){return this.throwIfDisposed(),Go(this)};Z().prototype.spaceToBatchND=function(e,t){return this.throwIfDisposed(),Ou(this,e,t)};Z().prototype.split=function(e,t){return this.throwIfDisposed(),an(this,e,t)};Z().prototype.sqrt=function(){return this.throwIfDisposed(),Xt(this)};Z().prototype.square=function(){return this.throwIfDisposed(),ot(this)};Z().prototype.squaredDifference=function(e){return this.throwIfDisposed(),gd(this,e)};Z().prototype.squeeze=function(e){return this.throwIfDisposed(),ba(this,e)};Z().prototype.stack=function(e,t){this.throwIfDisposed();let n=e instanceof Qe?[this,e]:[this,...e];return Sn(n,t)};Z().prototype.step=function(e){return this.throwIfDisposed(),Jo(this,e)};Z().prototype.stridedSlice=function(e,t,n,r,a,s,i,o){return this.throwIfDisposed(),sm(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(),Te(this,e,t)};Z().prototype.tan=function(){return this.throwIfDisposed(),im(this)};Z().prototype.tanh=function(){return this.throwIfDisposed(),Vo(this)};Z().prototype.tile=function(e){return this.throwIfDisposed(),wa(this,e)};Z().prototype.toBool=function(){return this.throwIfDisposed(),ye(this,"bool")};Z().prototype.toFloat=function(){return this.throwIfDisposed(),ye(this,"float32")};Z().prototype.toInt=function(){return this.throwIfDisposed(),ye(this,"int32")};Z().prototype.topk=function(e,t){return this.throwIfDisposed(),om(this,e,t)};Z().prototype.transpose=function(e){return this.throwIfDisposed(),at(this,e)};Z().prototype.unique=function(e){return this.throwIfDisposed(),wd(this,e)};Z().prototype.unsortedSegmentSum=function(e,t){return this.throwIfDisposed(),lm(this,e,t)};Z().prototype.unstack=function(e){return this.throwIfDisposed(),rr(this,e)};Z().prototype.where=function(e,t){return this.throwIfDisposed(),fn(e,this,t)};Z().prototype.zerosLike=function(){return this.throwIfDisposed(),He(this)};var Ub={kernelName:zi,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>W(e,Jo(ye(n,"float32"),-1))}}},jK={kernelName:Pi,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let r=ot(ye(n,"float32")),a=Xt(we(Se(1),r));return _t(Ne(e,a))}}}},GK={kernelName:Li,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let r=Xt(we(ot(ye(n,"float32")),1));return Ne(e,r)}}}},qK={kernelName:fa,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t,a=At(n.shape,r.shape);return{a:()=>{let s=e,i=Ot(n.shape,a);return i.length>0&&(s=Te(s,i)),q(s,n.shape)},b:()=>{let s=e,i=Ot(r.shape,a);return i.length>0&&(s=Te(s,i)),q(s,r.shape)}}}},XK={kernelName:Ka,saveAllInputs:!0,gradFunc:(e,t)=>{let n={};return t.forEach((r,a)=>{n[a]=()=>e.clone()}),n}},KK={kernelName:Za,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>He(n)}}},ZK={kernelName:su,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>He(n)}}},JK={kernelName:Wi,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>Ne(e,Xt(we(Se(1),ot(ye(n,"float32")))))}}},YK={kernelName:Bi,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let r=Xt(oe(Se(1),ot(ye(n,"float32"))));return Ne(e,r)}}}},QK={kernelName:Hi,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t,a=At(n.shape,r.shape);return{a:()=>{let s=oe(ot(n),ot(r)),i=W(e,Ne(r,s)),o=Ot(n.shape,a);return o.length>0&&(i=Te(i,o)),q(i,n.shape)},b:()=>{let s=oe(ot(n),ot(r)),i=_t(W(e,Ne(n,s))),o=Ot(r.shape,a);return o.length>0&&(i=Te(i,o)),q(i,r.shape)}}}},eZ={kernelName:Vi,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>Ne(e,oe(ot(ye(n,"float32")),1))}}},tZ={kernelName:Ui,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>Ne(e,we(Se(1),ot(ye(n,"float32"))))}}};function nZ(e,t,n,r,a,s){let i=R(e,"dy","avgPool3dGrad"),o=R(t,"input","avgPool3dGrad"),l=i,c=o,u=!1;o.rank===4&&(u=!0,l=q(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]]),c=q(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),M(l.rank===5,()=>`Error in avgPool3dGrad: dy must be rank 5 but got rank ${l.rank}.`),M(c.rank===5,()=>`Error in avgPool3dGrad: input must be rank 5 but got rank ${c.rank}.`),s!=null&&M(Ut(a),()=>`Error in avgPool3dGrad: pad must be an integer when using, dimRoundingMode ${s} but got pad ${a}.`);let h={dy:l,input:c},d={filterSize:n,strides:r,pad:a,dimRoundingMode:s},p=z.runKernel(mh,h,d);return u?q(p,[p.shape[1],p.shape[2],p.shape[3],p.shape[4]]):p}var rZ=L({avgPool3dGrad_:nZ}),aZ={kernelName:iu,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,{filterSize:a,strides:s,pad:i,dimRoundingMode:o}=n;return{x:()=>rZ(e,r,a,s,i,o)}}};function sZ(e,t,n,r,a){let s=R(e,"dy","avgPoolGrad"),i=R(t,"input","avgPoolGrad");M(i.rank===s.rank,()=>`Rank of input (${i.rank}) does not match rank of dy (${s.rank})`);let o=i,l=s,c=!1;i.rank===3&&(c=!0,o=q(i,[1,i.shape[0],i.shape[1],i.shape[2]]),l=q(s,[1,s.shape[0],s.shape[1],s.shape[2]])),M(l.rank===4,()=>`Error in avgPoolGrad: dy must be rank 4 but got rank ${l.rank}.`),M(o.rank===4,()=>`Error in avgPoolGrad: input must be rank 4 but got rank ${o.rank}.`);let u={dy:l,input:o},h={filterSize:n,strides:r,pad:a},d=z.runKernel(fh,u,h);return c?q(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var iZ=L({avgPoolGrad_:sZ}),oZ={kernelName:Ja,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,{filterSize:a,strides:s,pad:i}=n;return{x:()=>iZ(e,r,a,s,i)}}},lZ={kernelName:Ya,inputsToSave:["a","b"],gradFunc:(e,t,n)=>{let[r,a]=t,{transposeA:s,transposeB:i}=n;return!s&&!i?{a:()=>qe(e,a,!1,!0),b:()=>qe(r,e,!0,!1)}:!s&&i?{a:()=>qe(e,a,!1,!1),b:()=>qe(e,r,!0,!1)}:s&&!i?{a:()=>qe(a,e,!1,!0),b:()=>qe(r,e,!1,!1)}:{a:()=>qe(a,e,!0,!0),b:()=>qe(e,r,!0,!0)}}},uZ={kernelName:ou,gradFunc:(e,t,n)=>{let{blockShape:r,crops:a}=n;return{x:()=>Ou(e,r,a)}}},cZ={kernelName:D2,gradFunc:(e,t,n)=>{let r=n,a=r.inputShape,s=r.shape,i=Array.from(s);for(let l=a.length-1;l>=0;l--)if(a[l]===s[l])i[l]=1;else if(a[l]!==1)throw new Error(`broadcastTo(): [${a}] cannot be broadcast to [${s}].`);let o=[];for(let l=0;l<i.length;l++)i[l]>1&&o.push(l);return{x:()=>Te(e,o,!0)}}},hZ={kernelName:Qa,gradFunc:e=>({x:()=>e.clone()})},dZ={kernelName:ji,gradFunc:e=>({x:()=>He(e)})},pZ={kernelName:ma,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,{clipValueMin:a,clipValueMax:s}=n;return{x:()=>fn(nr(_a(r,a),Hs(r,s)),e,He(e))}}},fZ={kernelName:lu,inputsToSave:["x"],gradFunc:Ub.gradFunc},mZ={kernelName:Gi,saveAllInputs:!0,gradFunc:(e,t,n)=>{let r=t.map(o=>o.shape),{axis:a}=n,s=ar(a,t[0].shape)[0],i=r.map(o=>o[s]);return an(e,i,s).map(o=>()=>o)}},AZ={kernelName:es,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let[r,a]=t,{dilations:s,strides:i,pad:o,dataFormat:l}=n;return M(Ea(s),()=>`Error in gradient of conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${s}'`),{x:()=>Zm(r.shape,e,a,i,o,l),filter:()=>tA(r,e,a.shape,i,o,l)}}},yZ={kernelName:ts,inputsToSave:["dy","filter"],gradFunc:(e,t,n)=>{let[r,a]=t,{strides:s,pad:i,dataFormat:o,dimRoundingMode:l}=n;return{dy:()=>Zr(e,a,s,i,o,1,l),filter:()=>tA(e,r,a.shape,s,i,o,l)}}};function gZ(e,t,n,r,a){let s=e;e.rank===4&&(s=q(e,[1,e.shape[0],e.shape[1],e.shape[2],e.shape[3]]));let i=t;i.rank===4&&(i=q(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]])),M(s.rank===5,()=>`Error in conv3dDerFilter: input must be rank 5, but got shape ${s.shape}.`),M(i.rank===5,()=>`Error in conv3dDerFilter: dy must be rank 5, but got shape ${i.shape}.`),M(n.length===5,()=>`Error in conv3dDerFilter: filterShape must be length 5, but got ${n}.`),M(s.shape[4]===n[3],()=>`Error in conv3dDerFilter: depth of input ${s.shape[4]}) must match input depth in filter (${n[3]}.`),M(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 z.runKernel(xh,o,l)}var xZ=L({conv3DBackpropFilter_:gZ}),wZ={kernelName:uu,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let{dilations:r,strides:a,pad:s}=n;M(Ea(r),()=>`Error in gradient of conv3D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${r}'`);let[i,o]=t;return{x:()=>G5(i.shape,e,o,a,s),filter:()=>xZ(i,e,o.shape,a,s)}}},_Z={kernelName:ns,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>W(_t(pd(ye(n,"float32"))),e)}}},bZ={kernelName:qi,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>W(fd(ye(n,"float32")),e)}}},vZ={kernelName:rs,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,{axis:a,exclusive:s,reverse:i}=n;return{x:()=>{let o=K5([a],r.rank),l=td(e,a,s,!i);return o!=null&&(l=at(l,o)),l}}}},kZ={kernelName:as,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let{dilations:r,strides:a,pad:s,dimRoundingMode:i}=n,o=r==null?[1,1]:r;M(Ea(o),()=>`Error in gradient of depthwiseConv2dNative: dilation rates greater than 1 are not yet supported. Got dilations '${o}'`);let[l,c]=t;return M(l.rank===4,()=>`Error in gradient of depthwiseConv2dNative: input must be rank 4, but got rank ${l.rank}.`),M(c.rank===4,()=>`Error in gradient of depthwiseConv2dNative: filter must be rank 4, but got rank ${c.rank}.`),M(l.shape[3]===c.shape[2],()=>`Error in gradient of depthwiseConv2d: number of input channels (${l.shape[3]}) must match the inChannels dimension in filter ${c.shape[2]}.`),M(zr(a,o),()=>`Error in gradient of depthwiseConv2d: Either strides or dilations must be 1. Got strides ${a} and dilations '${o}'.`),i!=null&&M(Ut(s),()=>`Error in depthwiseConv2d: pad must be an integer when using, dimRoundingMode ${i} but got pad ${s}.`),{x:()=>Q5(l.shape,e,c,a,s,r,i),filter:()=>Y5(l,e,c.shape,a,s,r,i)}}},IZ={kernelName:cu,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let[r,a]=t,s={x:r,filter:a,dy:e},i={x:r,filter:a,dy:e};return{x:()=>z.runKernel(Ih,s,n),filter:()=>z.runKernel(Nh,i,n)}}},NZ={kernelName:Zi,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t,r={dy:e,y:n};return{x:()=>z.runKernel(Sh,r)}}},SZ={kernelName:Ji,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t,r=W(Wn(_t(ot(n))),2/Math.sqrt(Math.PI));return{x:()=>W(e,r)}}},TZ={kernelName:is,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t;return{x:()=>W(e,n)}}},EZ={kernelName:Qi,inputsToSave:["input"],gradFunc:(e,t)=>{let[n]=t;return{input:()=>q(e,n.shape)}}},CZ={kernelName:eo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>W(e,Wn(n))}}},RZ={kernelName:os,gradFunc:e=>({x:()=>He(e)})},FZ={kernelName:ls,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t,a=At(n.shape,r.shape);return{a:()=>{let s=Ne(e,ye(r,"float32")),i=Ot(n.shape,a);return i.length>0?q(Te(s,i),n.shape):s},b:()=>{let s=W(e,ye(n,"float32")),i=Ot(r.shape,a);i.length>0&&(s=q(Te(s,i),r.shape));let o=ot(r);return _t(Ne(s,ye(o,"float32")))}}}},MZ={kernelName:us,inputsToSave:["x","mean","variance","scale"],gradFunc:(e,t,n)=>{let{varianceEpsilon:r}=n,[a,s,i,o]=t,l=o==null?Se(1):o,c=Ot(s.shape,a.shape),u=[];if(s.rank===1){for(let m=0;m<a.shape.length-1;++m)u.push(a.shape[m]);u.push(1)}let h=we(a,s),d=W(e,l),p=hd(oe(i,Se(r))),f=W(W(W(p,p),p),Se(-.5));return{x:()=>s.rank===1?q(W(W(e,wa(q(p,[1,1,1,s.shape[0]]),u)),l),a.shape):q(W(W(e,p),l),a.shape),mean:()=>{let m=W(W(p,Se(-1)),d);return s.rank===1&&(m=Te(m,c)),q(m,s.shape)},variance:()=>{let m=W(W(f,h),d);return s.rank===1&&(m=Te(m,c)),q(m,s.shape)},scale:()=>{let m=W(h,p),A=W(e,m);return s.rank===1&&(A=Te(A,c)),q(A,s.shape)},offset:()=>{let m=e;return s.rank===1&&(m=Te(m,c)),q(m,s.shape)}}}},$Z={kernelName:no,inputsToSave:["x","indices"],gradFunc:(e,t,n)=>{let[r,a]=t,{axis:s}=n,i=ar(s,r.shape)[0];return{x:()=>{let o=r.shape,l=a.size,c=o.slice(0,i),u=c.length,h=o.slice(s,o.length).slice(1),d=h.length,p=Hb(0,u),f=Hb(u+1,u+1+d),m=jb([c,[l],h]),A=q(e,m),y=q(a,[l]),g=jb([[u],p,f]),w=at(A,g),x=lm(w,y,r.shape[i]),_=Ym(g);return x=at(x,_),x},indices:()=>a}}};function Hb(e,t){let n=[];for(let r=e;r<t;++r)n.push(r);return n}function jb(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 DZ={kernelName:cs,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t;return{a:()=>He(n),b:()=>He(r)}}},OZ={kernelName:so,gradFunc:e=>({x:()=>ye(e,"float32")})},zZ={kernelName:io,gradFunc:e=>({x:()=>He(e)})},PZ={kernelName:oo,gradFunc:e=>({x:()=>He(e)})},LZ={kernelName:lo,gradFunc:e=>({x:()=>He(e)})},WZ={kernelName:hs,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,{alpha:a}=n,s=tr(r,0);return{x:()=>fn(s,e,W(e,a))}}},BZ={kernelName:ho,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>Ne(e,oe(n,1))}}},VZ={kernelName:ds,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>Ne(e,ye(n,"float32"))}}},UZ={kernelName:O2,inputsToSave:[],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[r]=t,{axis:a}=n;return{logits:()=>{let s=!0,i=Wn(r);return we(e,W(Te(e,a,s),i))}}}};function HZ(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 z.runKernel(Fh,o,l)}var jZ=L({localResponseNormalizationBackprop_:HZ}),GZ={kernelName:fu,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[r,a]=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n;return{x:()=>jZ(r,a,e,s,i,o,l)}}};function Gb(e,t,n,r){return t.rank<n.rank&&(t=q(t,ei(t.shape,r))),e.rank<n.rank&&(e=q(e,ei(e.shape,r))),{x:()=>W(e,ye(xa(n,t),e.dtype))}}var qb={kernelName:ps,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let r=n,{reductionIndices:a}=r,s=t[0],i=t[1],o=ar(a,s.shape),l=Gb(e,i,s,o);return{x:()=>l.x()}}},qZ={kernelName:fs,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t;return{a:()=>W(e,ye(_a(n,r),"float32")),b:()=>W(e,ye(rd(n,r),"float32"))}}};function XZ(e,t,n,r,a,s,i){let o=R(e,"dy","maxPool3dGrad"),l=R(t,"input","maxPool3dGrad"),c=R(n,"output","maxPool3dGrad"),u=o,h=l,d=c,p=!1;l.rank===4&&(p=!0,u=q(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]]),h=q(l,[1,l.shape[0],l.shape[1],l.shape[2],l.shape[3]]),d=q(c,[1,c.shape[0],c.shape[1],c.shape[2],c.shape[3]])),M(u.rank===5,()=>`Error in maxPool3dGrad: dy must be rank 5 but got rank ${u.rank}.`),M(h.rank===5,()=>`Error in maxPool3dGrad: input must be rank 5 but got rank ${h.rank}.`),M(d.rank===5,()=>`Error in maxPool3dGrad: output must be rank 5 but got rank ${d.rank}.`),i!=null&&M(Ut(s),()=>`Error in maxPool3dGrad: pad must be an integer when using, dimRoundingMode ${i} but got pad ${s}.`);let f={dy:u,input:h,output:d},m={filterSize:r,strides:a,pad:s,dimRoundingMode:i},A=z.runKernel($h,f,m);return p?q(A,[A.shape[1],A.shape[2],A.shape[3],A.shape[4]]):A}var KZ=L({maxPool3dGrad_:XZ}),ZZ={kernelName:mu,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[r,a]=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n;return{x:()=>KZ(e,r,a,s,i,o,l)}}};function JZ(e,t,n,r,a,s,i){let o=R(e,"dy","maxPoolGrad"),l=R(t,"input","maxPoolGrad"),c=R(n,"output","maxPoolGrad");M(l.rank===o.rank,()=>`Rank of input (${l.rank}) does not match rank of dy (${o.rank})`),M(o.rank===4,()=>`Error in maxPoolGrad: dy must be rank 4 but got rank ${o.rank}.`),M(l.rank===4,()=>`Error in maxPoolGrad: input must be rank 4 but got rank ${l.rank}.`),i!=null&&M(Ut(s),()=>`Error in maxPoolGrad: pad must be an integer when using, dimRoundingMode ${i} but got pad ${s}.`);let u={dy:o,input:l,output:c},h={filterSize:r,strides:a,pad:s,dimRoundingMode:i};return z.runKernel(Mh,u,h)}var YZ=L({maxPoolGrad_:JZ}),QZ={kernelName:ms,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[r,a]=t,{filterSize:s,strides:i,pad:o}=n;return{x:()=>YZ(e,r,a,s,i,o)}}},eJ={kernelName:As,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,{axis:a}=n,s=ar(a,r.shape),i=X5(r.shape,s)[1],o=Dt(i);return{x:()=>{let l=r.shape.slice();s.forEach(u=>{l[u]=1});let c=q(e,l);return Ne(W(c,Er(r.shape,"float32")),o)}}}},tJ={kernelName:ys,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let r=n,{axis:a}=r,[s,i]=t,o=ar(a,s.shape),l=Gb(e,i,s,o);return{x:()=>l.x()}}},nJ={kernelName:gs,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t;return{a:()=>W(e,ye(Hs(n,r),"float32")),b:()=>W(e,ye(tr(n,r),"float32"))}}},rJ={kernelName:Au,inputsToSave:["x"],gradFunc:(e,t,n)=>{let r=t[0],{paddings:a}=n,s=a.map(i=>i[0]);return{x:()=>Me(e,s,r.shape)}}},aJ={kernelName:fo,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t,a=At(n.shape,r.shape);return{a:()=>{let s=Ot(n.shape,a);return s.length>0?q(Te(e,s),n.shape):e},b:()=>{let s=W(e,_t(jo(Ne(n,r)))),i=Ot(r.shape,a);return i.length>0?q(Te(s,i),r.shape):s}}}},sJ={kernelName:xs,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t,a=At(n.shape,r.shape);return{a:()=>{let s=W(e,ye(r,"float32")),i=Ot(n.shape,a);return i.length>0?q(Te(s,i),n.shape):s},b:()=>{let s=W(e,ye(n,"float32")),i=Ot(r.shape,a);return i.length>0?q(Te(s,i),r.shape):s}}}},iJ={kernelName:mo,gradFunc:e=>({x:()=>_t(e)})},oJ={kernelName:ws,inputsToSave:["indices"],gradFunc:(e,t)=>{let n=t[0];return{indices:()=>Ct(n.shape,"float32")}}},lJ={kernelName:wo,gradFunc:e=>({x:()=>He(e)})},uJ={kernelName:_o,saveAllInputs:!0,gradFunc:(e,t,n)=>{let{axis:r}=n;return rr(e,r).map(a=>()=>a)}},Xb={kernelName:_s,inputsToSave:["x"],gradFunc:(e,t,n)=>{let r=t[0],{paddings:a}=n,s=a.map(i=>i[0]);return{x:()=>Me(e,s,r.shape)}}},cJ={kernelName:bs,inputsToSave:["a","b"],outputsToSave:[!0],gradFunc:(e,t)=>{let[n,r,a]=t,s=n,i=r,o=At(s.shape,i.shape);return{a:()=>{let l=ye(i,"float32"),c=W(e,W(l,Yr(s,we(l,Se(1))))),u=Ot(s.shape,o);return u.length>0&&(c=Te(c,u)),q(c,s.shape)},b:()=>{let l=tr(s,0),c=fn(l,kn(s),He(s)),u=W(e,W(a,c)),h=Ot(i.shape,o);return h.length>0&&(u=Te(u,h)),q(u,i.shape)}}}},hJ={kernelName:vs,inputsToSave:["x","alpha"],gradFunc:(e,t)=>{let[n,r]=t,a=tr(n,0);return{x:()=>fn(a,e,W(e,r)),alpha:()=>{let s=fn(a,He(e),W(e,n)),i=Ot(r.shape,e.shape);return i.length>0&&(s=Te(s,i)),q(s,r.shape)}}}},dJ={kernelName:ss,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t,a=At(n.shape,r.shape);return{a:()=>{let s=Ne(e,ye(r,"float32")),i=Ot(n.shape,a);return i.length>0?q(Te(s,i),n.shape):s},b:()=>{let s=W(e,ye(n,"float32")),i=Ot(r.shape,a);i.length>0&&(s=q(Te(s,i),r.shape));let o=ot(r);return _t(Ne(s,ye(o,"float32")))}}}},pJ={kernelName:vo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>Ne(e,_t(ot(n)))}}},fJ={kernelName:Ns,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t,r=W(Hs(n,6),Jo(n));return{x:()=>W(e,ye(r,"float32"))}}},mJ={kernelName:ks,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>W(e,ye(Jo(n),"float32"))}}},AJ={kernelName:ko,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>q(e,n.shape)}}},yJ={kernelName:Is,inputsToSave:["images"],gradFunc:(e,t,n)=>{let[r]=t,a={dy:e,images:r};return{images:()=>z.runKernel(Lh,a,n)}}},gJ={kernelName:gu,inputsToSave:["images"],gradFunc:(e,t,n)=>{let[r]=t,a={dy:e,images:r};return{images:()=>z.runKernel(Ph,a,n)}}},xJ={kernelName:Ss,gradFunc:(e,t,n)=>{let{dims:r}=n,a=ar(r,e.shape);return{x:()=>Nn(e,a)}}},wJ={kernelName:Ts,gradFunc:e=>({x:()=>He(e)})},_J={kernelName:Es,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>_t(Ne(e,W(Yr(n,1.5),2)))}}},bJ={kernelName:No,inputsToSave:["condition"],gradFunc:(e,t)=>{let[n]=t;return{condition:()=>ye(He(n),"float32"),t:()=>W(e,ye(n,e.dtype)),e:()=>W(e,ye($u(n),e.dtype))}}},vJ={kernelName:So,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let r=tr(n,Se(0)),a=Se(ux),s=Se(cx),i=W(e,s),o=W(W(e,a),Wn(ye(n,"float32")));return fn(r,i,o)}}}},kJ={kernelName:Rs,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t;return{x:()=>W(e,W(n,we(Se(1),n)))}}},IJ={kernelName:Co,gradFunc:e=>({x:()=>He(e)})},NJ={kernelName:Cs,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>W(Ru(ye(n,"float32")),e)}}},SJ={kernelName:Eo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>W(ed(ye(n,"float32")),e)}}},TJ={kernelName:To,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,{begin:a,size:s}=n,i=r.shape,[o,l]=z5(r,a,s),c=[];for(let u=0;u<e.rank;u++)c.push([o[u],i[u]-o[u]-l[u]]);return{x:()=>Jr(e,c)}}},EJ={kernelName:$s,outputsToSave:[!0],gradFunc:(e,t,n)=>{let[r]=t,{dim:a}=n,s=!0,i=W(e,r);return{logits:()=>we(i,W(Te(i,[a],s),r))}}},CJ={kernelName:Ro,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>W(e,er(n))}}},Kb={kernelName:xu,gradFunc:(e,t,n)=>{let{blockShape:r,paddings:a}=n;return{x:()=>Eu(e,r,a)}}},Zb={kernelName:Fo,gradFunc:(e,t,n)=>{let{axis:r}=n;return{x:()=>ct(e,r)}}},RJ={kernelName:Fs,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>Ne(e,W(Xt(ye(n,"float32")),2))}}},FJ={kernelName:wu,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>W(e,W(ye(n,"float32"),2))}}},MJ={kernelName:Ds,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t,a=Se(2);return{a:()=>W(e,W(a,we(n,r))),b:()=>W(e,W(a,we(r,n)))}}},$J={kernelName:ya,gradFunc:e=>({x:()=>He(e)})},DJ={kernelName:Os,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,r]=t,a=At(n.shape,r.shape);return{a:()=>{let s=e,i=Ot(n.shape,a);return i.length>0&&(s=Te(s,i)),q(s,n.shape)},b:()=>{let s=e,i=Ot(r.shape,a);return i.length>0&&(s=Te(s,i)),q(_t(s),r.shape)}}}},OJ={kernelName:Ms,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,a=r.shape.slice(),{axis:s}=n;ar(s,r.shape).forEach(l=>{a[l]=1});let i=q(e,a),o=W(i,Er(r.shape,"float32"));return{x:()=>o}}},zJ={kernelName:$o,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>Ne(e,ot(Ru(n)))}}},PJ={kernelName:zs,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t;return{x:()=>W(we(Se(1),ot(n)),e)}}},LJ={kernelName:Aa,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[r]=t,{reps:a}=n;return{x:()=>{let s=He(r);if(r.rank===1)for(let i=0;i<a[0];++i)s=oe(s,Me(e,[i*r.shape[0]],[r.shape[0]]));else if(r.rank===2)for(let i=0;i<a[0];++i)for(let o=0;o<a[1];++o)s=oe(s,Me(e,[i*r.shape[0],o*r.shape[1]],[r.shape[0],r.shape[1]]));else if(r.rank===3)for(let i=0;i<a[0];++i)for(let o=0;o<a[1];++o)for(let l=0;l<a[2];++l)s=oe(s,Me(e,[i*r.shape[0],o*r.shape[1],l*r.shape[2]],[r.shape[0],r.shape[1],r.shape[2]]));else if(r.rank===4)for(let i=0;i<a[0];++i)for(let o=0;o<a[1];++o)for(let l=0;l<a[2];++l)for(let c=0;c<a[3];++c)s=oe(s,Me(e,[i*r.shape[0],o*r.shape[1],l*r.shape[2],c*r.shape[3]],[r.shape[0],r.shape[1],r.shape[2],r.shape[3]]));else throw new Error(`Gradient for tile operation is not implemented for rank-${r.rank} tensors yet.`);return s}}}},WJ={kernelName:Ps,gradFunc:(e,t,n)=>{let r=n,{perm:a}=r,s=Ym(a);return{x:()=>at(e,s)}}},BJ={kernelName:Oo,gradFunc:(e,t,n)=>{let r=n,{axis:a}=r;return{value:()=>Sn(e,a)}}},UJ={kernelName:_u,inputsToSave:["segmentIds"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>VJ(e,n)}}};function VJ(e,t){let n=Tr(t,He(t)),r=Us(e,n),a=_a(t,Se(0,"int32")),s=r.rank-a.rank;for(let o=0;o<s;++o)a=vn(a,o+1);a=nr(a,Er(r.shape,"bool"));let i=He(r);return fn(a,r,i)}var HJ={kernelName:zo,gradFunc:e=>({x:()=>He(e)})},jJ=[Ub,jK,GK,qK,XK,KK,ZK,JK,YK,QK,eZ,tZ,aZ,oZ,lZ,uZ,cZ,hZ,dZ,pZ,fZ,mZ,yZ,AZ,wZ,_Z,bZ,vZ,kZ,IZ,dJ,NZ,SZ,TZ,EZ,CZ,FZ,RZ,MZ,$Z,DZ,OZ,zZ,PZ,LZ,WZ,BZ,VZ,UZ,GZ,qb,qb,qZ,ZZ,QZ,eJ,tJ,nJ,rJ,aJ,sJ,iJ,oJ,lJ,uJ,Xb,Xb,cJ,hJ,pJ,fJ,mJ,AJ,yJ,gJ,xJ,wJ,_J,bJ,vJ,kJ,IJ,NJ,SJ,TJ,EJ,CJ,Kb,Kb,Zb,Zb,RJ,MJ,FJ,$J,DJ,OJ,zJ,PJ,LJ,WJ,BJ,UJ,HJ];for(let e of jJ)z2(e);var E0={};ze(E0,{maxNorm:()=>GJ,minMaxNorm:()=>KJ,nonNeg:()=>XJ,unitNorm:()=>qJ});var UA;function zt(){return UA==null&&(UA=Rf().epsilon()),UA}function gr(){return"channelsLast"}var sa=class extends Error{constructor(e){super(e);Object.setPrototypeOf(this,sa.prototype)}},xr=class extends Error{constructor(e){super(e);Object.setPrototypeOf(this,xr.prototype)}},B=class extends Error{constructor(e){super(e);Object.setPrototypeOf(this,B.prototype)}},De=class extends Error{constructor(e){super(e);Object.setPrototypeOf(this,De.prototype)}},Jb=class extends Error{constructor(e){super(e);Object.setPrototypeOf(this,Jb.prototype)}},ZJ=class extends Error{constructor(e){super(e);Object.setPrototypeOf(this,ZJ.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 Wr(e,t){if(!e)throw new Jb(t)}function Yb(e,t){let n=0;for(let r of e)r===t&&n++;return n}function An(e){return e.length===1?e[0]:e}function mt(e){return Array.isArray(e)?e:[e]}function ia(e){let t=e.replace(/(.)([A-Z][a-z0-9]+)/g,"$1_$2").replace(/([a-z])([A-Z])/g,"$1_$2").toLowerCase();return t[0]!=="_"?t:"private"+t}function hi(e){return e.length<=1||e.indexOf("_")===-1?e:e.replace(/[_]+(\w|$)/g,(t,n)=>n.toUpperCase())}var ir={};function HA(e){if(e==null)return null;let t={};return t.className=e.getClassName(),t.config=e.getConfig(),t}function jA(e){if(!(e==null||typeof e!="object"))if(Array.isArray(e))e.forEach(t=>jA(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:jA(r))}}}function gc(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 ir)i=ir[s];else if(i=t[s],i==null)throw new B(`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 ${r} is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().`);return i}else{let s=e;if(s.className==null||s.config==null)throw new B(`${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 ir?[o,l]=ir.className:i in t&&([o,l]=t[i]),o==null)throw new B(`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 c={};for(let p of Object.keys(ir))c[p]=ir[p];for(let p of Object.keys(n))c[p]=n[p];let u=s.config;u.customObjects=c;let h=Object.assign({},ir);for(let p of Object.keys(n))ir[p]=n[p];jA(s.config);let d=l(o,s.config,n,a);return ir=Object.assign({},h),d}else{let c=Object.assign({},ir);for(let h of Object.keys(n))ir[h]=n[h];let u=new o(s.config);return ir=Object.assign({},c),u}}}function JJ(e,t){return e<t?-1:e>t?1:0}function Ap(e,t){return-1*JJ(e,t)}function Ma(e){if(e==null)return e;let t=[];for(let n of e)t.indexOf(n)===-1&&t.push(n);return t}function YJ(e){if(e==null)throw new B(`Invalid value in obj: ${JSON.stringify(e)}`);for(let t in e)if(e.hasOwnProperty(t))return!1;return!0}function di(e,t,n){if(n!=null&&e.indexOf(n)<0)throw new B(`${n} is not a valid ${t}. Valid values are ${e} or null/undefined.`)}function GA(e,t,n=0,r=Infinity){return Wr(n>=0),Wr(r>=n),Array.isArray(e)&&e.length>=n&&e.length<=r&&e.every(a=>typeof a===t)}function jt(e,t){Array.isArray(e)?(v.assert(e.length>0,()=>`${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 ${Qb(e)}.`)}function Qb(e){return e===null?"null":Array.isArray(e)?"["+e.map(t=>Qb(t)).join(",")+"]":typeof e=="string"?`"${e}"`:`${e}`}function QJ(e,t){let n=v.now(),r;return(...a)=>{let s=v.now();return s-n<t||(n=s,r=e(...a)),r}}function e3(e){return e==="relu"?"relu":e==="linear"?"linear":e==="elu"?"elu":null}function qA(e,t){return U(()=>Xt(Te(W(e,e),t,!0)))}var xc=class extends re.Serializable{getConfig(){return{}}},XA=class extends xc{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 U(()=>{let t=qA(e,this.axis),n=pn(t,0,this.maxValue);return W(e,Ne(n,oe(zt(),t)))})}getConfig(){return{maxValue:this.maxValue,axis:this.axis}}};XA.className="MaxNorm";re.registerClass(XA);var KA=class extends xc{constructor(e){super();this.defaultAxis=0,this.axis=e.axis!=null?e.axis:this.defaultAxis}apply(e){return U(()=>Ne(e,oe(zt(),qA(e,this.axis))))}getConfig(){return{axis:this.axis}}};KA.className="UnitNorm";re.registerClass(KA);var ZA=class extends xc{apply(e){return Cr(e)}};ZA.className="NonNeg";re.registerClass(ZA);var JA=class extends xc{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 U(()=>{let t=qA(e,this.axis),n=oe(W(this.rate,pn(t,this.minValue,this.maxValue)),W(1-this.rate,t));return W(e,Ne(n,oe(zt(),t)))})}getConfig(){return{minValue:this.minValue,maxValue:this.maxValue,rate:this.rate,axis:this.axis}}};JA.className="MinMaxNorm";re.registerClass(JA);var t3={maxNorm:"MaxNorm",minMaxNorm:"MinMaxNorm",nonNeg:"NonNeg",unitNorm:"UnitNorm"};function Pt(e){return HA(e)}function n3(e,t={}){return gc(e,re.SerializationMap.getMap().classNameMap,t,"constraint")}function Lt(e){if(e==null)return null;if(typeof e=="string"){let t={className:e in t3?t3[e]:e,config:{}};return n3(t)}else return e instanceof xc?e:n3(e)}function GJ(e){return new XA(e)}function qJ(e){return new KA(e)}function XJ(){return new ZA}function KJ(e){return new JA(e)}var C0={};ze(C0,{constant:()=>nY,glorotNormal:()=>uY,glorotUniform:()=>lY,heNormal:()=>cY,heUniform:()=>hY,identity:()=>iY,leCunNormal:()=>dY,leCunUniform:()=>pY,ones:()=>tY,orthogonal:()=>fY,randomNormal:()=>aY,randomUniform:()=>rY,truncatedNormal:()=>sY,varianceScaling:()=>oY,zeros:()=>eY});var mY=["channelsFirst","channelsLast"],AY=["nearest","bilinear"],yY=["valid","same","causal"],gY=["max","avg"],xY=["sum","mul","concat","ave"],Il=new Map;function Tt(e){di(mY,"DataFormat",e)}function wY(e){di(AY,"InterpolationFormat",e)}function jn(e){di(yY,"PaddingMode",e)}function r3(e){di(gY,"PoolMode",e)}var wc=[],a3="/";function pi(e,t){wc.push(e);try{let n=t();return wc.pop(),n}catch(n){throw wc.pop(),n}}function _Y(){return wc.length===0?"":wc.join(a3)+a3}function i3(e){if(!s3(e))throw new Error("Not a valid tensor name: '"+e+"'");return _Y()+e}function o3(e){if(!s3(e))throw new Error("Not a valid tensor name: '"+e+"'");Il.has(e)||Il.set(e,0);let t=Il.get(e);if(Il.set(e,Il.get(e)+1),t>0){let n=`${e}_${t}`;return Il.set(n,1),n}else return e}var bY=new RegExp(/^[A-Za-z0-9][-A-Za-z0-9\._\/]*$/);function s3(e){return!!e.match(bY)}function vY(e){return e===parseInt(e.toString(),10)}function $a(e,t,n){t==null&&(t=0),n==null&&(n=e.length);let r=1;for(let a=t;a<n;++a)r*=e[a];return r}function l3(e){return e=Array.isArray(e)?new Float32Array(e):e,Qt(e)}function Nl(e){return qo(l3(e)).dataSync()[0]}function Da(e){return Bn(l3(e)).dataSync()[0]}function wr(e,t){if(t<e)throw new B(`end (${t}) < begin (${e}) is forbidden.`);let n=[];for(let r=e;r<t;++r)n.push(r);return n}function _c(e,t){return e.asType(t)}function bc(e,t=-1){let n=e.shape.slice();return t<0&&(t=n.length+t+1),n.splice(t,0,1),e.reshape(n)}function kY(e,t){return U(()=>{if(e.shape.length!==2)throw new B(`repeat() expects a rank-2 tensor, but received a rank-${e.shape.length} tensor.`);let n=bc(e,1);return YA(n,[1,t,1])})}function IY(e){let t=[$a(e.shape)];return e.reshape(t)}function NY(e){if(e.rank<=1)throw new B(`batchFlatten requires a minimum rank of 2. Got rank: ${e.rank}.`);let t=[e.shape[0],$a(e.shape,1)];return e.reshape(t)}function fi(e,t,n){return U(()=>{switch(e.rank){case 1:return md(e,t,n);case 2:return am(e,[t,0],[n,e.shape[1]]);case 3:return Ad(e,[t,0,0],[n,e.shape[1],e.shape[2]]);case 4:return Lu(e,[t,0,0,0],[n,e.shape[1],e.shape[2],e.shape[3]]);case 5:return Me(e,[t,0,0,0,0],[n,e.shape[1],e.shape[2],e.shape[3],e.shape[4]]);case 6:return Me(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 B(`sliceAlongFirstAxis() received an unsupported tensor rank: ${e.rank}`)}})}function QA(e,t,n){return U(()=>{switch(e.rank){case 1:return md(e,t,n);case 2:return am(e,[0,t],[e.shape[0],n]);case 3:return Ad(e,[0,0,t],[e.shape[0],e.shape[1],n]);case 4:return Lu(e,[0,0,0,t],[e.shape[0],e.shape[1],e.shape[2],n]);default:throw new B(`sliceAlongLastAxis() received an unsupported tensor rank: ${e.rank}`)}})}function yp(e,t,n,r){return U(()=>{switch(e.rank){case 1:return md(e,t,n);case 2:switch(r){case 1:return fi(e,t,n);case 2:return QA(e,t,n);default:throw new B(`The axis is not within the rank of the tensor ${r}`)}case 3:switch(r){case 1:return fi(e,t,n);case 2:return Ad(e,[0,t,0],[e.shape[0],n,e.shape[2]]);case 3:return QA(e,t,n);default:throw new B(`The axis is not within the rank of the tensor ${r}`)}case 4:switch(r){case 1:return fi(e,t,n);case 2:return Lu(e,[0,t,0,0],[e.shape[0],n,e.shape[2],e.shape[3]]);case 3:return Lu(e,[0,0,t,0],[e.shape[0],e.shape[1],n,e.shape[3]]);case 4:return QA(e,t,n);default:throw new B(`The axis is not within the rank of the tensor ${r}`)}default:throw new B(`sliceAlongLastAxis() received an unsupported tensor rank: ${e.rank}`)}})}function ey(e,t=-1){let n;return t<0&&(n=e[0].rank,n!==0?t=n:t=0),t===e[0].rank&&(t=-1),ct(e,t)}function u3(e,t){switch(e.rank){case 1:return J2([e,t]);case 2:return Jh([e,t],0);case 3:return Y2([e,t],0);case 4:return Q2([e,t],0);default:throw new B(`concatAlongFirstAxis() received an unsupported tensor rank: ${e.rank}`)}}function YA(e,t){if(Array.isArray(t)||(t=[t]),e.rank!==t.length)throw new B(`The length of input n (${t.length}) does not match the number of dimensions in input x (${e.rank})`);return wa(e,t)}function gp(e,t=0,n=1,r,a){return d0(e,t,n,r,a)}function Br(e,t,n,r){if(e.rank<2||t.rank<2)throw new De(`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 De(`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 va.matMul({a:e,b:t,transposeA:a,transposeB:s,bias:r?ty(e.rank,r,gr()):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(),c=[...i,o],u=Array.from({length:t.rank},(f,m)=>m===0?t.rank-2:m<=t.rank-2?m-1:m);t=t.transpose(u).reshape([l,-1]);let h=[...a,...c],d=!1,p=!1;return va.matMul({a:e,b:t,transposeA:d,transposeB:p,bias:r?ty(e.rank,r,gr()):null,activation:n}).reshape(h)}}function c3(e,t,n){return U(()=>(Array.isArray(t)?t=Qt(t,"int32"):t=t.toInt(),Us(e,t,n)))}function vc(e){return W(e,e)}function ty(e,t,n){let r=t.shape;if(t.rank!==1&&t.rank!==e)throw new B(`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 B(`Unsupported input rank by biasAdd: ${t.rank}`)}function Vr(e,t,n){return U(()=>(n==null&&(n=gr()),Tt(n),e.add(ty(e.rank,t,n))))}function SY(e,t=1){if(t!==1)throw new De(`Support for alpha values other than 1 (${t}) is not implemented yet.`);return Ho(e)}function TY(e){return U(()=>Ne(e,$t(e).add(1)))}function h3(e,t,n,r){return U(()=>y0(e,t,n,r))}function EY(e){return U(()=>{let t=oe(.5,W(.2,e));return pn(t,0,1)})}function kc(e,t,n=!1){return n?e():t()}var CY=["fanIn","fanOut","fanAvg"],RY=["normal","uniform","truncatedNormal"];function FY(e){di(CY,"FanMode",e)}function MY(e){di(RY,"Distribution",e)}var or=class extends re.Serializable{fromConfigUsesCustomObjects(){return!1}getConfig(){return{}}},ny=class extends or{apply(e,t){return Ct(e,t)}};ny.className="Zeros";re.registerClass(ny);var xp=class extends or{apply(e,t){return Er(e,t)}};xp.className="Ones";re.registerClass(xp);var ry=class extends or{constructor(e){super();if(typeof e!="object")throw new B(`Expected argument of type ConstantConfig but got ${e}`);if(e.value===void 0)throw new B(`config must have value set but got ${e}`);this.value=e.value}apply(e,t){return U(()=>W(Se(this.value),Er(e,t)))}getConfig(){return{value:this.value}}};ry.className="Constant";re.registerClass(ry);var ay=class extends or{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 Ko(e,this.minval,this.maxval,t)}getConfig(){return{minval:this.minval,maxval:this.maxval,seed:this.seed}}};ay.className="RandomUniform";re.registerClass(ay);var sy=class extends or{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 De(`randomNormal does not support dType ${t}.`);return gp(e,this.mean,this.stddev,t,this.seed)}getConfig(){return{mean:this.mean,stddev:this.stddev,seed:this.seed}}};sy.className="RandomNormal";re.registerClass(sy);var iy=class extends or{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 De(`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}}};iy.className="TruncatedNormal";re.registerClass(iy);var oy=class extends or{constructor(e){super();this.gain=e.gain!=null?e.gain:1}apply(e,t){return U(()=>{if(e.length!==2||e[0]!==e[1])throw new B("Identity matrix initializer can only be used for 2D square matrices.");return W(this.gain,Xf(e[0]))})}getConfig(){return{gain:this.gain}}};oy.className="Identity";re.registerClass(oy);function $Y(e,t="channelsLast"){let n,r;if(Tt(t),e.length===2)n=e[0],r=e[1];else if([3,4,5].indexOf(e.length)!==-1){if(t==="channelsFirst"){let a=$a(e,2);n=e[1]*a,r=e[0]*a}else if(t==="channelsLast"){let a=$a(e,0,e.length-2);n=e[e.length-2]*a,r=e[e.length-1]*a}}else{let a=$a(e);n=Math.sqrt(a),r=Math.sqrt(a)}return[n,r]}var yn=class extends or{constructor(e){super();if(e.scale<0)throw new B(`scale must be a positive float. Got: ${e.scale}`);this.scale=e.scale==null?1:e.scale,this.mode=e.mode==null?"fanIn":e.mode,FY(this.mode),this.distribution=e.distribution==null?"normal":e.distribution,MY(this.distribution),this.seed=e.seed}apply(e,t){let n=$Y(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 De(`${this.getClassName()} does not support dType ${t}.`);return xd(e,0,i,t,this.seed)}else{let i=Math.sqrt(3*s);return Ko(e,-i,i,t)}}getConfig(){return{scale:this.scale,mode:this.mode,distribution:this.distribution,seed:this.seed}}};yn.className="VarianceScaling";re.registerClass(yn);var wp=class extends yn{constructor(e){super({scale:1,mode:"fanAvg",distribution:"uniform",seed:e==null?null:e.seed})}getClassName(){return yn.className}};wp.className="GlorotUniform";re.registerClass(wp);var _p=class extends yn{constructor(e){super({scale:1,mode:"fanAvg",distribution:"normal",seed:e==null?null:e.seed})}getClassName(){return yn.className}};_p.className="GlorotNormal";re.registerClass(_p);var bp=class extends yn{constructor(e){super({scale:2,mode:"fanIn",distribution:"normal",seed:e==null?null:e.seed})}getClassName(){return yn.className}};bp.className="HeNormal";re.registerClass(bp);var vp=class extends yn{constructor(e){super({scale:2,mode:"fanIn",distribution:"uniform",seed:e==null?null:e.seed})}getClassName(){return yn.className}};vp.className="HeUniform";re.registerClass(vp);var kp=class extends yn{constructor(e){super({scale:1,mode:"fanIn",distribution:"normal",seed:e==null?null:e.seed})}getClassName(){return yn.className}};kp.className="LeCunNormal";re.registerClass(kp);var Ip=class extends yn{constructor(e){super({scale:1,mode:"fanIn",distribution:"uniform",seed:e==null?null:e.seed})}getClassName(){return yn.className}};Ip.className="LeCunNormal";re.registerClass(Ip);var ly=class extends or{constructor(e){super();if(this.DEFAULT_GAIN=1,this.gain=e.gain==null?this.DEFAULT_GAIN:e.gain,this.seed=e.seed,this.seed!=null)throw new De("Random seed is not implemented for Orthogonal Initializer yet.")}apply(e,t){return U(()=>{if(e.length<2)throw new De("Shape must be at least 2D.");e[0]*e[1]>2e3&&console.warn(`Orthogonal initializer is being called on a matrix with more than 2000 (${e[0]*e[1]}) elements: Slowness may result.`);let n=e[0]>e[1]?[e[1],e[0]]:e,r=gp(n,0,1,"float32"),a=x0.gramSchmidt(r);return e[0]>e[1]&&(a=a.transpose()),W(this.gain,a)})}getConfig(){return{gain:this.gain,seed:this.seed}}};ly.className="Orthogonal";re.registerClass(ly);var d3={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 p3(e,t={}){return gc(e,re.SerializationMap.getMap().classNameMap,t,"initializer")}function kt(e){return HA(e)}function gt(e){if(typeof e=="string"){let t=e in d3?d3[e]:e;if(t==="GlorotNormal")return new _p;if(t==="GlorotUniform")return new wp;if(t==="HeNormal")return new bp;if(t==="HeUniform")return new vp;if(t==="LeCunNormal")return new kp;if(t==="LeCunUniform")return new Ip;{let n={};return n.className=t,n.config={},p3(n)}}else return e instanceof or?e:p3(e)}function eY(){return new ny}function tY(){return new xp}function nY(e){return new ry(e)}function rY(e){return new ay(e)}function aY(e){return new sy(e)}function sY(e){return new iy(e)}function iY(e){return new oy(e)}function oY(e){return new yn(e)}function lY(e){return new wp(e)}function uY(e){return new _p(e)}function cY(e){return new bp(e)}function hY(e){return new vp(e)}function dY(e){return new kp(e)}function pY(e){return new Ip(e)}function fY(e){return new ly(e)}var R0={};ze(R0,{Layer:()=>Xe,RNN:()=>Fr,RNNCell:()=>Ic,activation:()=>ZY,add:()=>sQ,alphaDropout:()=>VQ,average:()=>iQ,averagePooling1d:()=>uy,averagePooling2d:()=>cy,averagePooling3d:()=>hy,avgPool1d:()=>mQ,avgPool2d:()=>yQ,avgPool3d:()=>xQ,avgPooling1d:()=>AQ,avgPooling2d:()=>gQ,avgPooling3d:()=>wQ,batchNormalization:()=>dQ,bidirectional:()=>$Q,concatenate:()=>oQ,conv1d:()=>VY,conv2d:()=>UY,conv2dTranspose:()=>HY,conv3d:()=>jY,convLstm2d:()=>CQ,convLstm2dCell:()=>RQ,cropping2D:()=>qY,dense:()=>JY,depthwiseConv2d:()=>KY,dot:()=>hQ,dropout:()=>YY,elu:()=>OY,embedding:()=>aQ,flatten:()=>eQ,gaussianDropout:()=>BQ,gaussianNoise:()=>WQ,globalAveragePooling1d:()=>_Q,globalAveragePooling2d:()=>bQ,globalMaxPool1d:()=>OQ,globalMaxPool2d:()=>zQ,globalMaxPooling1d:()=>f3,globalMaxPooling2d:()=>m3,gru:()=>kQ,gruCell:()=>IQ,input:()=>O0,inputLayer:()=>DY,layerNormalization:()=>pQ,leakyReLU:()=>PY,lstm:()=>NQ,lstmCell:()=>SQ,masking:()=>UQ,maxPool1d:()=>PQ,maxPool2d:()=>LQ,maxPooling1d:()=>A3,maxPooling2d:()=>y3,maxPooling3d:()=>vQ,maximum:()=>lQ,minimum:()=>uQ,multiply:()=>cQ,permute:()=>rQ,prelu:()=>LY,reLU:()=>zY,repeatVector:()=>tQ,reshape:()=>nQ,rnn:()=>FQ,separableConv2d:()=>GY,simpleRNN:()=>TQ,simpleRNNCell:()=>EQ,softmax:()=>WY,spatialDropout1d:()=>QY,stackedRNNCells:()=>MQ,thresholdedReLU:()=>BY,timeDistributed:()=>DQ,upSampling2d:()=>XY,zeroPadding2d:()=>fQ});var HQ=0;function g3(){return HQ++}var Np={};function Sp(e=""){return e in Np||(Np[e]=0),Np[e]+=1,e+Np[e].toString()}function dy(e){return Array.isArray(e)&&Array.isArray(e[0])}function Tp(e){return e.length===0?[]:Array.isArray(e[0])?e:[e]}function Pe(e){let t;if(Array.isArray(e)){if(e.length!==1)throw new B(`Expected Tensor length to be 1; got ${e.length}`);t=e[0]}else t=e;return t}function dt(e){if(Array.isArray(e)&&Array.isArray(e[0])){if(e.length===1)return e=e,e[0];throw new B(`Expected exactly 1 Shape; got ${e.length}`)}else return e}function Ep(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 x3="Variable",F0=class{constructor(e,t="float32",n=x3,r=!0,a=null){this.dtype=t==null?"float32":t,this.shape=e.shape,this.id=g3(),n=n==null?x3:n,this.originalName=i3(n),this.name=o3(this.originalName),this.trainable_=r,this.constraint=a,this.val=f0(e,this.trainable_,this.name,this.dtype)}read(){return this.assertNotDisposed(),this.val}write(e){return this.assertNotDisposed(),jQ(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 jQ(e,t){if(e.shape.toString()!==t.shape.toString())throw new Error("Shape mismatch: "+JSON.stringify(e.shape)+" vs. "+JSON.stringify(t.shape))}function py(e){return e.map(t=>t.read())}function fy(e){e.forEach(t=>{t[0].write(t[1])})}var Vt=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||{}}},mr=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=g3(),s!=null&&(this.originalName=i3(s),this.name=o3(this.originalName)),this.rank=t.length}},GQ=0,Cp=class{constructor(e,t){this.callArgs=t,this.id=GQ++,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}}},qQ=0,Xe=class extends re.Serializable{constructor(e={}){super();this._callHook=null,this._addedWeightNames=[],this._stateful=!1,this.id=qQ++,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=ia(n)+"_"+Sp(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 xr(`The layer has never been called and thus has no defined ${t}.`);if(this.inboundNodes.length<=e)throw new B(`Asked to get ${t} at node ${e}, but the layer has only ${this.inboundNodes.length} inbound nodes.`);return this.inboundNodes[e]}getInputAt(e){return An(this.getNodeAtIndex(e,"input").inputTensors)}getOutputAt(e){return An(this.getNodeAtIndex(e,"output").outputTensors)}get input(){if(this.inboundNodes.length>1)throw new sa(`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 sa(`Layer ${this.name} is not connected, no input to return.`);return An(this.getNodeAtIndex(0,"input").inputTensors)}get output(){if(this.inboundNodes.length===0)throw new sa(`Layer ${this.name} has no inbound nodes.`);if(this.inboundNodes.length>1)throw new sa(`Layer ${this.name} has multiple inbound nodes, hence the notion of "layer output" is ill-defined. Use \`getOutputAt(nodeIndex)\` instead.`);return An(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=mt(e),this.inputSpec==null||this.inputSpec.length===0)return;let t=mt(this.inputSpec);if(e.length!==t.length)throw new B(`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 B(`Input ${n} is incompatible with layer ${this.name}: expected ndim=${a.ndim}, found ndim=${s}`);if(a.maxNDim!=null&&s>a.maxNDim)throw new B(`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 B(`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 B(`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),c=a.axes[o],u=l>=0?i[l]:i[i.length+l];if(c!=null&&[c,null].indexOf(u)===-1)throw new B(`Input ${n} is incompatible with layer ${this.name}: expected axis ${l} of input shape to have value ${c} 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 B(`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=mt(e),r=!0;for(let s of n)if(!(s instanceof mr)){r=!1;break}let a=!0;for(let s of n)if(s instanceof mr){a=!1;break}if(r===a)throw new B("Arguments to apply() must be all SymbolicTensors or all Tensors");return pi(this.name,()=>{if(!this.built){this.assertInputCompatibility(e);let s=[];for(let i of mt(e))s.push(i.shape);this.build(An(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=mt(s),o=[];for(let l of i)n.indexOf(l)!==-1&&(l=l.clone()),o.push(l);if(s=An(o),this.activityRegularizer!=null)throw new De("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return s}else{let s=XQ(e),i=this.computeOutputShape(s),o,l=KQ(e);if(this.warnOnIncompatibleInputShape(Array.isArray(e)?s[0]:s),i!=null&&i.length>0&&Array.isArray(i[0])?o=i.map((c,u)=>new mr(l,c,this,mt(e),t,this.name,u)):o=new mr(l,i,this,mt(e),t,this.name),this.addInboundNode(e,o,null,null,s,i,t),this._refCount++,this.activityRegularizer!=null)throw new De("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 sa(`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 sa(`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 xr(`You tried to call countParams() on ${this.name}, but the layer is not built yet. Build it first by calling build(batchInputShape).`);return Ep(this.weights)}build(e){this.built=!0}getWeights(e=!1){return py(e?this.trainableWeights:this.weights)}setWeights(e){U(()=>{let t=this.weights;if(t.length!==e.length)throw new B(`You called setWeights(weights) on layer "${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=py(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 B(`Layer weight shape ${s.shape} not compatible with provided weight shape ${o.shape}`);n.push([i,o])}fy(n)})}addWeight(e,t,n,r,a,s,i){if(this._addedWeightNames.indexOf(e)!==-1)throw new B(`Duplicate weight name ${e} for layer ${this.name}`);this._addedWeightNames.push(e),n==null&&(n="float32"),this.fastWeightInitDuringBuild&&(r=gt("zeros"));let o=r.apply(t,n),l=new F0(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=mt(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 ${this.name} does not support masking, but was passed an inputMask.`);return null}return t}addInboundNode(e,t,n,r,a,s,i=null){let o=mt(e);t=mt(t),n=mt(n),r=mt(r),a=Tp(a),s=Tp(s);let l=[],c=[],u=[];for(let h of o)l.push(h.sourceLayer),c.push(h.nodeIndex),u.push(h.tensorIndex);new Cp({outboundLayer:this,inboundLayers:l,nodeIndices:c,tensorIndices:u,inputTensors:o,outputTensors:t,inputMasks:n,outputMasks:r,inputShapes:a,outputShapes:s},i);for(let h=0;h<t.length;h++)t[h].sourceLayer=this,t[h].nodeIndex=this.inboundNodes.length-1,t[h].tensorIndex=h}getConfig(){let e={name:this.name,trainable:this.trainable};return this.batchInputShape!=null&&(e.batchInputShape=this.batchInputShape),this.dtype!=null&&(e.dtype=this.dtype),e}disposeWeights(){return this.weights.forEach(e=>e.dispose()),this.weights.length}assertNotDisposed(){if(this._refCount===0)throw new Error(`Layer '${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 XQ(e){e=mt(e);let t=[];for(let n of e)t.push(n.shape);return An(t)}function KQ(e){return"float32"}function w3(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],c=w3(i,o,l);for(let u of c)a.indexOf(u)===-1&&a.push(u)}return a}}}var Sl=class extends Xe{constructor(e){super({dtype:e.dtype,name:e.name!=null?e.name:Sp("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 B("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 B("An InputLayer should be passed either a `batchInputShape` or an `inputShape`.");t=[e.batchSize].concat(e.inputShape)}else if(e.batchSize!=null)throw new B("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 mr(this.dtype,this.batchInputShape,this,[],{},this.name);r.nodeIndex=0,r.tensorIndex=0,new Cp({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:[r],outputTensors:[r],inputMasks:[null],outputMasks:[null],inputShapes:[t],outputShapes:[t]})}apply(e,t){throw new B(`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}}};Sl.className="InputLayer";re.registerClass(Sl);function _3(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 B("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 Sl({batchInputShape:t,name:e.name,dtype:n,sparse:e.sparse}).inboundNodes[0].outputTensors[0]}async function Oa(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];Ce(r)}}function b3(e){if(e!=null)for(let t in e){let n=e[t];typeof n!="number"&&n.dispose()}}var v3;(function(e){e[e.SILENT=0]="SILENT",e[e.VERBOSE=1]="VERBOSE"})(v3||(v3={}));var ZQ=125,Tl=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){}},M0=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)}},JQ=class extends Tl{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=U(()=>oe(this.totals[r],W(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:U(()=>{let r=W(Ne(1,this.seen),this.totals[n]);t[n]=r,this.totals[n].dispose(),Bt(t[n])}))}},$0=class extends Tl{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]}},D0=class extends Tl{constructor(e,t){super();if(this.currentEpoch=0,this.yieldEvery=t||"auto",this.yieldEvery==="auto"&&(this.yieldEvery=ZQ),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=QJ(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 Oa(n),r.push(this.yield(e,t,n))),r.push(Td()),await Promise.all(r)}async onEpochBegin(e,t){this.currentEpoch=e,this.epochBegin!=null&&(await Oa(t),await this.epochBegin(e,t))}async onEpochEnd(e,t){let n=[];this.epochEnd!=null&&(await Oa(t),n.push(this.epochEnd(e,t))),this.yieldEvery==="epoch"&&n.push(Td()),await Promise.all(n)}async onBatchBegin(e,t){this.batchBegin!=null&&(await Oa(t),await this.batchBegin(e,t))}async onBatchEnd(e,t){let n=[];this.batchEnd!=null&&(await Oa(t),n.push(this.batchEnd(e,t))),this.yieldEvery==="batch"?n.push(Td()):v.isNumber(this.yieldEvery)&&n.push(this.maybeWait(this.currentEpoch,e,t)),await Promise.all(n)}async onTrainBegin(e){this.trainBegin!=null&&(await Oa(e),await this.trainBegin(e))}async onTrainEnd(e){this.trainEnd!=null&&(await Oa(e),await this.trainEnd(e))}};function k3(e,t){return e==null&&(e={}),e instanceof Tl?[e]:Array.isArray(e)&&e[0]instanceof Tl?e:mt(e).map(n=>new D0(n,t))}var lr=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}`),lr.checkForDuplicate(t),lr.constructors[e]==null&&(lr.constructors[e]=[]),lr.constructors[e].push(t)}static checkForDuplicate(e){for(let t in lr.constructors)lr.constructors[+t].forEach(n=>{if(n===e)throw new B("Duplicate callback constructor.")})}static clear(){lr.constructors={}}static createCallbacks(e){let t=[];for(let n in lr.constructors){let r=+n;e>=r&&t.push(...lr.constructors[r])}return t.map(n=>new n)}};lr.constructors={};function I3(e,t,n,r,a,s,i,o,l){let c=new $0,u=[new JQ,...lr.createCallbacks(t)];e!=null&&u.push(...e),u.push(c);let h=new M0(u);return h.setParams({epochs:n,initialEpoch:r,samples:a,steps:s,batchSize:i,verbose:t,doValidation:o,metrics:l}),{callbackList:h,history:c}}function _r(e,t={},n=!1){return gc(e,re.SerializationMap.getMap().classNameMap,t,"layer",n)}function Rp(e,t){return U(()=>{e.dtype!=="float32"&&(e=e.asType("float32"));let n=Te(vc(e),t,!0),r=Fu(n.shape,zt()),a=Xt(Tr(n,r));return Ne(e,a)})}function mi(e,t){return U(()=>bt(vc(we(t,e)),-1))}function Fp(e,t){return U(()=>bt($t(we(t,e)),-1))}function El(e,t){return U(()=>{let n=we(e,t),r=pn($t(e),zt(),Number.MAX_VALUE),a=$t(Ne(n,r));return W(100,bt(a,-1))})}function YQ(e,t){return U(()=>{let n=pn(t,zt(),Number.MAX_VALUE),r=kn(oe(1,n)),a=pn(e,zt(),Number.MAX_VALUE),s=kn(oe(1,a));return bt(vc(we(r,s)),-1)})}function QQ(e,t){return U(()=>{let n=Tr(0,we(1,W(e,t)));return bt(vc(n),-1)})}function eee(e,t){return U(()=>{let n=Tr(0,we(1,W(e,t)));return bt(n,-1)})}function tee(e,t){return U(()=>{let n=Te(W(e,t),-1),r=Bn(W(we(1,e),t),-1);return Tr(0,oe(1,we(r,n)))})}function nee(e,t){return U(()=>{let n=Math.log(2),r=we(t,e),a=we(oe(r,Go(W(-2,r))),n);return bt(a,-1)})}function Nc(e,t,n=!1){return U(()=>{if(n)t=Wu(t);else{let r=Te(t,t.shape.length-1,!0);t=Ne(t,r)}return t=pn(t,zt(),1-zt()),_t(Te(W(e.toFloat(),kn(t)),t.shape.length-1))})}function Mp(e,t,n=!1){return U(()=>{let r=jo(IY(e)).toInt();t=pn(t,zt(),1-zt());let a=t.shape,s=Wo(r,a[a.length-1]).reshape(a);return Nc(s,t,n)})}function ree(e,t){if(!v.arraysEqual(e.shape,t.shape))throw new B(`logits and labels must have the same shape, but got shapes ${JSON.stringify(e.shape)} and ${JSON.stringify(t.shape)}`);return U(()=>{let n=t.relu(),r=t.abs().neg();return n.sub(t.mul(e)).add(r.exp().log1p())})}function $p(e,t){return U(()=>{let n;return n=pn(t,zt(),1-zt()),n=kn(Ne(n,we(1,n))),bt(ree(e,n),-1)})}function aee(e,t){return U(()=>{let n=pn(e,zt(),1),r=pn(t,zt(),1);return Te(W(e,kn(Ne(n,r))),-1)})}function see(e,t){return U(()=>{let n=kn(oe(zt(),t));return bt(we(t,W(e,n)),-1)})}function my(e,t){return U(()=>{let n=Rp(e,-1),r=Rp(t,-1),a=W(n,r);return _t(Te(a,-1))})}var Dp={meanSquaredError:mi,meanAbsoluteError:Fp,meanAbsolutePercentageError:El,meanSquaredLogarithmicError:YQ,squaredHinge:QQ,hinge:eee,categoricalHinge:tee,logcosh:nee,categoricalCrossentropy:Nc,sparseCategoricalCrossentropy:Mp,binaryCrossentropy:$p,kullbackLeiblerDivergence:aee,poisson:see,cosineProximity:my};function Ay(e){if(typeof e=="string"){if(e in Dp)return Dp[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 B(t)}else return e}function yy(e,t){return U(()=>{let n=W(.5,In(t)),r=_c(tr(t,n),e.dtype);return bt(xa(e,r),-1)})}function gy(e,t){return U(()=>_c(xa(Su(e,-1),Su(t,-1)),"float32"))}function N3(e,t){return U(()=>nr(e.equal(1),t.equal(1)).sum().cast("float32"))}function iee(e,t){return U(()=>nr(e.equal(1),t.equal(0)).sum().cast("float32"))}function oee(e,t){return U(()=>nr(e.equal(0),t.equal(1)).sum().cast("float32"))}function S3(e,t){return U(()=>{let n=N3(e,t),r=oee(e,t),a=n.add(r);return fn(tr(a,0),n.div(a),0).cast("float32")})}function lee(e,t){return U(()=>{let n=N3(e,t),r=iee(e,t),a=n.add(r);return fn(tr(a,0),n.div(a),0).cast("float32")})}function T3(e,t){return $p(e,t)}function E3(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)),xa(e,t).asType("float32")}var uee=mi,cee=mi,hee=Fp,dee=Fp,pee=El,fee=El,xy=Nc,mee=my,C3=Mp,Op={binaryAccuracy:yy,categoricalAccuracy:gy,precision:S3,categoricalCrossentropy:xy,sparseCategoricalCrossentropy:C3,mse:uee,MSE:cee,mae:hee,MAE:dee,mape:pee,MAPE:fee,cosine:mee};function Aee(e){if(typeof e=="string"&&e in Op)return Op[e];if(typeof e!="string"&&e!=null)return e;throw new B(`Unknown metric ${e}`)}function zp(e){if(Wr(e!==null,`Unknown LossOrMetricFn ${e}`),typeof e=="string")return e;{let t;for(let n of Object.keys(Dp))if(Dp[n]===e){t=n;break}if(t!==void 0)return t;for(let n of Object.keys(Op))if(Op[n]===e){t=n;break}return t!==void 0?t:e.name}}function yee(e){let t={Adagrad:()=>Gs.adagrad(.01),Adadelta:()=>Gs.adadelta(1,.95,zt()),Adam:()=>Gs.adam(.001,.9,.999,zt()),Adamax:()=>Gs.adamax(.002,.9,.999,zt(),0),RMSProp:()=>Gs.rmsprop(.001,.9,0,zt()),SGD:()=>Gs.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 B(`Unknown Optimizer ${e}`)}var R3=1*1024*1024;function F3(e,t,n=!1){if(e==null||typeof e!="object"||Object.getPrototypeOf(e)!==Object.prototype||!wy(e))throw new Error("User-defined metadata is expected to be a JSON object, but is not.");if(n){let r=JSON.stringify(e);r.length>R3&&console.warn(`User-defined metadata of model "${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 <= ${R3}.`)}}function wy(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"||!wy(e[n]))return!1;return!0}else if(Array.isArray(e)){for(let t of e)if(!wy(t))return!1;return!0}else return!1;else{let t=typeof e;return t==="string"||t==="number"||t==="boolean"}}function bee(e,t,n,r=console.log){let a=xee(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(u=>Math.floor(t*u)));let i;if(!a){s.push("Receives inputs"),i=[];for(let u in e.nodesByDepth)i.push(...e.nodesByDepth[u])}r("_".repeat(t)),Pp(s,n,r),r("=".repeat(t));let o=e.layers;for(let u=0;u<o.length;++u)a?wee(o[u],n,r):_ee(o[u],n,i,r),r((u===o.length-1?"=":"_").repeat(t));e.checkTrainableWeightsConsistency();let l=gee(e),c=Ep(e.nonTrainableWeights);r(`Total params: ${l+c}`),r(`Trainable params: ${l}`),r(`Non-trainable params: ${c}`),r("_".repeat(t))}function gee(e){let t;return e.collectedTrainableWeights!=null?t=Ep(e.collectedTrainableWeights):t=Ep(e.trainableWeights),t}function xee(e){let t=!0,n=[],r=[];for(let a in e.nodesByDepth)n.push(e.nodesByDepth[a]);for(let a of n){if(a.length>1||a.length===1&&a[0].inboundLayers.length>1){t=!1;break}r.push(...a)}if(t)for(let a of e.layers){let s=!1;for(let i of a.inboundNodes)if(r.indexOf(i)!==-1)if(s){t=!1;break}else s=!0;if(!t)break}return t}function Pp(e,t,n=console.log){let r="";for(let a=0;a<e.length;++a)a>0&&(r=r.slice(0,r.length-1)+" "),r+=e[a],r=r.slice(0,t[a]),r+=" ".repeat(t[a]-r.length);n(r)}function wee(e,t,n){let r;try{r=JSON.stringify(e.outputShape)}catch(o){r="multiple"}let a=e.name,s=e.getClassName(),i=[`${a} (${s})`,r,e.countParams().toString()];Pp(i,t,n)}function _ee(e,t,n,r){let a;try{a=JSON.stringify(e.outputShape)}catch(u){a="multiple"}let s=[];for(let u of e.inboundNodes)if(!(n!=null&&n.length>0&&n.indexOf(u)===-1))for(let h=0;h<u.inboundLayers.length;++h){let d=u.inboundLayers[h].name,p=u.nodeIndices[h],f=u.tensorIndices[h];s.push(`${d}[${p}][${f}]`)}let i=e.name,o=e.getClassName(),l=s.length===0?"":s[0],c=[`${i} (${o})`,a,e.countParams().toString(),l];Pp(c,t,r);for(let u=1;u<s.length;++u)Pp(["","","",s[u]],t,r)}function M3(e,t,n){return(e==="inboundNodes"||e==="outputLayers"||e==="inputLayers")&&t===0&&typeof n=="string"}function Sc(e,t){if(e===null)return null;if(typeof e=="string")return hi(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];M3(t,a,s)?n.push(s):n.push(Sc(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=hi(r);n[s]=Sc(a,s)}}return n}}function _y(e,t){if(e==null)return null;if(typeof e=="string")return ia(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];M3(t,a,s)?n.push(s):n.push(_y(s,t))}return n}else{let n={};for(let r of Object.keys(e)){let a=e[r],s=ia(r);(r==="name"||r==="className")&&typeof a=="string"?n[s]=a:n[s]=_y(a,r)}return n}}var Am="3.0.0";function vee(e,t){if(e.dtype==null||e.dtype===t.dtype)return t;try{return ye(t,e.dtype)}catch(n){throw new B(`The dtype of the feed (${t.dtype}) can not be cast to the dtype of the key '${e.name}' (${e.dtype}).`)}}var Ai=class{constructor(e){if(this.id2Value={},this.id2Mask={},this.name2Id={},e instanceof Ai)for(let t in e.id2Value)this.id2Value[t]=e.id2Value[t],t in e.id2Mask&&(this.id2Mask[t]=e.id2Mask[t]);else{if(e==null)return;for(let t of e)this.add(t.key,t.value)}}add(e,t,n){if(this.id2Value[e.id]==null)this.id2Value[e.id]=vee(e,t),this.name2Id[e.name]=e.id,n!=null&&(this.id2Mask[e.id]=n);else throw new B(`Duplicate key: name=${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 mr){if(this.id2Value[e.id]==null)throw new B(`Nonexistent key: ${e.name}`);return this.id2Value[e.id]}else{let t=this.name2Id[e];if(t==null)throw new B(`Feed dict has no SymbolicTensor name: ${e}`);return this.id2Value[t]}}getMask(e){if(e instanceof mr){if(this.id2Value[e.id]==null)throw new B(`Nonexistent key: ${e.name}`);return this.id2Mask[e.id]}else{let t=this.name2Id[e];if(t==null)throw new B(`Feed dict has no SymbolicTensor name: ${e}`);return this.id2Mask[t]}}disposeMasks(){this.id2Mask!=null&&Ce(this.id2Mask)}},by={},$3={};function Tc(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=[],c=t.names();for(let f of o)c.indexOf(f)!==-1?l.push(t.getValue(f)):l.push(null);r!=null&&(r.maxNumTensors=-Infinity,r.minNumTensors=Infinity);let u=o.join(",")+"|"+t.names().join(","),h,d;if(by[u]==null){let f=kee(i,t);h=f.sorted,d=f.recipientCounts,by[u]=h,$3[u]=d}h=by[u],d={},a||Object.assign(d,$3[u]);let p=new Ai(t);for(let f=0;f<h.length;++f){if(r!=null){let N=Gh().numTensors;N>r.maxNumTensors&&(r.maxNumTensors=N),N<r.minNumTensors&&(r.minNumTensors=N)}let m=h[f],A=m.sourceLayer;if(A instanceof Sl)continue;let y=[],g=[],w=[],x=!1;for(let N of m.inputs){let F=p.getValue(N),$=p.getMask(N);y.push(F),g.push($),$!=null&&(x=!0),a||(d[N.name]--,d[N.name]===0&&!t.hasKey(N)&&o.indexOf(N.name)===-1&&!F.isDisposed&&N.sourceLayer.stateful!==!0&&w.push(F))}x&&(n=n||{},n.mask=g[0]);let _=mt(A.apply(y,n)),I=null;A.supportsMasking&&(I=A.computeMask(y,g));let T=Iee(m),E=Array.isArray(T)?T:[T];for(let N=0;N<E.length;++N){p.hasKey(E[N])||p.add(E[N],_[N],Array.isArray(I)?I[0]:I);let F=o.indexOf(E[N].name);F!==-1&&(l[F]=_[N])}a||Ce(w)}return p.disposeMasks(),s?l:l[0]}function kee(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=D3(e[0],t);n=a.sorted,r=a.recipientMap}else{let a=new Set;for(let s of e){let{sorted:i,recipientMap:o}=D3(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(c=>r[l].add(c))}}return{sorted:n,recipientCounts:Nee(r)}}function Nee(e){let t={};for(let n in e)t[n]=e[n].size;return t}function D3(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 c of o.inputs)a[c.name]==null&&(a[c.name]=new Set),a[c.name].add(o.name),!n.has(c.name)&&s.push(c)}}return{sorted:r,recipientMap:a}}function Iee(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 Ur=class extends Xe{constructor(e){super({});if(this.containerNodes=new Set,this.name=e.name,this.name==null){let y=this.getClassName().toLowerCase();this.name=Sp(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],Ma(this.inputs).length!==this.inputs.length)throw new B(`The list of inputs passed to the model is redundant. All inputs should only appear once. Found: ${this.inputs.map(y=>y.name)}`);Ma(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,w=y.nodeIndex,x=y.tensorIndex;this.outputLayers.push(g),this.outputLayersNodeIndices.push(w),this.outputLayersTensorIndices.push(x)}for(let y of this.inputs){let g=y.sourceLayer,w=y.nodeIndex,x=y.tensorIndex;Wr(w===0,"input layer has >1 nodes"),Wr(x===0,"input layer has >1 tensors"),this.inputLayers.push(g),this.inputLayersNodeIndices.push(w),this.inputLayersTensorIndices.push(x)}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 Sl))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,w,x,_,I)=>{(x==null||_==null||I==null)&&(x=y.sourceLayer,_=y.nodeIndex,I=y.tensorIndex);let T=x.inboundNodes[_];if(w.indexOf(T)!==-1)throw new xr(`The tensor ${y.name} at layer "${x.name}" is part of a cycle.`);if(g.indexOf(T)!==-1)return;this.containerNodes.add(Ur.nodeKey(x,_)),x.id in s||(s[x.id]=Object.keys(s).length),w.indexOf(T)===-1&&w.push(T);let E=T.inboundLayers.length;for(let N=0;N<E;N++){let F=T.inputTensors[N],$=T.inboundLayers[N],D=T.nodeIndices[N],P=T.tensorIndices[N];o(F,g,w,$,D,P)}for(g.push(T);w.indexOf(T)>=0;)w.splice(w.indexOf(T),1);i.push(T)},l=[],c=[];for(let y of this.outputs)o(y,l,c);let u=i.slice().reverse();for(let y of u){n[y.id]=y,y.id in t||(t[y.id]=0);let g=t[y.id],w=r[y.outboundLayer.id]==null?0:r[y.outboundLayer.id];g=Math.max(g,w),r[y.outboundLayer.id]=g,a[y.outboundLayer.id]=y.outboundLayer,t[y.id]=g;for(let x=0;x<y.inboundLayers.length;x++){let _=y.inboundLayers[x],I=y.nodeIndices[x],T=_.inboundNodes[I],E=t[T.id]==null?0:t[T.id];t[T.id]=Math.max(g+1,E),n[T.id]=T}}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(Ap);this.layers=[];for(let y of p){let g=d[y];g.sort((w,x)=>{let _=s[w.id],I=s[x.id];return _<I?-1:_>I?1:0});for(let w of g)w instanceof Ur&&this.internalContainerRefs.push(w),this.layers.push(w)}this.layersByDepth=d,p=Object.keys(h).map(y=>parseInt(y,10)).sort(Ap);let f=this.inputs.slice(),m=[];for(let y of p)for(let g of h[y]){let w=g.outboundLayer;if(w!=null){for(let x of g.inputTensors)if(f.indexOf(x)===-1)throw new xr(`Graph disconnected: cannot obtain value for tensor ${x} at layer "${w.name}". The following previous layers were accessed without issue: ${m}`);for(let x of g.outputTensors)f.push(x);m.push(w.name)}}this.nodesByDepth=h;let A=this.layers.map(y=>y.name);for(let y of A){let g=A.filter(w=>w===y).length;if(g!==1)throw new xr(`The name "${y}" is used ${g} times in the model. All layer names should be unique. Layer names: `+JSON.stringify(A))}this.outboundNodes=[],this.inboundNodes=[],new Cp({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:this.inputs.map(y=>null),outputMasks:this.outputs.map(y=>null),inputShapes:this.inputs.map(y=>y.shape),outputShapes:this.outputs.map(y=>y.shape)}),this.built=!0,this._refCount=1}assertNotDisposed(){if(this._refCount===0)throw new Error(`Container '${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 B("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 B(`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 B(`Provided weight data has no target variable: ${s}`);delete n[i]}if(t){let s=[];for(let i in n)s.push(i);if(s.length>0)throw new B(`${s.length} of ${r} weights are not set: ${s}`)}fy(a)}updatedConfig(){let e=this.getConfig(),t={};return t.className=this.getClassName(),t.config=e,t.kerasVersion=`tfjs-layers ${Am}`,t.backend="TensorFlow.js",t}toJSON(e,t=!0){let n=_y(this.updatedConfig());return t?JSON.stringify(n):n}call(e,t){return U(()=>{e=mt(e);let n=new Ai;for(let r=0;r<this.inputs.length;++r)n.add(this.inputs[r],e[r]);return Tc(this.outputs,n,t)})}computeMask(e,t){return U(()=>{e=mt(e);let n;return t==null?n=ci(null,e.length):n=mt(t),this.runInternalGraph(e,n)[1]})}computeOutputShape(e){let t=Tp(e);if(t.length!==this.inputLayers.length)throw new B(`Invalid inputShape argument ${e}: model has ${this.inputLayers.length} tensor inputs.`);let n={};for(let i=0;i<t.length;i++){let o=this.inputLayers[i],l=t[i],c=o.name+"_0_0";n[c]=l}let r=Object.keys(this.nodesByDepth).map(i=>parseInt(i,10)).sort(Ap);if(r.length>1)for(let i of r){let o=this.nodesByDepth[i];for(let l of o){let c=l.outboundLayer;if(this.inputLayers.map(f=>f.id).indexOf(c.id)!==-1)continue;let u=[];for(let f=0;f<l.inboundLayers.length;f++){let m=l.inboundLayers[f],A=l.nodeIndices[f],y=l.tensorIndices[f],g=`${m.name}_${A}_${y}`,w=n[g];u.push(w)}let h=c.computeOutputShape(An(u)),d=Tp(h),p=c.inboundNodes.indexOf(l);for(let f=0;f<d.length;f++){let m=`${c.name}_${p}_${f}`;n[m]=d[f]}}}let a=[],s=[];for(let i=0;i<this.outputLayers.length;i++){let o=this.outputLayers[i],l=this.outputLayersNodeIndices[i],c=this.outputLayersTensorIndices[i],u=`${o.name}_${l}_${c}`;s.push(u)}for(let i=0;i<s.length;i++){let o=s[i];Wr(o in n),a.push(n[o])}return An(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],c=e[o],u=t[o];n[l.id]=[c,u]}let r=Object.keys(this.nodesByDepth).map(o=>parseInt(o,10)).sort(Ap);for(let o of r){let l=this.nodesByDepth[o];for(let c of l){let u=c.outboundLayer,h=c.inputTensors,d=c.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(c.callArgs!=null&&(f=c.callArgs),p.length===1){let[w,x]=p[0];f.mask==null&&(f.mask=x),y=mt(u.call(w,f)),g=mt(u.computeMask(w,x)),m=[w],A=[x]}else m=p.map(w=>w[0]),A=p.map(w=>w[1]),f.mask==null&&(f.mask=A),y=mt(u.call(m,f)),g=mt(u.computeMask(m,A));if(u.activityRegularizer)throw new De("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(let w=0;w<d.length;++w){let x=d[w],_=y[w],I=g[w];n[x.id]=[_,I]}}}}let a=[],s=[],i=[];for(let o of this.outputs){Wr(o.id in n,`Could not compute output ${o.name} : ${o.id}`);let[l,c]=n[o.id];i.push(l.shape),a.push(l),s.push(c)}return[a,s,i]}buildNodeConversionMap(e){let t={},n;for(let r of this.layers){n=r instanceof Ur?1:0;for(let a=0;a<r.inboundNodes.length;a++){let s=Ur.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 B(`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 B("Provide either a layer name or layer index");for(let n of this.layers)if(n.name===e)return n;throw new B(`No such layer: ${e}`)}calculateLosses(){return U(()=>{let e=[];for(let t of this.layers)for(let n=0;n<t.inboundNodes.length;++n){let r=Ur.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 u=0;u<s.inboundNodes.length;u++){let h=s.inboundNodes[u],d=Ur.nodeKey(s,u),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],w=Ur.nodeKey(A,y),x=t[w];x==null&&(x=0),f.push([A.name,x,g,p])}l.push(f)}}}let c={};c.name=s.name,c.className=i,c.config=o,c.inboundNodes=l,n.push(c)}e.layers=n;let r=[];for(let s=0;s<this.inputLayers.length;s++){let i=this.inputLayers[s],o=this.inputLayersNodeIndices[s],l=Ur.nodeKey(i,o);if(!this.containerNodes.has(l))continue;let c=t[l];c==null&&(c=0);let u=this.inputLayersTensorIndices[s];r.push([i.name,c,u])}e.inputLayers=r;let a=[];for(let s=0;s<this.outputLayers.length;s++){let i=this.outputLayers[s],o=this.outputLayersNodeIndices[s],l=Ur.nodeKey(i,o);if(!this.containerNodes.has(l))continue;let c=t[l];c==null&&(c=0);let u=this.outputLayersTensorIndices[s];a.push([i.name,c,u])}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 w of A){let x=w[0],_=w[1],I=w[2];if(g=w[3]==null?{}:w[3],!(x in a)){i(m,A);return}let T=a[x];if(T.inboundNodes.length<=_){i(m,A);return}let E=T.inboundNodes[_];y.push(E.outputTensors[I])}y.length>0&&m.apply(An(y),g)}function l(m){let A=m.name,y=_r(m,t.customObjects!=null?t.customObjects:{});y.setFastWeightInitDuringBuild(r),a[A]=y,m.inboundNodes.forEach(g=>{if(!(g instanceof Array))throw new B(`Corrupted configuration, expected array for nodeData: ${g}`);i(y,g)})}let c=t.name,u=t.layers;for(let m of u)l(m);for(;!YJ(s);)for(let m of u){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];Wr(A in a);let w=a[A].inboundNodes[y].outputTensors;h.push(w[g])}let f=t.outputLayers;for(let m of f){let A=m[0],y=m[1],g=m[2];Wr(A in a);let w=a[A].inboundNodes[y].outputTensors;d.push(w[g])}return new e({inputs:h,outputs:d,name:c})}get stateful(){if(this._stateful)throw new B("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(){U(()=>{this.layers.forEach(e=>{e.stateful&&e.resetStates()})})}};function See(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: ${JSON.stringify(e)}`)}function O3(e,t){return See(e,t,"classWeight")}async function z3(e,t,n,r){if(t!=null||r!=null)throw new Error("Support sampleWeight is not implemented yet");if(n!=null){let a=U(()=>{if(e.shape.length===1)return e.clone();if(e.shape.length===2)if(e.shape[1]>1){let o=1;return e.argMax(o)}else{if(e.shape[1]===1)return e.reshape([e.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${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());Ce(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])}),Qt(i,"float32")}else return null}function Tee(e,t){return W(e,t)}var Eee=32;function L3(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=P3("input",e.inputNames,n),i=P3("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 P3(e,t,n){if(n instanceof Qe)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 B(`The feature data generated by the dataset lacks the required ${e} key '${a}'.`);r.push(n[a])}return r}}function Cee(e){if(e.length===3)throw new De("Validation with sample weights is not implemented yet.");return{xs:e[0],ys:e[1]}}async function Fee(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(W3(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=Cee(n.validationData);s=A.xs,i=A.ys}let o=e.makeTrainFunction(),l=e.getDedupedMetricsNames(),c;a?c=l.slice().concat(l.map(A=>"val_"+A)):c=l.slice();let u=k3(n.callbacks,n.yieldEvery),h=n.verbose==null?1:n.verbose,{callbackList:d,history:p}=I3(u,h,n.epochs,null,null,Ree(t,n),null,a,c);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 w=await m.next();if(r&&w.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(w.value!=null){let{xs:x,ys:_}=L3(e,w.value),I={};I.batch=g,I.size=x[0].shape[0],await d.onBatchBegin(g,I);let T=[];if(n.classWeight!=null){let F=O3(n.classWeight,e.outputNames);for(let $=0;$<F.length;++$)T.push(await z3(_[$],null,F[$]))}let E=x.concat(_).concat(T),N=o(E);Ce(E);for(let F=0;F<l.length;++F){let $=l[F],D=N[F];I[$]=D,Bt(D)}await d.onBatchEnd(g,I),b3(I),g++,y++}if(r?y>=n.batchesPerEpoch:w.done){if(a){let x;W3(n.validationData)?x=mt(await e.evaluateDataset(n.validationData,{batches:n.validationBatches})):x=mt(e.evaluate(s,i,{batchSize:n.validationBatchSize==null?Eee:n.validationBatchSize,verbose:0}));for(let _=0;_<e.metricsNames.length;++_)A[`val_${e.metricsNames[_]}`]=x[_]}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 Ree(e,t){let n=null;return t.batchesPerEpoch!=null?n=t.batchesPerEpoch:Number.isFinite(e.size)&&(n=e.size),n}function W3(e){return typeof e.iterator=="function"}function Mee(e){return typeof e.next=="function"}async function $ee(e,t,n){n=n||{};let r=n.batches!=null,a=e.testFunction,s=[];if(n.verbose>0)throw new De("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=Mee(t)?t:await t.iterator(),o=0,l=0;for(;r?l<n.batches:!0;){let c=await i.next();if(s=U(()=>{if(c.value){let{xs:u,ys:h}=L3(e,c.value),d=u.concat(h),p=U(()=>a(d));if(Ce(d),l===0)for(let m=0;m<p.length;++m)s.push(Se(0));let f=d[0].shape[0];for(let m=0;m<p.length;++m){let A=p[m],y=s[m];s[m]=U(()=>oe(s[m],W(f,A))),l>0&&Ce(y)}Ce(p),o+=f,++l}return s}),c.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 c=0;c<s.length;++c){let u=s[c];s[c]=Ne(s[c],o),Ce(u)}return An(s)}function vy(e){v.assert(e>0&&Number.isInteger(e),()=>`batchSize is required to be a positive integer, but got ${e}`)}function Ec(e,t,n){return e==null?[null]:Array.isArray(e)?e.map(r=>fi(r,t,n-t)):fi(e,t,n-t)}function ky(e,t){return U(()=>e==null?null:Array.isArray(e)?e.map(n=>ky(n,t)):c3(e,t.dtype==="int32"?t:t.toInt()))}function Iy(e,t){let n=[],r=0,a=null;for(;r<e;)a=r+t,a>=e&&(a=e),n.push([r,a]),r=a;return n}async function Dee(e,t,n,r,a,s,i,o,l,c,u,h,d,p,f){a==null&&(a=32),s==null&&(s=1),u==null&&(u=!0),d==null&&(d=0);let m=!1;if(l!=null&&c!=null&&(m=!0),f!=null&&(m=!0,p==null))throw new B("Can only use `validationSteps` when doing step-wise training, i.e., `stepsPerEpoch` must be set.");let A=e.checkNumSamples(n,a,p,"steps_per_epoch"),y;A!=null&&(y=wr(0,A)),i==null&&(i=1);let{callbackList:g,history:w}=I3(o,i,s,d,A,p,a,m,h);g.setModel(e),e.history=w,await g.onTrainBegin(),e.stopTraining_=!1;for(let x=d;x<s;++x){await g.onEpochBegin(x);let _={};if(p!=null)throw new De("stepsPerEpoch mode is not implemented yet.");{if(u==="batch")throw new De("batch shuffling is not implemneted yet");u&&v.shuffle(y);let I=Qt(y),T=Iy(A,a);for(let E=0;E<T.length;++E){let N={};if(await g.onBatchBegin(E,N),U(()=>{let F=T[E][0],$=T[E][1],D=fi(I,F,$-F);N.batch=E,N.size=$-F;let P=ky(n,D),H=t(P);for(let V=0;V<r.length;++V){let K=r[V],X=H[V];N[K]=X,Bt(X)}if(E===T.length-1&&m){let V=e.testLoop(l,c,a);for(let K=0;K<r.length;++K){let X=r[K],ee=V[K];Bt(ee),_["val_"+X]=ee}}}),await g.onBatchEnd(E,N),b3(N),e.stopTraining_)break}I.dispose()}if(await g.onEpochEnd(x,_),e.stopTraining_)break}return await g.onTrainEnd(),await e.history.syncData(),e.history}async function Oee(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,c,u;try{let h=r.batchSize==null?32:r.batchSize;vy(h);let d=!1,p=await e.standardizeUserData(t,n,r.sampleWeight,r.classWeight,d,h);a=p[0],s=p[1],u=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 De("validationData including sample weights is not supported yet."):new B(`When passing validation data, it must contain 2 (valX, valY) or 3 (valX, valY, valSampleWeight) items; ${r.validationData} is invalid.`);let I=!0,T=await e.standardizeUserData(i,o,null,null,I,h);l=T[0],c=T[1],m=l.concat(c)}else if(r.validationSplit!=null&&r.validationSplit>0&&r.validationSplit<1){f=!0;let I=Math.floor(a[0].shape[0]*(1-r.validationSplit)),T=a[0].shape[0];l=Ec(a,I,T),a=Ec(a,0,I),c=Ec(s,I,T),s=Ec(s,0,I),m=l.concat(c)}else r.validationSteps!=null&&(f=!0);let A=a.concat(s).concat(u);e.checkTrainableWeightsConsistency();let y=e.makeTrainFunction(),g=e.getDedupedMetricsNames(),w,x;f?(e.makeTestFunction(),w=e.testFunction,x=g.slice().concat(g.map(I=>"val_"+I))):(w=null,m=[],x=g.slice());let _=k3(r.callbacks,r.yieldEvery);return await Dee(e,y,A,g,h,r.epochs,r.verbose,_,w,m,r.shuffle,x,r.initialEpoch,null,null)}finally{e.isTraining=!1,yi(a,t),yi(s,n),yi(l,i),yi(c,o),u!=null&&Ce(u)}}function B3(e){let t=[];e instanceof Qe&&(e=[e]);for(let n=0;n<e.length;++n){let r=e[n];if(r.rank===1)t.push(bc(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 yi(e,t){if(e==null)return;let n=[];if(t instanceof Qe)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 Qe)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 zee(e){return e instanceof Qe}function Ny(e){return Array.isArray(e)}function V3(e){return!zee(e)&&!Ny(e)}function U3(e,t,n,r=!0,a=""){if(t==null||t.length===0){if(e!=null){let i=!1;if(Ny(e)&&e.length>0)i=!0;else if(V3(e)){for(let o in e)if(e.hasOwnProperty(o)){i=!0;break}}else i=!0;if(i)throw new B(`Error when checking model ${a} expected no data, but got ${e}`)}return[]}if(e==null)return t.map(i=>null);let s;if(V3(e)){e=e,s=[];for(let i of t){if(e[i]==null)throw new B(`No data provided for "${i}". Need data for each key in: ${t}`);s.push(e[i])}}else if(Ny(e)){if(e=e,e.length!==t.length)throw new B(`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 B(`The model ${a} expects ${t.length} Tensor(s), but only received one Tensor. Found: Tensor with shape ${e.shape}`);s=[e]}if(s=B3(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 B(`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 c=o.shape[l],u=n[i][l];if(u!=null&&u>=0&&c!==u)throw new B(`Error when checking ${a}: expected ${t[i]} to have shape [${n[i]}], but got array with shape [${o.shape}].`)}}return s}function Pee(e,t,n){let r=Ma(e.map(s=>s.shape[0]));r.sort();let a=Ma(t.map(s=>s.shape[0]));if(a.sort(),r.length>1)throw new B(`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 B(`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 B(`Input Tensors should have the same number of samples as target Tensors. Found ${r[0]} input sample(s) and ${a[0]} target sample(s).`)}function Lee(e,t,n){let r=[mi,$p,Nc];for(let a=0;a<e.length;++a){let s=e[a],i=t[a],o=n[a];if(i!=null){if(i===Nc&&s.shape[s.shape.length-1]===1)throw new B(`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),c=o.slice(1);for(let u=0;u<l.length;++u){let h=l[u],d=c[u];if(d!=null&&h!==d)throw new B(`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 H3(e,t,n,r=!0,a=""){let s;if(Array.isArray(e)){if(e.length!==t.length)throw new B(`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 B(`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 B(`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 c=o.shape[l],u=n[i][l];if(u!=null&&u!==c)throw new B(`Error when checking ${a}: expected ${t[i]} to have shape ${JSON.stringify(n[i])} but got array with shape ${JSON.stringify(o.shape)}.`)}}}function Wee(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: ${e}`);if(Array.isArray(n))return t.map(r=>n);{let r=[];for(let a of t){let s=n.hasOwnProperty(a)?n[a]:[];Array.isArray(s)||(s=[s]),r.push(s)}return r}}var Bee="layers-model",ea=class extends Ur{constructor(e){super(e);this.isTraining=!1}summary(e,t,n=console.log){if(!this.built)throw new B("This model has never been called, thus its weights have not been created yet. So no summary can be displayed. Build the model first (e.g., by calling it on some test data).");bee(this,e,t,n)}compile(e){if(e.loss==null&&(e.loss=[]),this.loss=e.loss,typeof e.optimizer=="string")this.optimizer_=yee(e.optimizer),this.isOptimizerOwned=!0;else{if(!(e.optimizer instanceof Qr))throw new B("User-defined optimizer must be an instance of tf.Optimizer.");this.optimizer_=e.optimizer,this.isOptimizerOwned=!1}let t=[];if(!Array.isArray(e.loss)&&typeof e.loss!="string"&&typeof e.loss!="function"){e.loss=e.loss;for(let s in e.loss)if(this.outputNames.indexOf(s)===-1)throw new B(`Unknown entry in loss dictionary: "${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(Ay(e.loss[s]))}else if(Array.isArray(e.loss)){if(e.loss.length!==this.outputs.length)throw new B(`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=>Ay(s))}else{let s=Ay(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=[],pi("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=Wee(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])};pi("metric",()=>{for(let s=0;s<this.outputs.length;++s){if(n.indexOf(s)!==-1)continue;let i=r[s];(o=>{let l="",c,u,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]===$p?["accuracy","acc"].indexOf(d)!==-1?u=yy:["crossentropy","ce"].indexOf(d)!==-1&&(u=T3):this.lossFunctions[s]===Mp?["accuracy","acc"].indexOf(d)!==-1?u=E3:["crossentropy","ce"].indexOf(d)!==-1&&(u=C3):["accuracy","acc"].indexOf(d)!==-1?u=gy:["crossentropy","ce"].indexOf(d)!==-1&&(u=xy);let m;["accuracy","acc"].indexOf(d)!==-1?m="acc":["crossentropy","ce"].indexOf(d)!==-1&&(m="ce"),h=u,c=l+m}else h=Aee(d),c=l+zp(d);let p;pi(c,()=>{p=h}),a(s,c,p)}})(i)}}),this.collectedTrainableWeights=this.trainableWeights}checkTrainableWeightsConsistency(){this.collectedTrainableWeights!=null&&this.trainableWeights.length!==this.collectedTrainableWeights.length&&console.warn("Discrepancy between trainableweights and collected trainable weights. Did you set `model.trainable` without calling `model.compile()` afterwards?")}evaluate(e,t,n={}){let r=n.batchSize==null?32:n.batchSize;vy(r);let a=!0,s=this.standardizeUserDataXY(e,t,a,r);try{let i=s[0].concat(s[1]);this.makeTestFunction();let o=this.testFunction,l=this.testLoop(o,i,r,n.verbose,n.steps);return An(l)}finally{yi(s[0],e),yi(s[1],t)}}async evaluateDataset(e,t){return this.makeTestFunction(),$ee(this,e,t)}checkNumSamples(e,t,n,r="steps"){let a;if(n!=null){if(a=null,t!=null)throw new B(`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 B(`Either the input data should have a defined shape, or ${r} shoud be specified.`);return a}execute(e,t){if(Array.isArray(t)&&t.length===0)throw new B("`outputs` is an empty Array, which is not allowed.");let n=Array.isArray(t),r=n?t:[t],a=this.retrieveSymbolicTensors(r),s=new Ai;if(e instanceof Qe&&(e=[e]),Array.isArray(e)){if(e.length!==this.inputs.length)throw new B(`The number of inputs provided (${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 B(`No value is provided for the model's input ${o.name}`);s.add(o,l)}let i=Tc(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 B(`Cannot find SymbolicTensors for output name(s): ${JSON.stringify(r)}`)}return t}predictLoop(e,t=32,n=!1){return U(()=>{let r=this.checkNumSamples(e);if(n)throw new De("Verbose predictLoop() is not implemented yet.");let a=Iy(r,t),s=this.outputs.map(i=>[]);for(let i=0;i<a.length;++i)U(()=>{let o=a[i][0],l=a[i][1],c=Ec(e,o,l),u=[];if(Array.isArray(c))for(let d=0;d<c.length;++d)u.push({key:this.inputs[d],value:c[d]});else u.push({key:this.inputs[0],value:c});let h=new Ai(u);return Tc(this.outputs,h)}).forEach((o,l)=>s[l].push(o));return An(s.map(i=>ct(i,0)))})}predict(e,t={}){let n=B3(e);H3(n,this.inputNames,this.feedInputShapes,!1);try{let r=t.batchSize==null?32:t.batchSize;return vy(r),this.predictLoop(n,r)}finally{yi(n,e)}}predictOnBatch(e){H3(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 xr("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]===Mp?a.push(i.slice(0,i.length-1).concat([1])):a.push(i)}if(e=U3(e,this.feedInputNames,this.feedInputShapes,!1,"input"),t=U3(t,this.feedOutputNames,a,!1,"target"),Pee(e,t,null),Lee(t,this.feedLossFns,this.feedOutputShapes),this.stateful&&r!=null&&r>0&&e[0].shape[0]%r!=0)throw new B(`In a stateful network, you should only pass inputs with a number of samples that is divisible by the batch size ${r}. Found: ${e[0].shape[0]} sample(s).`);return[e,t]}async standardizeUserData(e,t,n,r,a=!0,s){let[i,o]=this.standardizeUserDataXY(e,t,a,s);if(n!=null)throw new Error("sample weight is not supported yet.");let l=null;if(r!=null){let c=O3(r,this.outputNames);l=[];for(let u=0;u<c.length;++u)l.push(await z3(o[u],null,c[u]))}return[i,o,l]}testLoop(e,t,n,r=0,a){return U(()=>{let s=this.checkNumSamples(t,n,a,"steps"),i=[];if(r>0)throw new De("Verbose mode is not implemented yet.");if(a!=null)throw new De("steps mode in testLoop() is not implemented yet");{let o=Iy(s,n),l=Qt(wr(0,s));for(let c=0;c<o.length;++c){let u=o[c][0],h=o[c][1],d=fi(l,u,h-u),p=ky(t,d),f=e(p);if(c===0)for(let m=0;m<f.length;++m)i.push(Se(0));for(let m=0;m<f.length;++m){let A=f[m];i[m]=oe(i[m],W(h-u,A))}}for(let c=0;c<i.length;++c)i[c]=Ne(i[c],s)}return i})}getDedupedMetricsNames(){let e=this.metricsNames,t=[];for(let n=0;n<e.length;++n){let r=e[n],a=r;Yb(e,r)>1&&(a+=`_${Yb(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 c=[];for(let p=0;p<this.inputs.length;++p)c.push({key:this.inputs[p],value:n[p]});let u=new Ai(c),h=Tc(this.outputs,u,{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=Tee(f,a[p]));let m=bt(f);t.push(m),p===0?d=f:d=oe(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=bt(m(r[A],h[A]))}Bt(f),s.push(f)}return d=bt(d),this.calculateLosses().forEach(p=>{d=oe(d,p)}),d},o=this.collectedTrainableWeights.map(c=>c.read()),l=!0;return[this.optimizer_.minimize(i,l,o)].concat(s)}}makeTestFunction(){this.testFunction=e=>U(()=>{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 Ai(s),o=Tc(this.outputs,i);for(let l=0;l<this.lossFunctions.length;++l){let c=this.lossFunctions[l],u=bt(c(a[l],o[l]));l===0?n=u:n=oe(n,u),t.push(n)}for(let l=0;l<this.metricsTensors.length;++l){let c=this.metricsTensors[l][0],u=this.metricsTensors[l][1],h=bt(c(a[u],o[u]));t.push(h)}return t})}async fit(e,t,n={}){return Oee(this,e,t,n)}async fitDataset(e,t){return Fee(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 Ce(s),An(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=Gh().numTensors;this.optimizer_.dispose(),e.numDisposedVariables+=t-Gh().numTensors}return e}getLossIdentifiers(){let e;if(typeof this.loss=="string")e=ia(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=>ia(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]=ia(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[ia(zp(this.metrics))];if(Array.isArray(this.metrics))return this.metrics.map(e=>ia(zp(e)));{let e={};for(let t in this.metrics)e[t]=ia(zp(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=Sc(e.optimizer_config),n=_r(t),r;if(typeof e.loss=="string")r=hi(e.loss);else if(Array.isArray(e.loss))r=e.loss.map(s=>hi(s));else if(e.loss!=null){r={};for(let s in e.loss)r[s]=hi(e.loss[s])}let a;if(Array.isArray(e.metrics))a=e.metrics.map(s=>hi(s));else if(e.metrics!=null){a={};for(let s in e.metrics)a[s]=hi(e.metrics[s])}this.compile({loss:r,metrics:a,optimizer:n})}async save(e,t){if(typeof e=="string"){let i=dn.getSaveHandlers(e);if(i.length===0)throw new B(`Cannot find any save handlers for URL '${e}'`);if(i.length>1)throw new B(`Found more than one (${i.length}) save handlers for URL '${e}'`);e=i[0]}if(e.save==null)throw new B("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");let n=await dn.encodeWeights(this.getNamedWeights(t)),r=!1,a=null,s={modelTopology:this.toJSON(a,r),format:Bee,generatedBy:`TensorFlow.js tfjs-layers v${Am}`,convertedBy:null};if((t==null?!1:t.includeOptimizer)&&this.optimizer!=null){s.trainingConfig=this.getTrainingConfig();let i="optimizer",{data:o,specs:l}=await dn.encodeWeights(await this.optimizer.getWeights(),i);n.specs.push(...l),n.data=dn.concatenateArrayBuffers([n.data,o])}if(this.userDefinedMetadata!=null){let i=!0;F3(this.userDefinedMetadata,this.name,i),s.userDefinedMetadata=this.userDefinedMetadata}return s.weightData=n.data,s.weightSpecs=n.specs,e.save(s)}setUserDefinedMetadata(e){F3(e,this.name),this.userDefinedMetadata=e}getUserDefinedMetadata(){return this.userDefinedMetadata}};ea.className="Model";re.registerClass(ea);var j3=class extends ea{};j3.className="Functional";re.registerClass(j3);async function Vee(e,t){"modelTopology"in e||(e={modelTopology:e}),e=e;let n=e.modelTopology;n.model_config!=null&&(n=n.model_config);let r=Sc(n),a=_r(r,t);if(e.weightsManifest!=null){let s=await dn.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),Ce(s)}return a}async function Hee(e,t){if(t==null&&(t={}),typeof e=="string"){let n=dn.getLoadHandlers(e,t);if(n.length===0)n.push(dn.browserHTTPRequest(e,t));else if(n.length>1)throw new B(`Found more than one (${n.length}) load handlers for URL '${e}'`);e=n[0]}return Uee(e,void 0,t)}async function Uee(e,t,n){if(n==null&&(n={}),e.load==null)throw new B("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=_r(Sc(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 B("LayersModel artifacts contains weight data, but not weight specs. Therefore loading of weights cannot proceed.");let{modelWeights:c,optimizerWeights:u}=jee(r.weightData,r.weightSpecs);o.loadWeights(c,s),o.optimizer!=null&&u.length>0&&await o.optimizer.setWeights(u),Ce(c),Ce(u.map(h=>h.tensor))}return o}function jee(e,t){let n=dn.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 Yo=class extends ea{constructor(e){super({inputs:[],outputs:[]});if(e=e||{},this.trainable=!0,this.built=!1,this.name=e.name!=null?e.name:Sp("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 B(`Negative dimension size caused by adding layer ${e.name} with input shape [${e.inboundNodes[0].inputTensors[0].shape}]`)}add(e){let t=e instanceof Yo||e instanceof ea,n;if(t){if(n=e,n.outputs.length!==1)throw new B("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 B("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 B("The first layer in a Sequential model must get an `inputShape` or `batchInputShape` argument.");let r=_3({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 B(`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 B("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=w3(this.outputs[0])}this.inboundNodes=[],new Cp({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(dt(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 ea({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 xr("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 xr("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 xr("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 xr("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 B("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 Yo))throw new De(`Sequential.fromConfig called on non-Sequential input: ${i}`);for(let o of a){let l=_r(o,void 0,r);r&&l.setFastWeightInitDuringBuild(!0),i.add(l)}return i}set stopTraining(e){if(this.model==null)throw new B("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 B("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}}};Yo.className="Sequential";re.registerClass(Yo);function y8(e){return new ea(e)}function g8(e){return new Yo(e)}function x8(e,t){return t==null&&(t={}),Hee(e,t)}function O0(e){return _3(e)}function w8(e,t){lr.registerCallbackConstructor(e,t)}var Fn=class extends re.Serializable{getConfig(){return{}}},G3=class extends Fn{apply(e,t=1){return SY(e,t)}};G3.className="elu";re.registerClass(G3);var q3=class extends Fn{apply(e){return dd(e)}};q3.className="selu";re.registerClass(q3);var X3=class extends Fn{apply(e){return Cr(e)}};X3.className="relu";re.registerClass(X3);var K3=class extends Fn{apply(e){return U(()=>Xo(6,Cr(e)))}};K3.className="relu6";re.registerClass(K3);var Z3=class extends Fn{apply(e){return e}};Z3.className="linear";re.registerClass(Z3);var J3=class extends Fn{apply(e){return er(e)}};J3.className="sigmoid";re.registerClass(J3);var Y3=class extends Fn{apply(e){return EY(e)}};Y3.className="hardSigmoid";re.registerClass(Y3);var Q3=class extends Fn{apply(e){return Go(e)}};Q3.className="softplus";re.registerClass(Q3);var e7=class extends Fn{apply(e){return TY(e)}};e7.className="softsign";re.registerClass(e7);var t7=class extends Fn{apply(e){return Vo(e)}};t7.className="tanh";re.registerClass(t7);var Sy=class extends Fn{apply(e,t=-1){return Wu(e,t)}};Sy.className="softmax";re.registerClass(Sy);var n7=class extends Fn{apply(e,t=-1){return sd(e,t)}};n7.className="logSoftmax";re.registerClass(n7);var r7=class extends Fn{apply(e,t=1){return U(()=>er(e.mul(t)).mul(e))}};r7.className="swish";re.registerClass(r7);function za(e){return e.getClassName()}function Ty(e,t={}){return gc(e,re.SerializationMap.getMap().classNameMap,t,"activation")}function Pa(e){if(e==null){let t={};return t.className="linear",t.config={},Ty(t)}if(typeof e=="string"){let t={};return t.className=e,t.config={},Ty(t)}else return e instanceof Fn?e:Ty(e)}function Ey(e){if(e!=null&&typeof e!="object")throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${e}`)}var a7=class extends re.Serializable{},Cc=class extends a7{constructor(e){super();Ey(e),this.l1=e==null||e.l1==null?.01:e.l1,this.l2=e==null||e.l2==null?.01:e.l2,this.hasL1=this.l1!==0,this.hasL2=this.l2!==0}apply(e){return U(()=>{let t=Ct([1]);return this.hasL1&&(t=oe(t,Te(W(this.l1,$t(e))))),this.hasL2&&(t=oe(t,Te(W(this.l2,vc(e))))),t.asScalar()})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(e,t){return new e({l1:t.l1,l2:t.l2})}};Cc.className="L1L2";re.registerClass(Cc);function Gee(e){return Ey(e),new Cc({l1:e!=null?e.l1:null,l2:0})}function qee(e){return Ey(e),new Cc({l2:e!=null?e.l2:null,l1:0})}var s7={l1l2:"L1L2"};function pt(e){return HA(e)}function i7(e,t={}){return gc(e,re.SerializationMap.getMap().classNameMap,t,"regularizer")}function xt(e){if(e==null)return null;if(typeof e=="string"){let t={className:e in s7?s7[e]:e,config:{}};return i7(t)}else return e instanceof a7?e:i7(e)}var Cy=class extends Xe{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null&&(this.maxValue=e.maxValue)}call(e,t){e=Pe(e);let n=Cr(e);return this.maxValue!=null&&(n=pn(n,0,this.maxValue)),n}computeOutputShape(e){return e}getConfig(){let e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}};Cy.className="ReLU";re.registerClass(Cy);var Ry=class extends Xe{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=Pe(e);return Mu(n,this.alpha)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};Ry.className="LeakyReLU";re.registerClass(Ry);var Fy=class extends Xe{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=gt(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=xt(e.alphaRegularizer),this.alphaConstraint=Lt(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 B(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=dt(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let r of this.sharedAxes)t[r-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let r=1;r<e.length;++r)n[r]=e[r];this.inputSpec=[new Vt({ndim:e.length,axes:n})],this.built=!0}call(e,t){return e=Pe(e),zu(e,this.alpha.read())}getConfig(){let e={alphaInitializer:kt(this.alphaInitializer),alphaRegularizer:pt(this.alphaRegularizer),alphaConstraint:Pt(this.alphaConstraint),sharedAxes:this.sharedAxes},t=super.getConfig();return Object.assign(e,t),e}};Fy.className="PReLU";re.registerClass(Fy);var My=class extends Xe{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA=1,e==null&&(e={}),e.alpha!=null&&e.alpha!==this.DEFAULT_ALPHA)throw new De(`Non-default alpha value (${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=Pe(e);return Ho(n)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};My.className="ELU";re.registerClass(My);var $y=class extends Xe{constructor(e){super(e==null?{}:e);this.DEFAULT_THETA=1,e==null&&(e={}),this.theta=e.theta==null?this.DEFAULT_THETA:e.theta}call(e,t){let n=Pe(e);return n.mul(_c(n.greater(this.theta),"float32"))}computeOutputShape(e){return e}getConfig(){let e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};$y.className="ThresholdedReLU";re.registerClass($y);var Dy=class extends Xe{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new Sy().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Pe(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}};Dy.className="Softmax";re.registerClass(Dy);function Cl(e,t,n){if(typeof e=="number")return ci(e,t);if(e.length!==t)throw new B(`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(!vY(a))throw new B(`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 br(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 Lp(e,t,n,r){if(e==null)return null;if(r==="valid")e=e*t+Da([n-t,0]);else if(r==="same")e=e*t;else throw new B(`Unsupport padding mode: ${r}.`);return e}function Oy(e,t){return U(()=>(Tt(t),t==="channelsFirst"?at(e,[0,2,3,1]):e))}function o7(e,t){return U(()=>(Tt(t),t==="channelsFirst"?at(e,[0,2,3,4,1]):e))}function Xee(e,t,n,r=1,a="valid",s,i=1){return U(()=>{if(s==null&&(s=gr()),Tt(s),e.shape.length!==3)throw new B(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new B(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new B(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(s==="channelsFirst"&&(e=at(e,[0,2,1])),a==="causal")throw new De("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=Yh(e,t,r,a==="same"?"same":"valid","NWC",i);return n!=null&&(o=Vr(o,n)),o})}function l7(e,t,n,r=[1,1],a="valid",s,i,o=null){return U(()=>{if(s==null&&(s=gr()),Tt(s),e.rank!==3&&e.rank!==4)throw new B(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new B(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=Oy(e,s);if(a==="causal")throw new De("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=va.conv2d({x:l,filter:t,strides:r,pad:a==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=at(l,[0,3,1,2])),l})}function Kee(e,t,n,r=[1,1,1],a="valid",s,i){return U(()=>{if(s==null&&(s=gr()),Tt(s),e.rank!==4&&e.rank!==5)throw new B(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new B(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=o7(e,s);if(a==="causal")throw new De("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=Vf(o,t,r,a==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Vr(o,n)),s==="channelsFirst"&&(o=at(o,[0,4,1,2,3])),o})}var zy=class extends Xe{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",zy.verifyArgs(t),this.rank=e,jt(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new De(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Cl(t.kernelSize,e,"kernelSize"),this.strides=Cl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,jn(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Tt(this.dataFormat),this.activation=Pa(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=gt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Lt(t.biasConstraint),this.biasRegularizer=xt(t.biasRegularizer),this.activityRegularizer=xt(t.activityRegularizer),this.dilationRate=Cl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new B(`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 B(`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 B(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Wr("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!GA(e.kernelSize,"number",1,3))throw new B(`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:za(this.activation),useBias:this.useBias,biasInitializer:kt(this.biasInitializer),biasRegularizer:pt(this.biasRegularizer),activityRegularizer:pt(this.activityRegularizer),biasConstraint:Pt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Rc=class extends zy{constructor(e,t){super(e,t);this.kernel=null,Rc.verifyArgs(t),this.filters=t.filters,jt(this.filters,"filters"),this.kernelInitializer=gt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Lt(t.kernelConstraint),this.kernelRegularizer=xt(t.kernelRegularizer)}build(e){e=dt(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new B(`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 U(()=>{e=Pe(e);let n,r=this.bias==null?null:this.bias.read(),a=e3(this.activation.getClassName());if(a!=null&&this.rank===2)n=l7(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate,a);else{if(this.rank===1)n=Xee(e,this.kernel.read(),r,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=l7(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=Kee(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new De("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=dt(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=br(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:kt(this.kernelInitializer),kernelRegularizer:pt(this.kernelRegularizer),kernelConstraint:Pt(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 B(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Fc=class extends Rc{constructor(e){super(2,e);Fc.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!GA(e.kernelSize,"number",1,2))throw new B(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Fc.className="Conv2D";re.registerClass(Fc);var Wp=class extends Rc{constructor(e){super(3,e);Wp.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 B(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};Wp.className="Conv3D";re.registerClass(Wp);var Py=class extends Fc{constructor(e){super(e);if(this.inputSpec=[new Vt({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new B(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=dt(e),e.length!==4)throw new B("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new B("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Vt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return U(()=>{let n=Pe(e);if(n.shape.length!==4)throw new B(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${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],c=this.kernelSize[0],u=this.kernelSize[1],h=this.strides[0],d=this.strides[1],p=Lp(o,h,c,this.padding),f=Lp(l,d,u,this.padding),m=[a,p,f,this.filters];this.dataFormat!=="channelsLast"&&(n=at(n,[0,2,3,1]));let A=Qh(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(A=at(A,[0,3,1,2])),this.bias!=null&&(A=Vr(A,this.bias.read(),this.dataFormat)),this.activation!=null&&(A=this.activation.apply(A)),A})}computeOutputShape(e){e=dt(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]=Lp(t[r],o,s,this.padding),t[a]=Lp(t[a],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};Py.className="Conv2DTranspose";re.registerClass(Py);var u7=class extends Rc{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 B("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new B("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 B(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=gt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=xt(t.depthwiseRegularizer),this.depthwiseConstraint=Lt(t.depthwiseConstraint),this.pointwiseInitializer=gt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=xt(t.pointwiseRegularizer),this.pointwiseConstraint=Lt(t.pointwiseConstraint)}build(e){if(e=dt(e),e.length<this.rank+2)throw new B(`Inputs to SeparableConv${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 B(`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 Vt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return U(()=>{e=Pe(e);let n;if(this.rank===1)throw new De("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=at(e,[0,2,3,1])),n=nm(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Vr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=at(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=kt(this.depthwiseInitializer),e.pointwiseInitializer=kt(this.pointwiseInitializer),e.depthwiseRegularizer=pt(this.depthwiseRegularizer),e.pointwiseRegularizer=pt(this.pointwiseRegularizer),e.depthwiseConstraint=Pt(this.depthwiseConstraint),e.pointwiseConstraint=Pt(this.pointwiseConstraint),e}};u7.className="SeparableConv";var Ly=class extends u7{constructor(e){super(2,e)}};Ly.className="SeparableConv2D";re.registerClass(Ly);var Bp=class extends Rc{constructor(e){super(1,e);Bp.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"&&!GA(e.kernelSize,"number",1,1))throw new B(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};Bp.className="Conv1D";re.registerClass(Bp);var Wy=class extends Xe{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 U(()=>{if(e=Pe(e),this.dataFormat==="channelsLast"){let n=yp(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return yp(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=yp(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return yp(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}};Wy.className="Cropping2D";re.registerClass(Wy);var By=class extends Xe{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,Tt(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,wY(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 U(()=>{let n=Pe(e),r=n.shape;if(this.dataFormat==="channelsFirst"){n=at(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 at(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}};By.className="UpSampling2D";re.registerClass(By);function Zee(e,t,n=[1,1],r="valid",a,s){return U(()=>{a==null&&(a=gr()),Tt(a);let i=Oy(e,a);if(e.rank!==4)throw new B(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new B(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=Uo(i,t,n,r==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=at(i,[0,3,1,2])),i})}var Vy=class extends zy{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=gt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Lt(e.depthwiseConstraint),this.depthwiseRegularizer=xt(e.depthwiseRegularizer)}build(e){if(e=dt(e),e.length<4)throw new B(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new B(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${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 U(()=>{e=Pe(e);let n=Zee(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Vr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=dt(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=br(t,this.kernelSize[0],this.padding,this.strides[0]),s=br(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=kt(this.depthwiseInitializer),e.depthwiseRegularizer=pt(this.depthwiseRegularizer),e.depthwiseConstraint=Pt(this.depthwiseRegularizer),e}};Vy.className="DepthwiseConv2D";re.registerClass(Vy);function c7(e,t,n,r){if(Array.isArray(e)){if(t!=null||n!=null)throw new B("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 h7(e,t,n,r=!1,a,s,i=!1,o=!1){return U(()=>{let l=t.shape.length;if(l<3)throw new B(`Input should be at least 3D, but is ${l}D.`);let c=[1,0].concat(wr(2,l));if(t=at(t,c),s!=null)throw new De("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=vn(a,-1)),a=at(a,c)),r&&(t=Nn(t,0),a!=null&&(a=Nn(a,0)));let u=[],h,d=n,p=t.shape[0],f=rr(t),m;a!=null&&(m=rr(a));for(let y=0;y<p;++y){let g=f[y],w=U(()=>e(g,d));if(a==null)h=w[0],d=w[1];else{let x=U(()=>{let _=m[y],I=In(_).sub(_),T=w[0].mul(_).add(d[0].mul(I)),E=d.map((N,F)=>w[1][F].mul(_).add(N.mul(I)));return{output:T,newStates:E}});h=x.output,d=x.newStates}o&&u.push(h)}let A;return o&&(A=Sn(u,1)),[h,A,d]})}var Fr=class extends Xe{constructor(e){super(e);let t;if(e.cell==null)throw new B("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Vp({cells:e.cell}):t=e.cell,t.stateSize==null)throw new B("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 Vt({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 wr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){dy(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 U(()=>{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 De("Constants support is not implemented in RNN yet.");dy(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,r=e.slice(2);this.inputSpec[0]=new Vt({shape:[n,null,...r]});let a=[e[0]].concat(e.slice(2));if(t!=null)throw new De("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 B(`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 Vt({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){U(()=>{if(!this.stateful)throw new sa("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new B("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=>Ct([n,r])):this.states_=[Ct([n,this.cell.stateSize])];else if(e==null)Ce(this.states_),this.keptStates!=null&&(Ce(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>Ct([n,r])):this.states_[0]=Ct([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new B(`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()):Ce(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 B(`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=>Bt(r.clone()))})}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=c7(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 Vt({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 mr){let o=[e].concat(s),l=this.inputSpec.concat(i),c=this.inputSpec;this.inputSpec=l;let u=super.apply(o,t);return this.inputSpec=c,u}else return super.apply(e,t)}call(e,t){return U(()=>{let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;e=Pe(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 B(`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=h7((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],c=o[1],u=o[2];this.stateful&&this.resetStates(u,r);let h=this.returnSequences?c:l;return this.returnState?[h].concat(u):h})}getInitialState(e){return U(()=>{let t=Ct(e.shape);return t=Te(t,[1,2]),t=bc(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?YA(t,[1,n]):t):this.cell.stateSize>1?[YA(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()===Fr.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let r=t.cell,a=_r(r,n);return new e(Object.assign(t,{cell:a}))}};Fr.className="RNN";re.registerClass(Fr);var Ic=class extends Xe{},Up=class extends Ic{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=Pa(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=gt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=gt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=gt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=xt(e.kernelRegularizer),this.recurrentRegularizer=xt(e.recurrentRegularizer),this.biasRegularizer=xt(e.biasRegularizer),this.kernelConstraint=Lt(e.kernelConstraint),this.recurrentConstraint=Lt(e.recurrentConstraint),this.biasConstraint=Lt(e.biasConstraint),this.dropout=Nl([1,Da([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Nl([1,Da([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=dt(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 U(()=>{if(e=e,e.length!==2)throw new B(`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=La({ones:()=>In(e),rate:this.dropout,training:r})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=La({ones:()=>In(n),rate:this.recurrentDropout,training:r}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=Br(W(e,s),this.kernel.read()):a=Br(e,this.kernel.read()),this.bias!=null&&(a=Vr(a,this.bias.read())),i!=null&&(n=W(n,i));let o=oe(a,Br(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:za(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:pt(this.kernelRegularizer),recurrentRegularizer:pt(this.recurrentRegularizer),biasRegularizer:pt(this.biasRegularizer),activityRegularizer:pt(this.activityRegularizer),kernelConstraint:Pt(this.kernelConstraint),recurrentConstraint:Pt(this.recurrentConstraint),biasConstraint:Pt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};Up.className="SimpleRNNCell";re.registerClass(Up);var Uy=class extends Fr{constructor(e){e.cell=new Up(e),super(e)}call(e,t){return U(()=>{this.cell.dropoutMask!=null&&(Ce(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ce(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)}};Uy.className="SimpleRNN";re.registerClass(Uy);var Hp=class extends Ic{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 B("GRUCell does not support reset_after parameter set to true.");this.units=e.units,jt(this.units,"units"),this.activation=Pa(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Pa(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=gt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=gt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=gt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=xt(e.kernelRegularizer),this.recurrentRegularizer=xt(e.recurrentRegularizer),this.biasRegularizer=xt(e.biasRegularizer),this.kernelConstraint=Lt(e.kernelConstraint),this.recurrentConstraint=Lt(e.recurrentConstraint),this.biasConstraint=Lt(e.biasConstraint),this.dropout=Nl([1,Da([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Nl([1,Da([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=dt(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 U(()=>{if(e=e,e.length!==2)throw new B(`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=La({ones:()=>In(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=La({ones:()=>In(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=W(e,a[0]));let c=Br(e,this.kernel.read());this.useBias&&(c=Vr(c,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(r=W(r,s[0]));let u=this.recurrentKernel.read(),[h,d]=an(u,[2*this.units,this.units],u.rank-1),p=Br(r,h),[f,m,A]=an(c,3,c.rank-1),[y,g]=an(p,2,p.rank-1);i=this.recurrentActivation.apply(oe(f,y)),o=this.recurrentActivation.apply(oe(m,g));let w=Br(W(o,r),d);l=this.activation.apply(oe(A,w));let x=oe(W(i,r),W(oe(1,_t(i)),l));return[x,x]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:za(this.activation),recurrentActivation:za(this.recurrentActivation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:pt(this.kernelRegularizer),recurrentRegularizer:pt(this.recurrentRegularizer),biasRegularizer:pt(this.biasRegularizer),activityRegularizer:pt(this.activityRegularizer),kernelConstraint:Pt(this.kernelConstraint),recurrentConstraint:Pt(this.recurrentConstraint),biasConstraint:Pt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};Hp.className="GRUCell";re.registerClass(Hp);var Hy=class extends Fr{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 Hp(e),super(e)}call(e,t){return U(()=>{this.cell.dropoutMask!=null&&(Ce(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ce(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)}};Hy.className="GRU";re.registerClass(Hy);var Mc=class extends Ic{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=Pa(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Pa(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=gt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=gt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=gt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=xt(e.kernelRegularizer),this.recurrentRegularizer=xt(e.recurrentRegularizer),this.biasRegularizer=xt(e.biasRegularizer),this.kernelConstraint=Lt(e.kernelConstraint),this.recurrentConstraint=Lt(e.recurrentConstraint),this.biasConstraint=Lt(e.biasConstraint),this.dropout=Nl([1,Da([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Nl([1,Da([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=dt(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 or{apply(i,o){let l=a.apply([s]),c=new xp().apply([s]),u=a.apply([s*2]);return u3(u3(l,c),u)}},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 U(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new B(`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=La({ones:()=>In(e),rate:this.dropout,training:n,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=La({ones:()=>In(r),rate:this.recurrentDropout,training:n,count:4}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,c,u;0<this.dropout&&this.dropout<1&&(e=W(e,s[0]));let h=Br(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(r=W(r,i[0])),h=oe(h,Br(r,this.recurrentKernel.read())),this.useBias&&(h=Vr(h,this.bias.read()));let[d,p,f,m]=an(h,4,h.rank-1);o=this.recurrentActivation.apply(d),l=this.recurrentActivation.apply(p),c=oe(W(l,a),W(o,this.activation.apply(f))),u=this.recurrentActivation.apply(m);let A=W(u,this.activation.apply(c));return[A,A,c]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:za(this.activation),recurrentActivation:za(this.recurrentActivation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:pt(this.kernelRegularizer),recurrentRegularizer:pt(this.recurrentRegularizer),biasRegularizer:pt(this.biasRegularizer),activityRegularizer:pt(this.activityRegularizer),kernelConstraint:Pt(this.kernelConstraint),recurrentConstraint:Pt(this.recurrentConstraint),biasConstraint:Pt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};Mc.className="LSTMCell";re.registerClass(Mc);var jy=class extends Fr{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 Mc(e),super(e)}call(e,t){return U(()=>{this.cell.dropoutMask!=null&&(Ce(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ce(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)}};jy.className="LSTM";re.registerClass(jy);var Vp=class extends Ic{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 U(()=>{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){dy(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,r)=>{pi(`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(_r(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 py(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]])}fy(t)}};Vp.className="StackedRNNCells";re.registerClass(Vp);function La(e){let{ones:t,rate:n,training:r=!1,count:a=1}=e,s=()=>h3(t(),n),i=()=>kc(s,t,r);return!a||a<=1?Bt(i().clone()):Array(a).fill(void 0).map(i).map(o=>Bt(o.clone()))}var Jee=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},d7=class extends Fr{constructor(e){if(e.unroll)throw new De("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new De("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new Vt({ndim:5})]}call(e,t){return U(()=>{if(this.cell.dropoutMask!=null&&(Ce(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ce(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new B("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 U(()=>{let{stateSize:t}=this.cell,n=e.shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)],s=Ct(a);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){U(()=>{if(!this.stateful)throw new sa("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 B("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(()=>Ct(a)):this.states_=[Ct(a)];else if(e==null)Ce(this.states_),this.keptStates!=null&&(Ce(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Ct(a)):this.states_[0]=Ct(a);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new B(`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()):Ce(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 B(`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=>Bt(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],c=e[o?4:3],u=br(l,r[0],a,s[0],i[0]),h=br(c,r[1],a,s[1],i[1]);return[...e.slice(0,2),...o?[n,u,h]:[u,h,n]]}};d7.className="ConvRNN2D";var jp=class extends Mc{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=Cl(n,2,"kernelSize"),this.kernelSize.forEach(o=>jt(o,"kernelSize")),this.strides=Cl(r||1,2,"strides"),this.strides.forEach(o=>jt(o,"strides")),this.padding=a||"valid",jn(this.padding),this.dataFormat=s||"channelsLast",Tt(this.dataFormat),this.dilationRate=Cl(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>jt(o,"dilationRate"))}build(e){var t;e=dt(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new B(`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,c=this.filters;o=new(t=class extends or{apply(u,h){let d=l.apply([c]),p=Er([c]),f=l.apply([c*2]);return ey([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 U(()=>{if(e.length!==3)throw new B(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,r=e[0],a=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=La({ones:()=>In(r),rate:this.dropout,training:n,count:i}));let o=this.dropoutMask,l=(J,ae,Y)=>!ae||!ae[Y]?J:W(ae[Y],J),c=l(r,o,0),u=l(r,o,1),h=l(r,o,2),d=l(r,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=La({ones:()=>In(a),rate:this.recurrentDropout,training:n,count:i}));let p=this.recurrentDropoutMask,f=l(a,p,0),m=l(a,p,1),A=l(a,p,2),y=l(a,p,3),g=3,[w,x,_,I]=an(this.kernel.read(),i,g),[T,E,N,F]=this.useBias?an(this.bias.read(),i):[null,null,null,null];c=this.inputConv(c,w,T,this.padding),u=this.inputConv(u,x,E,this.padding),h=this.inputConv(h,_,N,this.padding),d=this.inputConv(d,I,F,this.padding);let[$,D,P,H]=an(this.recurrentKernel.read(),i,g);f=this.recurrentConv(f,$),m=this.recurrentConv(m,D),A=this.recurrentConv(A,P),y=this.recurrentConv(y,H);let V=this.recurrentActivation.apply(oe(c,f)),K=this.recurrentActivation.apply(oe(u,m)),X=oe(W(K,s),W(V,this.activation.apply(oe(h,A)))),ee=W(this.recurrentActivation.apply(oe(d,y)),this.activation.apply(X));return[ee,ee,X]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=Jee(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=Zr(e,t,this.strides,r||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Vr(a,n,this.dataFormat):a}recurrentConv(e,t){return Zr(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};jp.className="ConvLSTM2DCell";re.registerClass(jp);var Gy=class extends d7{constructor(e){let t=new jp(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};Gy.className="ConvLSTM2D";re.registerClass(Gy);var Gp=class extends Xe{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 U(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(0<this.rate&&this.rate<1){let r=t.training==null?!1:t.training,a=this.getNoiseShape(n);return kc(()=>h3(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()}};Gp.className="Dropout";re.registerClass(Gp);var qy=class extends Gp{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};qy.className="SpatialDropout1D";re.registerClass(qy);var Xy=class extends Xe{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=Pa(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=gt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=gt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Lt(e.kernelConstraint),this.biasConstraint=Lt(e.biasConstraint),this.kernelRegularizer=xt(e.kernelRegularizer),this.biasRegularizer=xt(e.biasRegularizer),this.activityRegularizer=xt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=dt(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=dt(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return U(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=e3(this.activation.getClassName()),a;return r!=null?a=Br(n,this.kernel.read(),r,this.bias?this.bias.read():null):(a=Br(n,this.kernel.read()),this.bias!=null&&(a=Vr(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:za(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:pt(this.kernelRegularizer),biasRegularizer:pt(this.biasRegularizer),activityRegularizer:pt(this.activityRegularizer),kernelConstraint:Pt(this.kernelConstraint),biasConstraint:Pt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Xy.className="Dense";re.registerClass(Xy);var Ky=class extends Xe{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=dt(e);for(let t of e.slice(1))if(t==null)throw new B(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],$a(e,1)]}call(e,t){return U(()=>{this.invokeCallHook(e,t);let n=Pe(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 NY(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};Ky.className="Flatten";re.registerClass(Ky);var Zy=class extends Xe{constructor(e){super(e);this.supportsMasking=!0,this.activation=Pa(e.activation)}call(e,t){return U(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.activation.apply(n)})}getConfig(){let e={activation:za(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};Zy.className="Activation";re.registerClass(Zy);var Jy=class extends Xe{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 U(()=>(e=Pe(e),kY(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};Jy.className="RepeatVector";re.registerClass(Jy);var Yy=class extends Xe{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 B("Can only specifiy one unknown dimension.");else a*=l}let i=$a(e);if(s!==null){if(a===0||i%a!=0)throw new B(n);r[s]=i/a}else if(i!==a)throw new B(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 U(()=>{this.invokeCallHook(e,t);let n=Pe(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}};Yy.className="Reshape";re.registerClass(Yy);var Qy=class extends Xe{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=wr(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 Vt({ndim:this.dims.length+1})]}computeOutputShape(e){e=dt(e);let t=e.slice();return this.dims.forEach((n,r)=>{t[r+1]=e[n]}),t}call(e,t){return at(Pe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};Qy.className="Permute";re.registerClass(Qy);var eg=class extends Xe{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=Pe(e),r=-1;return Nu(js(n,this.maskValue),r)}call(e,t){return U(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=-1,a=!0,s=Nu(js(n,this.maskValue),r,a);return n.mul(s.asType(n.dtype))})}};eg.className="Masking";re.registerClass(eg);var tg=class extends Xe{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(mt(e.inputLength))}this.inputDim=e.inputDim,jt(this.inputDim,"inputDim"),this.outputDim=e.outputDim,jt(this.outputDim,"outputDim"),this.embeddingsInitializer=gt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=xt(e.embeddingsRegularizer),this.activityRegularizer=xt(e.activityRegularizer),this.embeddingsConstraint=Lt(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 U(()=>this.maskZero?(e=Pe(e),js(e,He(e))):null)}computeOutputShape(e){if(e=dt(e),this.inputLength==null)return[...e,this.outputDim];let t=mt(this.inputLength);if(t.length!==e.length-1)throw new B(`"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 B(`"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 U(()=>{this.invokeCallHook(e,t);let n=Pe(e);return n.dtype!=="int32"&&(n=_c(n,"int32")),c3(this.embeddings.read(),n.as1D()).reshape(dt(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:kt(this.embeddingsInitializer),embeddingsRegularizer:pt(this.embeddingsRegularizer),activityRegularizer:pt(this.activityRegularizer),embeddingsConstraint:Pt(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};tg.className="Embedding";re.registerClass(tg);var gi=class extends Xe{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new De}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 B("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=[dt(e)]),e=e,e.length<2)throw new B(`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=Ma(t),t.length>1)throw new B(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let n=e[0]==null?null:e[0].slice(1);for(let a=1;a<e.length;++a){let s=e[a]==null?null:e[a].slice(1);n=this.computeElementwiseOpOutputShape(n,s)}let r=e.map(a=>a.length);e.indexOf(null)===-1&&Ma(r).length===1?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return U(()=>{if(e=e,this.reshapeRequired){let n=[],r=e.map(a=>a.rank);if(r.indexOf(null)===-1){let a=Da(r);for(let s of e){let i=s.rank;for(let o=0;o<a-i;++o)s=bc(s,1);n.push(s)}return this.mergeFunction(n)}else{let a=!1;for(let o of e){let l=o.rank;if(l==null){let c=o.shape,u=c[0],h=c.slice(1).concat([u]),d=o.reshape([u].concat($a(c.slice(1))));d=at(d,[1,0]),d=d.reshape(h),n.push(d),a=!0}else if(l>1){let c=wr(1,l).concat([0]);n.push(at(o,c)),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,c=o[l-1],u=[c].concat(o.slice(0,o.length-1));s=at(s.reshape([-1,c]),[1,0]).reshape(u)}else if(i>1){let o=[i-1].concat(wr(0,i-1));s=at(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=Ma(n),n.length===1?t=n.concat(t):t=[null].concat(t),t}computeMask(e,t){return U(()=>{if(t==null)return null;if(!Array.isArray(t))throw new B("`mask` should be an Array");if(!Array.isArray(e))throw new B("`inputs` should be an Array");if(t.length!==e.length)throw new B(`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:vn(r,0));let n=t[0];for(let r=1;r<t.length-1;++r)n=nr(n,t[r]);return n})}},ng=class extends gi{constructor(e){super(e)}mergeFunction(e){return U(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=oe(t,e[n]);return t})}};ng.className="Add";re.registerClass(ng);var rg=class extends gi{constructor(e){super(e)}mergeFunction(e){return U(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=W(t,e[n]);return t})}};rg.className="Multiply";re.registerClass(rg);var ag=class extends gi{constructor(e){super(e)}mergeFunction(e){return U(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=oe(t,e[n]);return W(1/e.length,t)})}};ag.className="Average";re.registerClass(ag);var sg=class extends gi{constructor(e){super(e)}mergeFunction(e){return U(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=Tr(t,e[n]);return t})}};sg.className="Maximum";re.registerClass(sg);var ig=class extends gi{constructor(e){super(e)}mergeFunction(e){return U(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=Xo(t,e[n]);return t})}};ig.className="Minimum";re.registerClass(ig);var og=class extends gi{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 B("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 B("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return U(()=>ey(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new B("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 B("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new B("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new B(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return U(()=>{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(In(e[s]).asType("bool")):t[s].rank<e[s].rank?r.push(vn(t[s],-1)):r.push(t[s]);let a=ct(r,this.axis);return Zh(a,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};og.className="Concatenate";re.registerClass(og);function $c(e,t){for(;e<0;)e+=t;return e}function Yee(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new De("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 De("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 U(()=>{let i;if(r>a){i=r-a;let l=[];for(let c=0;c<i;++c)l.push(1);t=t.reshape(t.shape.concat(l))}else if(a>r){i=a-r;let l=[];for(let c=0;c<i;++c)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,c=s[1]===t.shape.length-1;o=e.matMul(t,l,c)}if(i>0){let l;r>a?l=r+a-3:l=r-1;let c=[];for(let u=l;u<l+i;++u)c.push(u);o=o.squeeze(c)}return o.shape.length===1&&(o=o.expandDims(1)),o})}var lg=class extends gi{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 De("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 B(`Dimension incompatibility: ${t[r[0]]} !== ${n[r[1]]}`)}mergeFunction(e){if(e.length!==2)throw new B(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],n=e[1],r;return Array.isArray(this.axes)?r=this.axes.map((a,s)=>$c(a,e[s].shape.length)):r=[$c(this.axes,t.shape.length),$c(this.axes,n.shape.length)],this.normalize&&(t=Rp(t,r[0]),n=Rp(n,r[1])),Yee(t,n,r)}interpretAxes(e,t){let n;return Array.isArray(this.axes)?n=this.axes:n=[$c(this.axes,e.length),$c(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 De("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}};lg.className="Dot";re.registerClass(lg);var ug=class extends Xe{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 U(()=>{this.invokeCallHook(e,t);let n=Pe(e);return kc(()=>gp(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};ug.className="GaussianNoise";re.registerClass(ug);var cg=class extends Xe{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 U(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.rate>0&&this.rate<1?kc(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return n.mul(gp(n.shape,1,r))},()=>n,t.training||!1):n})}};cg.className="GaussianDropout";re.registerClass(cg);var hg=class extends Xe{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Pe(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 U(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return kc(()=>{let r=Pe(e),a=1.6732632423543772,s=1.0507009873554805,i=-a*s,o=_a(Ko(n),this.rate);o=_c(o,"float32");let l=((1-this.rate)*(1+this.rate*i**2))**-.5,c=-l*i*this.rate;return r.mul(o).add(o.add(-1).mul(i)).mul(l).add(c)},()=>Pe(e),t.training||!1)}return e})}};hg.className="AlphaDropout";re.registerClass(hg);function Dc(e,t,n,r,a,s=.001){let i;if(e.rank===2)i=q2(e,t,n,r,a,s);else if(e.rank===3)i=X2(e,t,n,r,a,s);else if(e.rank===4)i=K2(e,t,n,r,a,s);else throw new De(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return i}function Qee(e,t,n,r,a=.001){return U(()=>{let s=od(e,r),i=s.mean,o=s.variance;return[Dc(e,i,o,n,t,a),i,o]})}function ete(e,t,n,r,a=.001){return U(()=>{let s=od(e,r),i=s.mean,o=s.variance,l=[];for(let p of wr(0,e.rank))r.indexOf(p)!==-1?l.push(1):l.push(e.shape[p]);let c=i.reshape(l),u=o.reshape(l),h=t==null?null:t.reshape(l),d=n==null?null:n.reshape(l);return[Dc(e,c,u,d,h,a),i,o]})}function tte(e,t,n,r,a=.001){return v.arraysEqual(r.slice().sort(),wr(0,e.rank-1))?Qee(e,t,n,r,a):ete(e,t,n,r,a)}var dg=class extends Xe{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=gt(e.betaInitializer||"zeros"),this.gammaInitializer=gt(e.gammaInitializer||"ones"),this.movingMeanInitializer=gt(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=gt(e.movingVarianceInitializer||"ones"),this.betaConstraint=Lt(e.betaConstraint),this.gammaConstraint=Lt(e.gammaConstraint),this.betaRegularizer=xt(e.betaRegularizer),this.gammaRegularizer=xt(e.gammaRegularizer)}build(e){e=dt(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new B(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new Vt({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 U(()=>{let n=t.training==null?!1:t.training,r=Pe(e),a=r.shape,s=a.length,i=wr(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 c=i.slice();c.sort();let u=!v.arraysEqual(c,wr(0,s).slice(0,s-1)),h=()=>{if(u){let A=this.movingMean.read().reshape(l),y=this.movingVariance.read().reshape(l),g=this.center?this.beta.read().reshape(l):null,w=this.scale?this.gamma.read().reshape(l):null;return Dc(r,A,y,g,w,this.epsilon)}else return Dc(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]=tte(r,this.gamma.read(),this.beta.read(),i,this.epsilon),m=(A,y,g)=>{U(()=>{let w=1-g,x=A.read(),_=x.sub(y).mul(w);A.write(x.sub(_))})};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:kt(this.betaInitializer),gammaInitializer:kt(this.gammaInitializer),movingMeanInitializer:kt(this.movingMeanInitializer),movingVarianceInitializer:kt(this.movingVarianceInitializer),betaRegularizer:pt(this.betaRegularizer),gammaRegularizer:pt(this.gammaRegularizer),betaConstraint:Pt(this.betaConstraint),gammaConstraint:Pt(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};dg.className="BatchNormalization";re.registerClass(dg);var pg=class extends Xe{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=gt(e.betaInitializer||"zeros"),this.gammaInitializer=gt(e.gammaInitializer||"ones"),this.betaRegularizer=xt(e.betaRegularizer),this.gammaRegularizer=xt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=dt(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!==Ma(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=Pe(e),r=n.shape,a=r.length;return U(()=>{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 c=f=>f!=null&&f.shape.length!==a&&this.axis!==[a-1]?f.reshape(l):f,u=c(this.gamma.read()),h=c(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),u=u.tile(p),h=h.tile(p),Dc(n,i,o,h,u,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:kt(this.betaInitializer),gammaInitializer:kt(this.gammaInitializer),betaRegularizer:pt(this.betaRegularizer),gammaRegularizer:pt(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};pg.className="LayerNormalization";re.registerClass(pg);function nte(e,t,n){return U(()=>{if(e.rank!==4)throw new B(`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 B("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=gr()),n!=="channelsLast"&&n!=="channelsFirst")throw new B(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let r;return n==="channelsFirst"?r=[[0,0],[0,0],t[0],t[1]]:r=[[0,0],t[0],t[1],[0,0]],Jr(e,r)})}var fg=class extends Xe{constructor(e){if(e==null&&(e={}),super(e),this.dataFormat=e.dataFormat==null?gr():e.dataFormat,e.padding==null)this.padding=[[1,1],[1,1]];else if(typeof e.padding=="number")this.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,e.padding.length!==2)throw new B(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${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 B(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${e.padding[0].length} array.`);if(t=e.padding[0],e.padding[1].length!==2)throw new B(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new Vt({ndim:4})]}computeOutputShape(e){e=dt(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 U(()=>nte(Pe(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};fg.className="ZeroPadding2D";re.registerClass(fg);function qp(e,t,n,r,a,s){return U(()=>{Tt(a),r3(s),jn(r),n==null&&(n=[1,1]),r==null&&(r="valid"),a==null&&(a=gr()),s==null&&(s="max"),e=Oy(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=Du(e,t,n,o):i=Tu(e,t,n,o),a==="channelsFirst"&&(i=at(i,[0,3,1,2])),i})}function p7(e,t,n,r,a,s){return U(()=>{Tt(a),r3(s),jn(r),n==null&&(n=[1,1,1]),r==null&&(r="valid"),a==null&&(a=gr()),s==null&&(s="max"),e=o7(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=Jf(e,t,n,o):i=Wf(e,t,n,o),a==="channelsFirst"&&(i=at(i,[0,4,1,2,3])),i})}var f7=class extends Xe{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 B(`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 B(`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,jn(this.padding),this.inputSpec=[new Vt({ndim:3})]}computeOutputShape(e){e=dt(e);let t=br(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return U(()=>{this.invokeCallHook(e,t),e=bc(Pe(e),2);let n=this.poolingFunction(Pe(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return ba(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},mg=class extends f7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),jn(r),qp(e,t,n,r,a,"max")}};mg.className="MaxPooling1D";re.registerClass(mg);var Ag=class extends f7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),jn(r),qp(e,t,n,r,a,"avg")}};Ag.className="AveragePooling1D";re.registerClass(Ag);var m7=class extends Xe{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 B(`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,Tt(this.dataFormat),jn(this.padding),this.inputSpec=[new Vt({ndim:4})]}computeOutputShape(e){e=dt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=br(t,this.poolSize[0],this.padding,this.strides[0]),n=br(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 U(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(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}},yg=class extends m7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),jn(r),qp(e,t,n,r,a,"max")}};yg.className="MaxPooling2D";re.registerClass(yg);var gg=class extends m7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),jn(r),qp(e,t,n,r,a,"avg")}};gg.className="AveragePooling2D";re.registerClass(gg);var A7=class extends Xe{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 B(`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,Tt(this.dataFormat),jn(this.padding),this.inputSpec=[new Vt({ndim:5})]}computeOutputShape(e){e=dt(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=br(t,this.poolSize[0],this.padding,this.strides[0]),n=br(n,this.poolSize[1],this.padding,this.strides[1]),r=br(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 U(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(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}},xg=class extends A7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),jn(r),p7(e,t,n,r,a,"max")}};xg.className="MaxPooling3D";re.registerClass(xg);var wg=class extends A7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),jn(r),p7(e,t,n,r,a,"avg")}};wg.className="AveragePooling3D";re.registerClass(wg);var y7=class extends Xe{constructor(e){super(e);this.inputSpec=[new Vt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new De}},_g=class extends y7{constructor(e){super(e||{})}call(e,t){return U(()=>{let n=Pe(e);return bt(n,1)})}};_g.className="GlobalAveragePooling1D";re.registerClass(_g);var bg=class extends y7{constructor(e){super(e||{})}call(e,t){return U(()=>{let n=Pe(e);return Bn(n,1)})}};bg.className="GlobalMaxPooling1D";re.registerClass(bg);var g7=class extends Xe{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Tt(this.dataFormat),this.inputSpec=[new Vt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new De}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},vg=class extends g7{call(e,t){return U(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?bt(n,[1,2]):bt(n,[2,3])})}};vg.className="GlobalAveragePooling2D";re.registerClass(vg);var kg=class extends g7{call(e,t){return U(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?Bn(n,[1,2]):Bn(n,[2,3])})}};kg.className="GlobalMaxPooling2D";re.registerClass(kg);var x7=class extends Xe{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=_r(r,n);delete t.layer;let s={layer:a};return Object.assign(s,t),new e(s)}},Ig=class extends x7{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=dt(e),e.length<3)throw new B(`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=dt(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 U(()=>(e=Pe(e),h7((n,r)=>[Pe(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};Ig.className="TimeDistributed";re.registerClass(Ig);function rte(e){di(xY,"BidirectionalMergeMode",e)}var ate="concat",Ng=class extends x7{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=_r(n),t.goBackwards=t.goBackwards!==!0;let r={};if(r.className=e.layer.getClassName(),r.config=t,this.backwardLayer=_r(r),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?ate:e.mergeMode,rte(this.mergeMode),e.weights)throw new De("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()):An(r)}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=c7(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 B("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 c=n.map(u=>new Vt({shape:u.shape}));this.forwardLayer.stateSpec=c.slice(0,l/2),this.backwardLayer.stateSpec=c.slice(l/2),i.push(...c)}if(r!=null)throw new De("Support for constants in Bidirectional layers is not implemented yet.");let o=s[0]instanceof mr;for(let l of s)if(l instanceof mr!==o)throw new B("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),c=this.inputSpec.concat(i),u=this.inputSpec;this.inputSpec=c;let h=super.apply(l,t);return this.inputSpec=u,h}else return super.apply(e,t)}call(e,t){return U(()=>{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=Nn(a,1));let i;return this.mergeMode==="concat"?i=ey([r,a]):this.mergeMode==="sum"?i=oe(r,a):this.mergeMode==="ave"?i=W(.5,oe(r,a)):this.mergeMode==="mul"?i=W(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){pi(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),pi(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=_r(t.layer);if(delete t.layer,t.numConstants!=null)throw new De("Deserialization of a Bidirectional layer with numConstants present is not supported yet.");let r=t;return r.layer=n,new e(r)}};Ng.className="Bidirectional";re.registerClass(Ng);function DY(e){return new Sl(e)}function OY(e){return new My(e)}function zY(e){return new Cy(e)}function PY(e){return new Ry(e)}function LY(e){return new Fy(e)}function WY(e){return new Dy(e)}function BY(e){return new $y(e)}function VY(e){return new Bp(e)}function UY(e){return new Fc(e)}function HY(e){return new Py(e)}function jY(e){return new Wp(e)}function GY(e){return new Ly(e)}function qY(e){return new Wy(e)}function XY(e){return new By(e)}function KY(e){return new Vy(e)}function ZY(e){return new Zy(e)}function JY(e){return new Xy(e)}function YY(e){return new Gp(e)}function QY(e){return new qy(e)}function eQ(e){return new Ky(e)}function tQ(e){return new Jy(e)}function nQ(e){return new Yy(e)}function rQ(e){return new Qy(e)}function aQ(e){return new tg(e)}function sQ(e){return new ng(e)}function iQ(e){return new ag(e)}function oQ(e){return new og(e)}function lQ(e){return new sg(e)}function uQ(e){return new ig(e)}function cQ(e){return new rg(e)}function hQ(e){return new lg(e)}function dQ(e){return new dg(e)}function pQ(e){return new pg(e)}function fQ(e){return new fg(e)}function uy(e){return new Ag(e)}function mQ(e){return uy(e)}function AQ(e){return uy(e)}function cy(e){return new gg(e)}function yQ(e){return cy(e)}function gQ(e){return cy(e)}function hy(e){return new wg(e)}function xQ(e){return hy(e)}function wQ(e){return hy(e)}function _Q(e){return new _g(e)}function bQ(e){return new vg(e)}function f3(e){return new bg(e)}function m3(e){return new kg(e)}function A3(e){return new mg(e)}function y3(e){return new yg(e)}function vQ(e){return new xg(e)}function kQ(e){return new Hy(e)}function IQ(e){return new Hp(e)}function NQ(e){return new jy(e)}function SQ(e){return new Mc(e)}function TQ(e){return new Uy(e)}function EQ(e){return new Up(e)}function CQ(e){return new Gy(e)}function RQ(e){return new jp(e)}function FQ(e){return new Fr(e)}function MQ(e){return new Vp(e)}function $Q(e){return new Ng(e)}function DQ(e){return new Ig(e)}var OQ=f3,zQ=m3,PQ=A3,LQ=y3;function WQ(e){return new ug(e)}function BQ(e){return new cg(e)}function VQ(e){return new hg(e)}function UQ(e){return new eg(e)}var z0={};ze(z0,{MAPE:()=>mte,MSE:()=>gte,binaryAccuracy:()=>ste,binaryCrossentropy:()=>ite,categoricalAccuracy:()=>lte,categoricalCrossentropy:()=>ute,cosineProximity:()=>dte,mape:()=>Ate,meanAbsoluteError:()=>pte,meanAbsolutePercentageError:()=>fte,meanSquaredError:()=>yte,mse:()=>xte,precision:()=>cte,recall:()=>hte,sparseCategoricalAccuracy:()=>ote});function ste(e,t){return yy(e,t)}function ite(e,t){return T3(e,t)}function ote(e,t){return E3(e,t)}function lte(e,t){return gy(e,t)}function ute(e,t){return xy(e,t)}function cte(e,t){return S3(e,t)}function hte(e,t){return lee(e,t)}function dte(e,t){return my(e,t)}function pte(e,t){return Fp(e,t)}function fte(e,t){return El(e,t)}function mte(e,t){return El(e,t)}function Ate(e,t){return El(e,t)}function yte(e,t){return mi(e,t)}function gte(e,t){return mi(e,t)}function xte(e,t){return mi(e,t)}var P0={};ze(P0,{modelFromJSON:()=>Vee});var L0={};ze(L0,{l1:()=>_te,l1l2:()=>wte,l2:()=>bte});function wte(e){return new Cc(e)}function _te(e){return Gee(e)}function bte(e){return qee(e)}var W0=class extends Tl{constructor(){super(...arguments);this.model=null}setModel(e){if(!(e instanceof ea))throw new Error("model must be a LayersModel, not some other Container");this.model=e}};function Xp(e,t){return e<t}function w7(e,t){return e>t}var B0=class extends W0{constructor(e){super();if(e==null&&(e={}),e.restoreBestWeights)throw new De("restoreBestWeights = True is not implemented in EarlyStopping yet.");this.monitor=e.monitor||"val_loss",this.minDelta=Math.abs(e.minDelta||0),this.patience=e.patience||0,this.verbose=e.verbose||0,this.mode=e.mode||"auto",this.baseline=e.baseline,["auto","min","max"].indexOf(this.mode)===-1&&(console.warn(`EarlyStopping mode '${this.mode}' is invalid. Falling back to mode 'auto'.`),this.mode="auto"),this.mode==="min"?this.monitorFunc=Xp:this.mode==="max"?this.monitorFunc=w7:this.monitor.indexOf("acc")!==-1?this.monitorFunc=w7:this.monitorFunc=Xp,this.monitorFunc===Xp&&(this.minDelta*=-1)}async onTrainBegin(e){this.wait=0,this.stoppedEpoch=0,this.baseline!=null?this.best=this.baseline:this.best=this.monitorFunc===Xp?Infinity:-Infinity}async onEpochEnd(e,t){await Oa(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 vte(e){return new B0(e)}var _8={earlyStopping:vte},vr;(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"})(vr||(vr={}));var _7;(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={}))})(_7||(_7={}));var Sg={};function b8(e,t){let n={tfOpName:e,category:"custom",inputs:[],attrs:[],customExecutor:t};Sg[e]=n}function b7(e){return Sg[e]}function v8(e){delete Sg[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 gn(t.inputNames[s.inputIndexStart],n,r,a);if(s.type==="tensors")return t.inputNames.slice(o,l).map(h=>gn(h,n,r,a));let c=gn(t.inputNames.slice(o)[0],n,r,a),u=c.dataSync();return s.type==="number"?u[0]:v.toNestedArray(c.shape,u)}let i=t.attrParams[e];return i&&i.value}function gn(e,t,n,r){let[a,s]=Mn(e);if(r!=null){let o=r.getHashTableHandleByName(a);if(o!=null)return o}let i=n.currentContextIds.find(o=>!!t[Kp(a,o)]);return i!==void 0?t[Kp(a,i)][s]:void 0}function kte(e,t,n){return t[Kp(e,n.currentContextId)]}function oa(e,t){let[n,r]=Mn(e);return[Kp(n,t&&t.currentContextId),r]}function Kp(e,t){return t?`${e}-${t}`:e}function Mn(e){let t=e.split(":");return t.length===1?[e,0]:[t[0],Number(t[t.length-1])]}function Zp(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 la(e){return e.kept?e:Nr(e)}var v7={};ze(v7,{json:()=>Ite});var Ite=[{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}]}],k7={};ze(k7,{json:()=>Nte});var Nte=[{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}]}],I7={};ze(I7,{json:()=>Ste});var Ste=[{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"}]}],N7={};ze(N7,{json:()=>Tte});var Tte=[{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"}]}],S7={};ze(S7,{json:()=>Ete});var Ete=[{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"}]}],T7={};ze(T7,{json:()=>Cte});var Cte=[{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}]}],E7={};ze(E7,{json:()=>Rte});var Rte=[{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"}]}],C7={};ze(C7,{json:()=>Fte});var Fte=[{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"}]}],R7={};ze(R7,{json:()=>Mte});var Mte=[{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}]}],F7={};ze(F7,{json:()=>$te});var $te=[{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"}]}],M7={};ze(M7,{json:()=>Dte});var Dte=[{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}]}],$7={};ze($7,{json:()=>Ote});var Ote=[{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}]}],D7={};ze(D7,{json:()=>zte});var zte=[{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}]}],O7={};ze(O7,{json:()=>Pte});var Pte=[{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"}]}],z7={};ze(z7,{json:()=>Lte});var Lte=[{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}]}],P7={};ze(P7,{json:()=>Wte});var Wte=[{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}]}],L7={};ze(L7,{json:()=>Bte});var Bte=[{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:[]}],B7=class{static get Instance(){return this._instance||(this._instance=new this)}constructor(){let e=[v7,k7,I7,N7,S7,T7,E7,M7,F7,C7,$7,D7,O7,z7,P7,L7,R7],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=[],c={},u={};t!=null&&(c=this.mapSignatureEntries(t.inputs),u=this.mapSignatureEntries(t.outputs));let h=Object.keys(i);h.forEach(f=>{let m=i[f];m.inputNames.forEach(A=>{let[y]=oa(A);m.inputs.push(i[y]),i[y].children.push(m)})}),Object.keys(u).length===0?h.forEach(f=>{let m=i[f];m.children.length===0&&l.push(m)}):Object.keys(u).forEach(f=>{let[m]=oa(f),A=i[m];A!=null&&(A.signatureKey=u[f],l.push(A))}),Object.keys(c).length>0?Object.keys(c).forEach(f=>{let[m]=oa(f),A=i[m];A&&(A.signatureKey=c[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=b7(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=Tg(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=Tg(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"string[]":i=Og(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=Og(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"number":i=Cg(e.attr,a.tfName,a.defaultValue||0),i===void 0&&!!a.tfDeprecatedName&&(i=Cg(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"number[]":i=Dg(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=Dg(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"bool":i=Eg(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=Eg(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"bool[]":i=Pg(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=Pg(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"shape[]":i=zg(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=zg(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"dtype":i=Fg(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=Fg(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"dtype[]":i=Mg(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=Mg(e.attr,a.tfDeprecatedName,a.defaultValue));break;case"func":i=W7(e.attr,a.tfName,a.defaultValue),i===void 0&&!!a.tfDeprecatedName&&(i=W7(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((c,u)=>(c[u.name]=this.mapNode(u),u.op==="Const"&&r.push(c[u.name]),c),{}));let s=[],i=[];e.signature.inputArg.forEach(c=>{let[u]=oa(c.name),h={name:u,op:"Placeholder",inputs:[],inputNames:[],category:"graph",inputParams:{},attrParams:{dtype:{value:Rg(c.type),type:"dtype"}},children:[]};h.signatureKey=c.name,s.push(h),a[u]=h}),Object.keys(a).forEach(c=>{let u=a[c];u.inputNames.forEach(h=>{let[d]=oa(h);u.inputs.push(a[d]),a[d].children.push(u)})});let o=e.ret;e.signature.outputArg.forEach(c=>{let[u,h]=oa(o[c.name]),d=a[u];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 Vte(e){let t=Q().global;if(typeof t.atob!="undefined")return t.atob(e);if(typeof Buffer!="undefined")return new Buffer(e,"base64").toString();throw new Error("Unable to decode base64 in this environment. Missing built-in atob() or Buffer()")}function V7(e,t){let n=Array.isArray(e)?String.fromCharCode.apply(null,e):Vte(e);return t?n:n.toLowerCase()}function Tg(e,t,n,r=!1){let a=e[t];return a!=null?V7(a.s,r):n}function Eg(e,t,n){let r=e[t];return r?r.b:n}function Cg(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 Rg(e){switch(typeof e=="string"&&(e=vr[e]),e){case vr.DT_FLOAT:return"float32";case vr.DT_INT32:case vr.DT_INT64:case vr.DT_INT8:case vr.DT_UINT8:return"int32";case vr.DT_BOOL:return"bool";case vr.DT_DOUBLE:return"float32";case vr.DT_STRING:return"string";default:return null}}function W7(e,t,n){let r=e[t];return r&&r.func?r.func.name:n}function Fg(e,t,n){let r=e[t];return r&&r.type?Rg(r.type):n}function Mg(e,t,n){let r=e[t];return r&&r.list&&r.list.type?r.list.type.map(a=>Rg(a)):n}function U7(e){if(!e.unknownRank)return e.dim!=null?e.dim.map(t=>typeof t.size=="number"?t.size:parseInt(t.size,10)):[]}function $g(e,t,n){let r=e[t];return r&&r.shape?U7(r.shape):n}function Dg(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 Og(e,t,n,r=!1){let a=e[t];return a&&a.list&&a.list.s?a.list.s.map(s=>V7(s,r)):n}function zg(e,t,n){let r=e[t];return r&&r.list&&r.list.shape?r.list.shape.map(a=>U7(a)):n}function Pg(e,t,n){let r=e[t];return r&&r.list&&r.list.b?r.list.b:n}var Ute=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 gn(e,this.tensorMap,this.context)}getAttr(e,t){let n=this.node.rawAttrs[e];if(n.tensor!=null)return gn(e,this.tensorMap,this.context);if(n.i!=null||n.f!=null)return Cg(this.node.rawAttrs,e,t);if(n.s!=null)return Tg(this.node.rawAttrs,e,t);if(n.b!=null)return Eg(this.node.rawAttrs,e,t);if(n.shape!=null)return $g(this.node.rawAttrs,e,t);if(n.type!=null)return Fg(this.node.rawAttrs,e,t);if(n.list!=null){if(n.list.i!=null||n.list.f!=null)return Dg(this.node.rawAttrs,e,t);if(n.list.s!=null)return Og(this.node.rawAttrs,e,t);if(n.list.shape!=null)return zg(this.node.rawAttrs,e,t);if(n.list.b!=null)return Pg(this.node.rawAttrs,e,t);if(n.list.type!=null)return Mg(this.node.rawAttrs,e,t)}return t}},Hte=(e,t,n)=>{switch(e.op){case"BiasAdd":case"AddV2":case"Add":return[oe(k("a",e,t,n),k("b",e,t,n))];case"AddN":return[Kh(k("tensors",e,t,n))];case"FloorMod":case"Mod":return[Qf(k("a",e,t,n),k("b",e,t,n))];case"Mul":return[W(k("a",e,t,n),k("b",e,t,n))];case"RealDiv":case"Div":return[Ne(k("a",e,t,n),k("b",e,t,n))];case"DivNoNan":return[jf(k("a",e,t,n),k("b",e,t,n))];case"FloorDiv":return[Xh(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[Xo(k("a",e,t,n),k("b",e,t,n))];case"Maximum":return[Tr(k("a",e,t,n),k("b",e,t,n))];case"Pow":return[Yr(k("a",e,t,n),k("b",e,t,n))];case"SquaredDifference":return[gd(k("a",e,t,n),k("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},jte=(e,t,n)=>{switch(e.op){case"Abs":case"ComplexAbs":return[$t(k("x",e,t,n))];case"Acos":return[Ff(k("x",e,t,n))];case"Acosh":return[Mf(k("x",e,t,n))];case"Asin":return[Df(k("x",e,t,n))];case"Asinh":return[Of(k("x",e,t,n))];case"Atan":return[zf(k("x",e,t,n))];case"Atan2":return[Pf(k("x",e,t,n),k("y",e,t,n))];case"Atanh":return[Lf(k("x",e,t,n))];case"Ceil":return[Bf(k("x",e,t,n))];case"Complex":return[ga(k("real",e,t,n),k("imag",e,t,n))];case"Cos":return[Ru(k("x",e,t,n))];case"Cosh":return[ed(k("x",e,t,n))];case"Elu":return[Ho(k("x",e,t,n))];case"Erf":return[Gf(k("x",e,t,n))];case"Exp":return[Wn(k("x",e,t,n))];case"Expm1":return[qf(k("x",e,t,n))];case"Floor":return[jo(k("x",e,t,n))];case"Log":return[kn(k("x",e,t,n))];case"Log1p":return[ad(k("x",e,t,n))];case"Imag":return[nd(k("x",e,t,n))];case"Neg":return[_t(k("x",e,t,n))];case"Reciprocal":return[em(k("x",e,t,n))];case"Real":return[Pu(k("x",e,t,n))];case"Relu":return[Cr(k("x",e,t,n))];case"Round":return[tm(k("x",e,t,n))];case"Selu":return[dd(k("x",e,t,n))];case"Sigmoid":return[er(k("x",e,t,n))];case"Sin":return[pd(k("x",e,t,n))];case"Sign":return[rm(k("x",e,t,n))];case"Sinh":return[fd(k("x",e,t,n))];case"Softplus":return[Go(k("x",e,t,n))];case"Sqrt":return[Xt(k("x",e,t,n))];case"Square":return[ot(k("x",e,t,n))];case"Tanh":return[Vo(k("x",e,t,n))];case"Tan":return[im(k("x",e,t,n))];case"ClipByValue":return[pn(k("x",e,t,n),k("clipValueMin",e,t,n),k("clipValueMax",e,t,n))];case"Relu6":return[cd(k("x",e,t,n))];case"Rsqrt":return[hd(gn(e.inputNames[0],t,n))];case"Prod":return[ld(k("x",e,t,n),k("axes",e,t,n))];case"LeakyRelu":return[Mu(k("x",e,t,n),k("alpha",e,t,n))];case"Prelu":return[zu(k("x",e,t,n),k("alpha",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function ur(e,t,n=""){v.assert(Gte(e,t),()=>n+` Shapes ${e} and ${t} must match`)}function Gte(e,t){if(e.length!==t.length)return!1;for(let n=0;n<e.length;n++)if(e[n]!==-1&&t[n]!==-1&&e[n]!==t[n])return!1;return!0}var qte=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=Se(0),Bt(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),ur(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,Bt(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 pr([],[0].concat(this.elementShape));let n=this.readMany(e);return ur(this.elementShape,n[0].shape,"TensorArray shape mismatch: "),Sn(n,0)}concat(e){if(!!e&&e!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but concat requested dtype ${e}`);if(this.size()===0)return pr([],[0].concat(this.elementShape));let t=[];for(let r=0;r<this.size();r++)t.push(r);let n=this.readMany(t);return ur(this.elementShape,n[0].shape,`TensorArray shape mismatch: tensor array shape (${this.elementShape}) vs first tensor shape (${n[0].shape})`),ct(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,rr(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=[];U(()=>{t=q(t,[1,n,a]);for(let o=0;o<e.length;++o){let l=o===0?0:r[o-1],c=[0,l,0],u=[1,e[o],a];s[o]=q(Me(t,c,u),this.elementShape)}return s});let i=[];for(let o=0;o<e.length;o++)i[o]=o;this.writeMany(i,s)}},Oc=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}`);ur(t,a.shape,"TensorList shape mismatch: "),Bt(a)}),this.idTensor=Se(0),this.maxNumElements=r,Bt(this.idTensor)}get id(){return this.idTensor.id}copy(){return new Oc([...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.`);return ur(e,this.elementShape,"TensorList shape mismatch: "),U(()=>{let r=this.tensors.map(a=>q(a,e));return Sn(r,0)})}popBack(e,t){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(this.size()===0)throw new Error("Trying to pop from an empty list.");let n=this.tensors.pop();return ur(n.shape,e,"TensorList shape mismatch: "),q(n,e)}pushBack(e){if(e.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${this.elementDtype}`);if(ur(e.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");Bt(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.`);return ur(this.tensors[e].shape,t,"TensorList shape mismatch: "),this.tensors[e]}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.`);ur(this.elementShape,t.shape,"TensorList shape mismatch: "),Bt(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}`);return ur(this.elementShape,n,"TensorList shape mismatch: "),e=e.slice(0,this.size()),e.length===0?pr([],[0].concat(this.elementShape)):U(()=>{let r=e.map(a=>q(this.tensors[a],n));return Sn(r,0)})}concat(e,t){if(!!e&&e!==this.elementDtype)throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${e}`);return ur(this.elementShape,t,"TensorList shape mismatch: "),this.size()===0?pr([],[0].concat(this.elementShape)):U(()=>{let n=this.tensors.map(r=>q(r,t));return ct(n,0)})}};function Xte(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);ur(a,t,"TensorList shape mismatch: ");let s=rr(e);return new Oc(s,t,r)}function Kte(e,t,n){return new Oc([],e,t,n)}function Zte(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 Oc([],n,e.dtype,r),i=rr(e,0);return t.forEach((o,l)=>{s.setItem(o,i[l])}),s}function Jte(e,t,n){let r=0,a=t.map(l=>(r+=l,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=r===0?0:e.size/r,i=U(()=>{let l=[];e=q(e,[1,r,s]);for(let c=0;c<t.length;++c){let u=c===0?0:a[c-1],h=[0,u,0],d=[1,t[c],s];l[c]=q(Me(e,h,d),n)}return e.dispose(),l}),o=new Oc([],n,e.dtype,t.length);for(let l=0;l<i.length;l++)o.setItem(l,i[l]);return o}var Yte=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(u=>u.id),l=await i[0].data();i.forEach(u=>{!u.kept&&o.indexOf(u.id)===-1&&u.dispose()});let c=s;for(;l[0];){let u=c;c=await n.functionMap[r].executeFunctionAsync(c,n.tensorArrayMap,n.tensorListMap);let h=c.map(p=>p.id);u.forEach(p=>{!p.kept&&o.indexOf(p.id)===-1&&h.indexOf(p.id)===-1&&p.dispose()});let d=await n.functionMap[a].executeFunctionAsync(c,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 c}case"LoopCond":{let r=k("pred",e,t,n);return[la(r)]}case"Switch":{let r=k("pred",e,t,n),a=k("data",e,t,n);return a.kept||(a=la(a)),(await r.data())[0]?[void 0,a]:[a,void 0]}case"Merge":{let r=e.inputNames.find(a=>gn(a,t,n)!==void 0);if(r){let a=gn(r,t,n);return[la(a)]}return}case"Enter":{let r=k("frameName",e,t,n),a=k("tensor",e,t,n);return n.enterFrame(r),[la(a)]}case"Exit":{let r=k("tensor",e,t,n);return n.exitFrame(),[la(r)]}case"NextIteration":{let r=k("tensor",e,t,n);return n.nextIteration(),[la(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),c=k("name",e,t,n),u=new qte(c,a,r,s,l,i,o);return n.addTensorArray(u),[u.idTensor,Se(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[Se(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=Zte(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=Kte(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=Xte(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=Jte(r,s,a);return n.addTensorList(i),[i.idTensor]}default:throw TypeError(`Node type ${e.op} is not implemented`)}};function H7(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 c=k("strides",e,t,n),u=Zp(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:c,pad:u,dataFormat:h,dilations:d,biasArg:p,preluArg:f,activationFunc:a,leakyreluAlpha:m}}var Qte=(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[Yh(k("x",e,t,n),k("filter",e,t,n),r,a,s,i)]}case"Conv2D":{let r=k("strides",e,t,n),a=Zp(e,t,n),s=k("dataFormat",e,t,n).toUpperCase(),i=k("dilations",e,t,n);return[Zr(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:c,leakyreluAlpha:u}=H7(e,t,n);return[va.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:c,preluActivationWeights:l,leakyreluAlpha:u})]}case"FusedDepthwiseConv2dNative":{let{stride:r,pad:a,dataFormat:s,dilations:i,biasArg:o,preluArg:l,activationFunc:c,leakyreluAlpha:u}=H7(e,t,n);return[va.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:c,preluActivationWeights:l,leakyreluAlpha:u})]}case"Conv2DBackpropInput":case"Conv2dTranspose":{let r=k("outputShape",e,t,n),a=k("strides",e,t,n),s=Zp(e,t,n);return[Qh(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=Zp(e,t,n),s=k("dilations",e,t,n),i=k("dataFormat",e,t,n).toUpperCase();return[Uo(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[Vf(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[Tu(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[Du(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}=u0(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[Wf(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[Jf(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],c=s[2];return[Hf(k("x",e,t,n),k("filter",e,t,n),[i,o],a,[l,c],"NHWC")]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},ene=(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[Fu(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[s0(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[c0(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[Wo(r,a,s,i)]}case"Ones":return[Er(k("shape",e,t,n),k("dtype",e,t,n))];case"OnesLike":return[In(k("x",e,t,n))];case"RandomUniform":return[Ko(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[ud(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[Ct(k("shape",e,t,n),k("dtype",e,t,n))];case"ZerosLike":return[He(k("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function Lg(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 tne=async(e,t,n)=>{switch(e.op){case"NonMaxSuppressionV5":{let{boxes:r,scores:a,maxOutputSize:s,iouThreshold:i,scoreThreshold:o,softNmsSigma:l}=Lg(e,t,n),c=await St.nonMaxSuppressionWithScoreAsync(r,a,s,i,o,l);return[c.selectedIndices,c.selectedScores]}case"NonMaxSuppressionV4":{let{boxes:r,scores:a,maxOutputSize:s,iouThreshold:i,scoreThreshold:o}=Lg(e,t,n),l=k("padToMaxOutputSize",e,t,n),c=await St.nonMaxSuppressionPaddedAsync(r,a,s,i,o,l);return[c.selectedIndices,c.validOutputs]}case"NonMaxSuppressionV3":case"NonMaxSuppressionV2":{let{boxes:r,scores:a,maxOutputSize:s,iouThreshold:i,scoreThreshold:o}=Lg(e,t,n);return[await St.nonMaxSuppressionAsync(r,a,s,i,o)]}case"Where":{let r=ye(k("condition",e,t,n),"bool"),a=[await um(r)];return r.dispose(),a}case"ListDiff":return p0(k("x",e,t,n),k("y",e,t,n));default:throw TypeError(`Node type ${e.op} is not implemented`)}},nne=(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=om(r,a,s);return[i.values,i.indices]}case"Unique":{let r=k("x",e,t,n),a=wd(r);return[a.values,a.indices]}case"UniqueV2":{let r=k("x",e,t,n),a=k("axis",e,t,n),s=wd(r,a);return[s.values,s.indices]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},rne=(e,t,n)=>{switch(e.op){case"Const":return t[e.name];case"PlaceholderWithDefault":let r=k("default",e,t,n);return[gn(e.name,t,n)||r];case"Placeholder":return[gn(e.name,t,n)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":{let c=k("x",e,t,n);return[la(c)]}case"IdentityN":return k("x",e,t,n).map(c=>la(c));case"Snapshot":let a=k("x",e,t,n);return[la(a)];case"Shape":return[Qt(k("x",e,t,n).shape,"int32")];case"ShapeN":return k("x",e,t,n).map(c=>Qt(c.shape));case"Size":return[Se(k("x",e,t,n).size,"int32")];case"Rank":return[Se(k("x",e,t,n).rank,"int32")];case"NoOp":return[Se(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 c=0;c<i.length;c++)console.log(Array.prototype.slice.call(i[c].dataSync()).slice(0,l));return[s];default:throw TypeError(`Node type ${e.op} is not implemented`)}},ane=class{constructor(e,t){this.keyDType=e,this.valueDType=t,this.handle=Se(0),this.tensorMap=new Map,Bt(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}async import(e,t){this.checkKeyAndValueTensor(e,t);let n=await e.data();return this.tensorMap.forEach(r=>r.dispose()),this.tensorMap.clear(),U(()=>{let r=rr(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];Bt(l),this.tensorMap.set(o,l)}return this.handle})}async find(e,t){this.checkKeyAndValueTensor(e,t);let n=await e.data();return U(()=>{let r=[];for(let a=0;a<n.length;a++){let s=n[a],i=this.findWithDefault(s,t);r.push(i)}return Sn(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}`)}},sne=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 ane(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)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},ine=(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[St.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[St.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[St.cropAndResize(r,a,s,i,o,l)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},one=(e,t,n)=>{switch(e.op){case"Equal":return[xa(k("a",e,t,n),k("b",e,t,n))];case"NotEqual":return[js(k("a",e,t,n),k("b",e,t,n))];case"Greater":return[tr(k("a",e,t,n),k("b",e,t,n))];case"GreaterEqual":return[_a(k("a",e,t,n),k("b",e,t,n))];case"Less":return[rd(k("a",e,t,n),k("b",e,t,n))];case"LessEqual":return[Hs(k("a",e,t,n),k("b",e,t,n))];case"LogicalAnd":return[nr(k("a",e,t,n),k("b",e,t,n))];case"LogicalNot":return[$u(k("a",e,t,n))];case"LogicalOr":return[id(k("a",e,t,n),k("b",e,t,n))];case"Select":case"SelectV2":return[fn(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`)}},lne=(e,t,n)=>{switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[qe(k("a",e,t,n),k("b",e,t,n),k("transposeA",e,t,n),k("transposeB",e,t,n))];case"Transpose":return[at(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[c,u]=k("args",e,t,n);return[va.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:c,activation:a,preluActivationWeights:u,leakyreluAlpha:l})];default:throw TypeError(`Node type ${e.op} is not implemented`)}},une=(e,t,n)=>{switch(e.op){case"FusedBatchNorm":case"FusedBatchNormV2":return[Vs(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[Vs(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[Kf(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[Wu(k("x",e,t,n))];case"LogSoftmax":return[sd(k("x",e,t,n))];case"SparseToDense":return[cm(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 ${e.op} is not implemented`)}},cne=(e,t,n)=>{switch(e.op){case"Max":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[Bn(k("x",e,t,n),i,o)]}case"Mean":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[bt(k("x",e,t,n),i,o)]}case"Min":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[qo(k("x",e,t,n),i,o)]}case"Sum":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[Te(k("x",e,t,n),i,o)]}case"All":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[Zh(k("x",e,t,n),i,o)]}case"Any":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[Nu(k("x",e,t,n),i,o)]}case"ArgMax":{let i=k("axis",e,t,n);return[Su(k("x",e,t,n),i)]}case"ArgMin":{let i=k("axis",e,t,n);return[$f(k("x",e,t,n),i)]}case"Prod":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[ld(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[td(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[Z2(r,a,s)];case"DenseBincount":{let i=k("x",e,t,n),o=k("weights",e,t,n),l=k("size",e,t,n),c=k("binaryOutput",e,t,n);return[e0(i,o,l,c)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},hne=(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),[ct(s,a)]}case"Gather":{let r=k("x",e,t,n),a=k("indices",e,t,n);return[Us(r,ye(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[Us(s,ye(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[Nn(s,a)]}case"ReverseV2":{let r=k("axis",e,t,n),a=k("x",e,t,n);return[Nn(a,r)]}case"Slice":{let r=k("begin",e,t,n),a=k("size",e,t,n);return[Me(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),c=k("newAxisMask",e,t,n),u=k("shrinkAxisMask",e,t,n),h=k("x",e,t,n);return[sm(h,r,a,s,i,o,l,c,u)]}case"Pack":return U(()=>{let r=k("axis",e,t,n),a=k("tensors",e,t,n),s=a[0].shape,i=ba(a[0]).shape,o=a.map(l=>{let c=v.arraysEqual(l.shape,s);if(!c&&!v.arraysEqual(ba(l).shape,i))throw new Error("the input tensors shape does not match");return c?l:q(l,s)});return[Sn(o,r)]});case"Unpack":{let r=k("axis",e,t,n),a=k("tensor",e,t,n);return rr(a,r)}case"Tile":{let r=k("reps",e,t,n);return[wa(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 an(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[m0(r,a,s)]}case"GatherNd":{let r=k("x",e,t,n),a=k("indices",e,t,n);return[A0(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[cm(r,s,a,s.dtype===i.dtype?i:ye(i,s.dtype))]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},dne=(e,t,n)=>{switch(e.op){case"FFT":return[Bu(k("x",e,t,n))];case"IFFT":return[Zo(k("x",e,t,n))];case"RFFT":return[Vu(k("x",e,t,n))];case"IRFFT":return[yd(k("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},pne=(e,t,n)=>{switch(e.op){case"Cast":return[ye(k("x",e,t,n),k("dtype",e,t,n))];case"ExpandDims":{let r=k("axis",e,t,n);return[vn(k("x",e,t,n),r)]}case"Squeeze":{let r=k("axis",e,t,n);return[ba(k("x",e,t,n),r)]}case"Reshape":return[q(k("x",e,t,n),k("shape",e,t,n))];case"MirrorPad":return[Yf(k("x",e,t,n),k("padding",e,t,n),k("mode",e,t,n))];case"PadV2":case"Pad":return[Jr(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[Ou(k("x",e,t,n),r,a)]}case"BatchToSpaceND":{let r=k("blockShape",e,t,n),a=k("crops",e,t,n);return[Eu(k("x",e,t,n),r,a)]}case"DepthToSpace":{let r=k("blockSize",e,t,n),a=k("dataFormat",e,t,n).toUpperCase();return[Uf(k("x",e,t,n),r,a)]}case"BroadcastTo":return[Cu(k("x",e,t,n),k("shape",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function j7(e,t,n,r){let a=((s,i,o)=>{switch(s.category){case"arithmetic":return U(()=>Hte(s,i,o));case"basic_math":return U(()=>jte(s,i,o));case"control":return Yte(s,i,o);case"convolution":return U(()=>Qte(s,i,o));case"creation":return U(()=>ene(s,i,o));case"dynamic":return tne(s,i,o);case"evaluation":return U(()=>nne(s,i,o));case"image":return U(()=>ine(s,i,o));case"graph":return U(()=>rne(s,i,o));case"logical":return U(()=>one(s,i,o));case"matrices":return U(()=>lne(s,i,o));case"normalization":return U(()=>une(s,i,o));case"reduction":return U(()=>cne(s,i,o));case"slice_join":return U(()=>hne(s,i,o));case"spectral":return U(()=>dne(s,i,o));case"transformation":return U(()=>pne(s,i,o));case"hash_table":return sne(s,i,o,r);case"custom":let l=b7(s.op);if(l&&l.customExecutor)return l.customExecutor(new Ute(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 G7=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 X7(e,t,n,r){let a=new Set,s=[],i=null,o=null,l=new Set,c=Object.keys(e).map(d=>Mn(d)[0]),u=[];r!=null&&(u=r.map(d=>Mn(d.name)[0]));let h=[...t];for(;h.length>0;){let d=h.pop();if((q7(d)||fne(d)||mne(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&&c.indexOf(d.name)===-1&&u.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 Ane(e,t,n){let{usedNodes:r,inputs:a}=n,s=[],i=Object.keys(a).map(u=>Mn(u)[0]).map(u=>e.nodes[u]),o=e.initNodes;i.forEach(u=>{r.has(u.name)&&s.push(u)}),e.weights.forEach(u=>{r.has(u.name)&&s.push(u)}),o!=null&&o.forEach(u=>{r.has(u.name)&&s.push(u)});let l=new Set,c=[];for(;s.length>0;){let u=s.pop();l.add(u.name),t[u.name]||c.push(u),u.children.forEach(h=>{!l.has(h.name)&&r.has(h.name)&&h.inputs.every(d=>l.has(d.name))&&s.push(h)})}return c}var yne=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],gne=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],xne=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2"];function q7(e){return yne.indexOf(e.op)>=0}function fne(e){return gne.indexOf(e.op)>=0}function mne(e){return xne.indexOf(e.op)>=0}var Wg=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 Wg(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=X7(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 Ane(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(u=>this.graph.nodes[Mn(u)[0]]),a=t.map(u=>Mn(u)[0]),s=a.map(u=>this.graph.nodes[u]);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={},c={};return U(()=>{let u=new G7(this.weightMap,l,c,this.functionExecutorMap),h=Object.assign({},this.weightMap);Object.keys(e).forEach(f=>{let[m,A]=Mn(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=j7(m,h,u,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,u,d,a,p)}}return this.parent==null&&u.dispose(d),t.map(f=>gn(f,h,u))})}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=kte(o.name,n,r);l!=null&&l.forEach(c=>{if(c&&!a.has(c.id)){let u=i[c.id];u===1?(c.dispose(),delete i[c.id]):u!=null&&i[c.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 G7(this.weightMap,r,a,this.functionExecutorMap),i=await this.executeWithControlFlow(e,s,t,n),o=t.map(h=>gn(h,i,s)),l=o.map(h=>h.id),c=Object.keys(e).map(h=>e[h].id),u=new Set([...l,...c,...this.weightIds]);return Object.keys(i).forEach(h=>{i[h].forEach(d=>{d&&!d.isDisposed&&!u.has(d.id)&&d.dispose()})}),this.parent==null&&s.dispose(u),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[Mn(g)[0]]),i=n.map(g=>Mn(g)[0]),o=i.map(g=>this.graph.nodes[g]);o.length===0&&(o=this._outputs);let{usedNodes:l,missingInputs:c,dynamicNode:u,syncInputs:h}=X7(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[w,x]=Mn(g),_=[];_[x]=e[g],p[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)}u==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=>!q7(g)&&!gn(g.name,p,t)).map(g=>g.name);if(y.length>0){let g="";throw u!=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: [${c}]. ${g}`)}return p}processStack(e,t,n,r,a,s,i,o,l){let c=[];for(;t.length>0;){let u=t.pop();n.currentContext=u.contexts;let h="";if(u.node.op==="Enter"&&k("isConstant",u.node,r,n)&&([h]=oa(u.node.name,n)),r[u.node.name]==null){let d=j7(u.node,r,n,this._resourceManager);h||([h]=oa(u.node.name,n));let p=n.currentContext;v.isPromise(d)?c.push(d.then(f=>(r[h]=f,n.currentContext=p,this.checkTensorForDisposal(h,u.node,r,n,s,i,o),this.processChildNodes(u.node,t,n,r,a,l),f))):(r[h]=d,this.checkTensorForDisposal(h,u.node,r,n,s,i,o),this.processChildNodes(u.node,t,n,r,a,l))}else this.processChildNodes(u.node,t,n,r,a,l)}return c}processChildNodes(e,t,n,r,a,s){e.children.forEach(i=>{let[o]=oa(i.name,n);a[o]||!s.has(i.name)||(i.op==="Merge"?i.inputNames.some(l=>!!gn(l,r,n))&&(a[o]=!0,t.push({contexts:n.currentContext,node:i})):i.inputNames.every(l=>!!gn(l,r,n))&&(a[o]=!0,t.push({contexts:n.currentContext,node:i})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let n=e[t],[r]=Mn(t),a=this.graph.nodes[r];if(a.attrParams.shape&&a.attrParams.shape.value){let s=a.attrParams.shape.value,i=s.length===n.shape.length&&n.shape.every((o,l)=>s[l]===-1||s[l]===o);v.assert(i,()=>`The shape of dict['${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 ${n.dtype}`)})}mapInputs(e){let t={};for(let n in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let r=this._signature.inputs[n];t[r.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[r]=Mn(n);return this.graph.nodes[r]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${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]=Mn(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}},wne=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},_ne="?tfjs-format=file",bne="model.json",V0=class{constructor(e,t={}){this.modelUrl=e,this.loadOptions=t,this.version="n/a",t==null&&(this.loadOptions={}),this.resourceManager=new wne}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=dn.browserHTTPRequest(e,this.loadOptions);else{let t=dn.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(dn.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${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}.${t.versions.minConsumer}`;let r=dn.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new Wg(B7.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let a=B7.Instance.transformGraph(e.modelInitializer);this.initializer=new Wg(a),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=dn.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${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 Qe)&&!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 ${e.length} input tensors.`);return this.inputNodes.reduce((t,n,r)=>(t[n]=e[r],t),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,n)=>(t[n]=[e[n]],t),{})}dispose(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}};async function Yn(e,t={}){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");t==null&&(t={}),t.fromTFHub&&e.load==null&&(e.endsWith("/")||(e=e+"/"),e=`${e}${bne}${_ne}`);let n=new V0(e,t);return await n.load(),n}var k8="3.0.0",U0={};ze(U0,{CSVDataset:()=>Z7,Dataset:()=>Rl,FileDataSource:()=>J7,TextLineDataset:()=>K7,URLDataSource:()=>Y7,array:()=>vne,csv:()=>Ine,func:()=>Nne,generator:()=>Sne,microphone:()=>Ene,version_data:()=>Cne,webcam:()=>Tne,zip:()=>kne});var Rne=Qo(H0()),Fne=Qo(H0());function Mne(e,t){return Jp(e,t)}function Jp(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(Fl(e)){let s=Array.isArray(e)?[]:{};r.add(e);for(let i in e){let o=e[i],l=Jp(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 $ne(e,t=e6){return Q7(e,t)}function Q7(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(Fl(r)){let s=Array.isArray(r)?[]:{};n.add(r);for(let i in r){let o=e.map(c=>c[i]),l=Q7(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 e6(e){return e===null?null:Fl(e[0])?{value:null,recurse:!0}:{value:e,recurse:!1}}async function t6(e,t){let n=new Map;Jp(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 Jp(e,t,n)}function Fl(e){return e!=null&&!ArrayBuffer.isView(e)&&(Array.isArray(e)||typeof e=="object"&&!(e instanceof Qe))}function One(e){return e==null||Dne(e)||Array.isArray(e)||typeof e=="object"&&e instanceof Qe||v.isTypedArray(e)}function Dne(e){return e===null||typeof e!="object"&&typeof e!="function"}function Pne(e){return Mne(e,zne)}function zne(e){return e instanceof Qe?{value:e.clone(),recurse:!1}:Fl(e)?{value:null,recurse:!0}:{value:e,recurse:!1}}var n6=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}},Bg=class extends n6{constructor(){super(Bg.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}};Bg.INITIAL_CAPACITY=32;function r6(e){return new Lne(e)}function Vg(e){return new Wne(e)}function Bne(e,t){return new a6(e,t)}function Une(e,t=Wa.FAIL){return new Vne(e,t)}var Gt=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 Zne(this,e)}filter(e){return new Xne(this,e)}map(e){return new Kne(this,e)}mapAsync(e){return new s6(this,e)}serialMapAsync(e){return new s6(this,e).serial()}flatmap(e){return new Jne(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 qne(this,e,t)}columnMajorBatch(e,t=!0,n=e6){return this.rowMajorBatch(e,t).map(r=>$ne(r,n))}concatenate(e,t){return new a6(r6([this,e]),t)}take(e){return e<0||e==null?this:new Gne(this,e)}skip(e){return e<0||e==null?this:new jne(this,e)}prefetch(e){return new i6(this,e)}shuffle(e,t){return new Yne(this,e,t)}serial(){return new Hne(this)}},Lne=class extends Gt{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:Pne(e),done:!1}}},Wne=class extends Gt{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: ${e.message}`,e}}},Hne=class extends Gt{constructor(e){super();this.upstream=e,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Serial`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){return this.upstream.next()}},jne=class extends Gt{constructor(e,t){super();this.upstream=e,this.maxCount=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Skip`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.count++<this.maxCount;){let e=await this.upstream.next();if(e.done)return e;Ce(e.value)}return this.upstream.next()}},Gne=class extends Gt{constructor(e,t){super();this.upstream=e,this.maxCount=t,this.count=0}summary(){return`${this.upstream.summary()} -> Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},qne=class extends Gt{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`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length<this.batchSize;){let t=await this.upstream.next();if(t.done)return this.enableSmallLastBatch&&e.length>0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},Xne=class extends Gt{constructor(e,t){super();this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${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;Ce(e.value)}}},Kne=class extends Gt{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=dr.getTensorsInContainer(e.value),n=this.transform(e.value),r=dr.getTensorsInContainer(n);for(let a of t)dr.isTensorInList(a,r)||a.dispose();return{value:n,done:!1}}},Zne=class extends Gt{constructor(e,t){super();this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${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}}}},s6=class extends Gt{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=dr.getTensorsInContainer(e.value),n=await this.transform(e.value),r=dr.getTensorsInContainer(n);for(let a of t)dr.isTensorInList(a,r)||a.dispose();return{value:n,done:!1}}},Ug=class extends Gt{constructor(){super();this.outputQueue=new Bg,this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.outputQueue.length()===0;)if(!await this.pump())return{value:null,done:!0};return{value:this.outputQueue.shift(),done:!1}}},Jne=class extends Ug{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){let e=await this.upstream.next();if(e.done)return!1;let t=dr.getTensorsInContainer(e.value),n=this.transform(e.value),r=dr.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let a of t)dr.isTensorInList(a,r)||a.dispose();return!0}},a6=class extends Gt{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}},Wa;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(Wa||(Wa={}));var Vne=class extends Gt{constructor(e,t=Wa.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 Gt?{value:s.next().then(i=>(t++,i.done&&n++,i.value)),recurse:!1}:{value:null,recurse:!0}}let a=await t6(this.iterators,r);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case Wa.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case Wa.SHORTEST:return{value:null,done:!0};case Wa.LONGEST:default:}return this.count++,{value:a,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},i6=class extends Gt{constructor(e,t){super();this.upstream=e,this.bufferSize=t,this.buffer=new n6(t)}summary(){return`${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()}},Yne=class extends i6{constructor(e,t,n){super(e,t);this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=Fne.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}}},Rl=class{constructor(){this.size=null}batch(e,t=!0){let n=this;v.assert(e>0,()=>`batchSize needs to be positive, but it is
${e}`);let r;return this.size===Infinity||this.size==null?r=this.size:t?r=Math.ceil(this.size/e):r=Math.floor(this.size/e),$n(async()=>(await n.iterator()).columnMajorBatch(e,t,Qne),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,$n(async()=>(await t.iterator()).concatenate(await e.iterator()),n)}filter(e){let t=this,n;return this.size===Infinity?n=Infinity:n=null,$n(async()=>(await t.iterator()).filter(r=>U(()=>e(r))),n)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return $n(async()=>(await t.iterator()).map(n=>U(()=>e(n))),this.size)}mapAsync(e){let t=this;return $n(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 $n(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,n;return this.size!=null&&e>0?n=this.size*e:e===0?n=0:this.size!=null&&(e===void 0||e<0)?n=Infinity:n=null,$n(async()=>{let r=Vg(async()=>({value:await t.iterator(),done:!1}));return Bne(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,$n(async()=>(await t.iterator()).skip(e),n)}shuffle(e,t,n=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified. If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let r=this,a=Rne.alea(t||v.now().toString());return $n(async()=>{let s=a.int32();return n&&(s+=a.int32()),(await r.iterator()).shuffle(e,s.toString())},this.size)}take(e){let t=this,n;return this.size!=null&&this.size>e?n=e:this.size!=null&&this.size<=e?n=this.size:n=null,$n(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()}};Rl.MAX_BUFFER_SIZE=1e4;function $n(e,t=null){return new class extends Rl{constructor(){super(...arguments);this.size=t}async iterator(){return e()}}}function vne(e){return $n(async()=>r6(e),e.length)}function kne(e){if(!Fl(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 $n(async()=>{let n=await t6(e,r=>{if(r instanceof Rl)return{value:r.iterator(),recurse:!1};if(Fl(r))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return Une(n,Wa.SHORTEST)},t)}function Qne(e){if(e===null)return null;let t=e[0];return One(t)?{value:ere(e),recurse:!1}:{value:null,recurse:!0}}function ere(e){if(e.length===0)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof Qe?Sn(e):pr(e)}var K7=class extends Rl{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))}},Yp='"',zc=Symbol("out"),o6=Symbol("field"),Qp=Symbol("quote"),Hg=Symbol("quoteafterquote"),l6=Symbol("quoteinquote"),Z7=class extends Rl{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 K7(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 c=Number(o);if(isNaN(c))i&&i.dtype==="bool"?l=this.getBoolean(o):l=o;else if(!i||!i.dtype)l=c;else switch(i.dtype){case"float32":l=c;break;case"int32":l=Math.floor(c);break;case"bool":l=this.getBoolean(o);break;default:l=c}}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=zc;for(let i=0;i<a;i++)switch(s){case zc:switch(e.charAt(i)){case Yp:r=i+1,s=Qp;break;case this.delimiter:if(r=i+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),s=zc;break;default:s=o6,r=i;break}break;case o6:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(r,i)),s=zc,r=i+1;break;default:}break;case Qp:switch(e.charAt(i)){case Yp:s=Hg;break;default:}break;case Hg:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(r,i-1)),s=zc,r=i+1;break;case Yp:s=Qp;break;default:s=l6;break}break;case l6:switch(e.charAt(i)){case Yp:s=Qp;break;default:}break;default:}if(s===Hg?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}},u6=class extends Gt{constructor(e){super();this.microphoneConfig=e,this.isClosed=!1,this.fftSize=e.fftSize||1024;let t=Math.log2(this.fftSize);if(this.fftSize<0||t<4||t>14||!Number.isInteger(t))throw new Error(`Invalid fftSize: it must be a power of 2 between 2 to 4 and 2 to 14, but got ${this.fftSize}`);if(this.numFrames=e.numFramesPerSpectrogram||43,this.sampleRateHz=e.sampleRateHz,this.columnTruncateLength=e.columnTruncateLength||this.fftSize,this.audioTrackConstraints=e.audioTrackConstraints,this.smoothingTimeConstant=e.smoothingTimeConstant||0,this.includeSpectrogram=e.includeSpectrogram!==!1,this.includeWaveform=e.includeWaveform===!0,!this.includeSpectrogram&&!this.includeWaveform)throw new Error("Both includeSpectrogram and includeWaveform are false. At least one type of data should be returned.")}summary(){return"microphone"}static async create(e={}){if(Q().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new u6(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),pr(n,t)}},c6=class extends Gt{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=Qt([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=fr([s,a,o,i],[1,4])}else this.cropBox=fr([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(Q().get("IS_NODE"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new c6(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=ku.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: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return U(()=>{let t=vn(ye(e,"float32"),0),n;n=St.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let r=n.shape;return q(n,r.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(e=>e.stop());try{this.webcamVideoElement.srcObject=null}catch(e){console.log(e),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},h6=class{},d6=class extends Gt{split(e){return new tre(this,e)}},tre=class extends d6{constructor(e,t){super();this.upstream=e,this.impl=new nre(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},nre=class extends Ug{constructor(e,t){super();this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let n of t.slice(0,-1))this.outputQueue.push(n);return this.carryover=t[t.length-1],!0}},are=class extends Gt{decodeUTF8(){return new rre(this)}},rre=class extends d6{constructor(e){super();this.upstream=e,this.impl=new sre(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},sre=class extends Ug{constructor(e){super();if(this.upstream=e,Q().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=ok();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let n;return Q().get("IS_BROWSER")?n=this.decoder.decode(t,{stream:!0}):n=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(n),!0}},p6=class extends are{constructor(e,t={}){super();this.file=e,this.options=t,v.assert(e instanceof Uint8Array||(Q().get("IS_BROWSER")?e instanceof File||e instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=t.offset||0,this.chunkSize=t.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((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 ore(e,t={}){let n,r;typeof e=="string"?n=e:(n=e.url,r=ire(e));let a=await v.fetch(n,r);if(a.ok){let s=new Uint8Array(await a.arrayBuffer());return new p6(s,t)}else throw new Error(a.statusText)}var ire=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 f6(e){return typeof e=="string"&&e.substr(0,7)==="file://"}var J7=class extends h6{constructor(e,t={}){super();this.input=e,this.options=t}async iterator(){if(f6(this.input)&&Q().get("IS_NODE")){let e=require("fs");this.input=e.readFileSync(this.input.substr(7))}return new p6(this.input,this.options)}},Y7=class extends h6{constructor(e,t={}){super();this.url=e,this.fileOptions=t}async iterator(){return f6(this.url)?new J7(this.url,this.fileOptions).iterator():ore(this.url,this.fileOptions)}};function Ine(e,t={}){return new Z7(new Y7(e),t)}function Nne(e){let t=Vg(e);return $n(async()=>t)}function Sne(e){return $n(async()=>{let t=await e();return Vg(()=>t.next())})}async function Tne(e,t){return c6.create(e,t)}async function Ene(e){return u6.create(e)}var Cne="3.0.0",I8={tfjs:lk,"tfjs-core":uk,"tfjs-data":ck,"tfjs-layers":hk,"tfjs-converter":dk,"tfjs-backend-cpu":_0,"tfjs-backend-webgl":k0,"tfjs-backend-wasm":T0},cn={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 lre(){if(!G2(cn.name)){Ue("backend registration:",cn.name);try{cn.canvas=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(cn.width,cn.height):document.createElement("canvas")}catch(e){Ue("error: cannot create canvas:",e);return}try{cn.gl=cn.canvas.getContext("webgl2",cn.webGLattr)}catch(e){Ue("error: cannot get WebGL2 context:",e);return}try{pm(2,cn.gl)}catch(e){Ue("error: cannot set WebGL2 context:",e);return}try{let e=new fm(cn.gl);Iu(cn.name,()=>new mm(e),cn.priority)}catch(e){Ue("error: cannot register WebGL backend:",e);return}try{bu("webgl").forEach(e=>{let t={...e,backendName:cn.name};Lo(t)})}catch(e){Ue("error: cannot update WebGL backend registration:",e);return}try{bn.set("WEBGL_VERSION",2),bn.set("WEBGL_MAX_TEXTURE_SIZE",cn.gl.getParameter(cn.gl.MAX_TEXTURE_SIZE)),bn.set("WEBGL_FORCE_F16_TEXTURES",!0),bn.set("WEBGL_PACK_DEPTHWISECONV",!0)}catch(e){Ue("error: cannot set WebGL backend flags:",e);return}Ue("backend registered:",cn.name)}}var m6=6;function ure(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 c=a*(l+.5);for(let u=0;u<i;u++){let h=a*(u+.5);for(let d=0;d<o;d++)n.push([h,c])}}}return n}var cre=e=>({startEndTensor:e,startPoint:Me(e,[0,0],[-1,2]),endPoint:Me(e,[0,2],[-1,2])});function hre(e,t,n){let r=Me(e,[0,1],[-1,2]),a=oe(r,t),s=Me(e,[0,3],[-1,2]),i=Ne(s,n),o=Ne(a,n),l=Ne(i,2),c=we(o,l),u=oe(o,l),h=W(c,n),d=W(u,n);return Jh([h,d],1)}var dre=class{constructor(e,t){this.blazeFaceModel=e,this.width=t.face.detector.inputSize,this.height=t.face.detector.inputSize,this.anchorsData=ure(t.face.detector.inputSize),this.anchors=fr(this.anchorsData),this.inputSize=Qt([this.width,this.height]),this.config=t,this.scaleFaces=.8}async getBoundingBoxes(e){if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return null;let[t,n,r]=U(()=>{let c=e.resizeBilinear([this.width,this.height]),u=we(c.div(127.5),1),h=this.blazeFaceModel.predict(u),d;if(Array.isArray(h)){let A=h.sort((w,x)=>w.size-x.size),y=ct([A[0],A[2]],2),g=ct([A[1],A[3]],2);d=ct([g,y],1).squeeze(0)}else d=h.squeeze();let p=hre(d,this.anchors,this.inputSize),f=Me(d,[0,0],[-1,1]),m=er(f).squeeze();return[d,p,m]}),a=await St.nonMaxSuppressionAsync(n,r,this.config.face.detector.maxFaces,this.config.face.detector.iouThreshold,this.config.face.detector.scoreThreshold),s=a.arraySync();a.dispose();let i=s.map(c=>Me(n,[c,0],[1,-1])).map(c=>{let u=c.arraySync();return c.dispose(),u}),o=r.dataSync(),l=[];for(let c=0;c<i.length;c++){let u=s[c],h=o[u];if(h>this.config.face.detector.minConfidence){let d=cre(i[c]),p=this.anchorsData[u],f=U(()=>Me(t,[u,m6-1],[1,-1]).squeeze().reshape([m6,-1]));l.push({box:d,landmarks:f,anchor:p,confidence:h})}}return t.dispose(),n.dispose(),r.dispose(),t.dispose(),{boxes:l,scaleFactor:[e.shape[2]/this.width,e.shape[1]/this.height]}}};async function I4(e){let t=await Yn(e.face.detector.modelPath,{fromTFHub:e.face.detector.modelPath.includes("tfhub.dev")}),n=new dre(t,e);return Ue(`load model: ${e.face.detector.modelPath.match(/\/(.*)\./)[1]}`),n}function pre(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 e1(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function t1(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function A6(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 St.cropAndResize(t,s,[0],n)}function jg(e,t=1.5){let n=t1(e),r=e1(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 Gg(e){let t=t1(e),n=e1(e),r=Math.max(...n)/2,a=[t[0]-r,t[1]-r],s=[t[0]+r,t[1]+r];return{startPoint:a,endPoint:s,landmarks:e.landmarks}}var qg=[[1,0,0],[0,1,0],[0,0,1]];function fre(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function mre(e,t){let n=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return fre(n)}function y6(e,t){return[[1,0,e],[0,1,t],[0,0,1]]}function xi(e,t){let n=0;for(let r=0;r<e.length;r++)n+=e[r]*t[r];return n}function Are(e,t){let n=[];for(let r=0;r<e.length;r++)n.push(e[r][t]);return n}function g6(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(xi(e[a],Are(t,s)))}return n}function x6(e,t){let n=Math.cos(e),r=Math.sin(e),a=[[n,-r,0],[r,n,0],[0,0,1]],s=y6(t[0],t[1]),i=g6(s,a),o=y6(-t[0],-t[1]);return g6(i,o)}function yre(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],n=[e[0][2],e[1][2]],r=[-xi(t[0],n),-xi(t[1],n)];return[t[0].concat(r[0]),t[1].concat(r[1]),[0,0,1]]}function gre(e,t){return[xi(e,t[0]),xi(e,t[1])]}var pa={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]},w6=[{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]}],Xg=[[.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]],N4=[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],xre=[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],wre=[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],_re=[33,133,362,263,1,78,308],Wae=xre.map(e=>Xg[e]),Bae=wre.map(e=>Xg[e]),Vae=_re.map(e=>Xg[e]),bre=468,vre=13,kre=[vre,pa.midwayBetweenEyes[0]],Ire=3,Nre=2,Sre=[Ire,Nre],Kg=pa.leftEyeLower0,Zg=[Kg[0],Kg[Kg.length-1]],Jg=pa.rightEyeLower0,Yg=[Jg[0],Jg[Jg.length-1]],Tre=3,Ere=4,Cre=71,Qg=76;function n1(e,t,n,r=null){for(let a=0;a<w6.length;a++){let{key:s,indices:i}=w6[a],o=pa[`${n}${s}`];if(!r||r.includes(s))for(let l=0;l<i.length;l++){let c=i[l];e[o[l]]=[t[c][0],t[c][1],(t[c][2]+e[o[l]][2])/2]}}}var S4=class{constructor(e,t,n,r){this.storedBoxes=[],this.runsWithoutFaceDetector=0,this.boundingBoxDetector=e,this.meshDetector=t,this.irisModel=n,this.meshWidth=r.face.mesh.inputSize,this.meshHeight=r.face.mesh.inputSize,this.irisSize=r.face.iris.inputSize,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(e,t,n,r){let a=e1({startPoint:t.startPoint,endPoint:t.endPoint}),s=[a[0]/this.meshWidth,a[1]/this.meshHeight],i=e.map(h=>[s[0]*(h[0]-this.meshWidth/2),s[1]*(h[1]-this.meshHeight/2),h[2]]),o=n!==0?x6(n,[0,0]):qg,l=n!==0?i.map(h=>[...gre(h,o),h[2]]):i,c=n!==0?yre(r):qg,u=[...t1({startPoint:t.startPoint,endPoint:t.endPoint}),1];return l.map(h=>[h[0]+xi(u,c[0]),h[1]+xi(u,c[1]),h[2]])}getLeftToRightEyeDepthDifference(e){let t=e[Zg[0]][2],n=e[Yg[0]][2];return t-n}getEyeBox(e,t,n,r,a=!1){let s=Gg(jg(this.calculateLandmarksBoundingBox([e[n],e[r]]),this.irisEnlarge)),i=e1(s),o=St.cropAndResize(t,[[s.startPoint[1]/this.meshHeight,s.startPoint[0]/this.meshWidth,s.endPoint[1]/this.meshHeight,s.endPoint[0]/this.meshWidth]],[0],[this.irisSize,this.irisSize]);return a&&(o=St.flipLeftRight(o)),{box:s,boxSize:i,crop:o}}getEyeCoords(e,t,n,r=!1){let a=[];for(let s=0;s<Qg;s++){let i=e[s*3],o=e[s*3+1],l=e[s*3+2];a.push([(r?1-i/this.irisSize:i/this.irisSize)*n[0]+t.startPoint[0],o/this.irisSize*n[1]+t.startPoint[1],l])}return{rawCoords:a,iris:a.slice(Cre)}}getAdjustedIrisCoords(e,t,n){let r=e[pa[`${n}EyeUpper0`][Tre]][2],a=e[pa[`${n}EyeLower0`][Ere]][2],s=(r+a)/2;return t.map((i,o)=>{let l=s;return o===2?l=r:o===4&&(l=a),[i[0],i[1],l]})}async predict(e,t){let n=!1,r;if((this.skipped===0||this.skipped>t.face.detector.skipFrames||!t.face.mesh.enabled||!t.videoOptimized)&&(r=await this.boundingBoxDetector.getBoundingBoxes(e),this.skipped=0),t.videoOptimized&&this.skipped++,r&&r.boxes&&(!t.face.mesh.enabled||r.boxes.length!==this.detectedFaces&&this.detectedFaces!==t.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let s of r.boxes)this.storedBoxes.push({startPoint:s.box.startPoint.dataSync(),endPoint:s.box.endPoint.dataSync(),landmarks:s.landmarks,confidence:s.confidence});this.storedBoxes.length>0&&(n=!0)}if(n){if(!r||!r.boxes||r.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let s=0;s<this.storedBoxes.length;s++){let i=pre({startPoint:this.storedBoxes[s].startPoint,endPoint:this.storedBoxes[s].endPoint},r.scaleFactor),o=jg(i),l=Gg(o),c=this.storedBoxes[s].landmarks.arraySync(),u=this.storedBoxes[s].confidence;this.storedBoxes[s]={...l,confidence:u,landmarks:c}}this.runsWithoutFaceDetector=0}r&&r.boxes&&r.boxes.forEach(s=>{s.box.startPoint.dispose(),s.box.endPoint.dispose(),s.landmarks.dispose()});let a=U(()=>this.storedBoxes.map((s,i)=>{let o,l=0,c;if(t.face.detector.rotation){let[w,x]=s.landmarks.length>=bre?kre:Sre;l=mre(s.landmarks[w],s.landmarks[x]);let _=t1({startPoint:s.startPoint,endPoint:s.endPoint}),I=[_[0]/e.shape[2],_[1]/e.shape[1]],T=St.rotateWithOffset(e,l,0,I);c=x6(-l,_),o=A6({startPoint:s.startPoint,endPoint:s.endPoint},T,[this.meshHeight,this.meshWidth]).div(255)}else{c=qg;let w=e.clone();o=A6({startPoint:s.startPoint,endPoint:s.endPoint},w,[this.meshHeight,this.meshWidth]).div(255)}if(!t.face.mesh.enabled)return{coords:null,box:s,faceConfidence:null,confidence:s.confidence,image:o};let[,u,h]=this.meshDetector.predict(o),d=u.dataSync()[0];if(d<t.face.detector.minConfidence)return null;let p=q(h,[-1,3]).arraySync();if(t.face.iris.enabled){let{box:w,boxSize:x,crop:_}=this.getEyeBox(p,o,Zg[0],Zg[1],!0),{box:I,boxSize:T,crop:E}=this.getEyeBox(p,o,Yg[0],Yg[1]),N=this.irisModel.predict(ct([_,E])).dataSync(),F=N.slice(0,Qg*3),{rawCoords:$,iris:D}=this.getEyeCoords(F,w,x,!0),P=N.slice(Qg*3),{rawCoords:H,iris:V}=this.getEyeCoords(P,I,T),K=this.getLeftToRightEyeDepthDifference(p);Math.abs(K)<30?(n1(p,$,"left"),n1(p,H,"right")):K<1?n1(p,$,"left",["EyeUpper0","EyeLower0"]):n1(p,H,"right",["EyeUpper0","EyeLower0"]);let X=this.getAdjustedIrisCoords(p,D,"left"),ee=this.getAdjustedIrisCoords(p,V,"right");p=p.concat(X).concat(ee)}let f=this.transformRawCoords(p,s,l,c),m=jg(this.calculateLandmarksBoundingBox(f)),A=Gg(m),y=fr(f),g={coords:y,box:m,faceConfidence:d,confidence:s.confidence,image:o,rawCoords:p};return t.face.mesh.returnRawData||delete g.rawCoords,this.storedBoxes[i]={...A,landmarks:y.arraySync(),confidence:s.confidence,faceConfidence:d},g}));return a=a.filter(s=>s!==null),this.detectedFaces=a.length,a}calculateLandmarksBoundingBox(e){let t=e.map(s=>s[0]),n=e.map(s=>s[1]),r=[Math.min(...t),Math.min(...n)],a=[Math.max(...t),Math.max(...n)];return{startPoint:r,endPoint:a,landmarks:e}}},_6=ru(T4()),b6={};Kr(b6,{FaceBoxes:()=>v6,load:()=>Rre});var k6={};function Pc(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};k6[e]=i,Ue("Human profiler",e,i)}var v6=class{constructor(e,t){this.enlarge=1.1,this.model=e,this.config=t}async estimateFaces(e,t){t&&(this.config=t);let n=[],r=St.resizeBilinear(e,[this.config.face.detector.inputSize,this.config.face.detector.inputSize]),a=r.toInt(),s,i;if(t.profile){let o=await Bo(()=>this.model.executeAsync(a));s=o.result[0].dataSync(),i=o.result[1].squeeze().arraySync(),o.result.forEach(l=>l.dispose()),Pc("faceboxes",o)}else{let[o,l,c]=await this.model.executeAsync(a);s=o.dataSync();let u=l.squeeze();i=u.arraySync(),o.dispose(),l.dispose(),u.dispose(),c.dispose()}a.dispose(),r.dispose();for(let o in i)if(s[o]&&s[o]>this.config.face.detector.minConfidence){let l=[i[o][0]/this.enlarge,i[o][1]/this.enlarge,i[o][2]*this.enlarge,i[o][3]*this.enlarge],c=[l[1],l[0],l[3]-l[1],l[2]-l[0]],u=[parseInt((c[0]*e.shape[2]).toString()),parseInt((c[1]*e.shape[1]).toString()),parseInt((c[2]*e.shape[2]).toString()),parseInt((c[3]*e.shape[1]).toString())],h=St.cropAndResize(e,[l],[0],[this.config.face.detector.inputSize,this.config.face.detector.inputSize]),d=h.div([255]);h.dispose(),n.push({confidence:s[o],box:u,boxRaw:this.config.face.mesh.returnRawData?c:null,image:d})}return n}};async function Rre(e){let t=await Yn(e.face.detector.modelPath);Ue(`load model: ${e.face.detector.modelPath.match(/\/(.*)\./)[1]}`);let n=new v6(t,e);return e.face.mesh.enabled&&Ue(`load model: ${e.face.mesh.modelPath.match(/\/(.*)\./)[1]}`),e.face.iris.enabled&&Ue(`load model: ${e.face.iris.modelPath.match(/\/(.*)\./)[1]}`),n}var I6={};Kr(I6,{load:()=>e2,predict:()=>t2});var Ml,r1={age:0},a1=Number.MAX_SAFE_INTEGER;async function e2(e){return Ml||(Ml=await Yn(e.face.age.modelPath),Ue(`load model: ${e.face.age.modelPath.match(/\/(.*)\./)[1]}`)),Ml}async function t2(e,t){return Ml?a1<t.face.age.skipFrames&&t.videoOptimized&&r1.age&&r1.age>0?(a1++,r1):(t.videoOptimized?a1=0:a1=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=St.resizeBilinear(e,[t.face.age.inputSize,t.face.age.inputSize],!1),a=W(r,[255]);Ce(r);let s,i={age:0};if(!t.profile)t.face.age.enabled&&(s=await Ml.predict(a));else{let o=t.face.age.enabled?await Bo(()=>Ml.predict(a)):{};s=o.result.clone(),o.result.dispose(),Pc("age",o)}if(a.dispose(),s){let o=s.dataSync();i.age=Math.trunc(10*o[0])/10}s.dispose(),r1=i,n(i)})):null}var N6={};Kr(N6,{load:()=>n2,predict:()=>r2});var wi,a2={gender:""},s1=Number.MAX_SAFE_INTEGER,s2=!1,i2=[.2989,.587,.114];async function n2(e){return wi||(wi=await Yn(e.face.gender.modelPath),s2=wi.inputs[0].shape[3]===1,Ue(`load model: ${e.face.gender.modelPath.match(/\/(.*)\./)[1]}`)),wi}async function r2(e,t){return wi?s1<t.face.gender.skipFrames&&t.videoOptimized&&a2.gender!==""?(s1++,a2):(t.videoOptimized?s1=0:s1=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=St.resizeBilinear(e,[t.face.gender.inputSize,t.face.gender.inputSize],!1),a;s2?a=U(()=>{let[o,l,c]=an(r,3,3),u=W(o,i2[0]),h=W(l,i2[1]),d=W(c,i2[2]);return Kh([u,h,d]).sub(.5).mul(2)}):a=W(r,[255]),Ce(r);let s,i={gender:"",confidence:0};if(!t.profile)t.face.gender.enabled&&(s=await wi.predict(a));else{let o=t.face.gender.enabled?await Bo(()=>wi.predict(a)):{};s=o.result.clone(),o.result.dispose(),Pc("gender",o)}if(a.dispose(),s){let o=s.dataSync();if(s2){let l=Math.trunc(100*Math.abs(o[0]-o[1]))/100;l>t.face.gender.minConfidence&&(i.gender=o[0]>o[1]?"female":"male",i.confidence=l)}else{let l=Math.trunc(200*Math.abs(o[0]-.5))/100;l>t.face.gender.minConfidence&&(i.gender=o[0]<=.5?"female":"male",i.confidence=Math.min(.99,l))}}s.dispose(),a2=i,n(i)})):null}var S6={};Kr(S6,{load:()=>o2,predict:()=>l2});var Fre=["angry","disgust","fear","happy","sad","surprise","neutral"],$l,u2=[],i1=Number.MAX_SAFE_INTEGER,c2=[.2989,.587,.114],T6=1;async function o2(e){return $l||($l=await Yn(e.face.emotion.modelPath),Ue(`load model: ${e.face.emotion.modelPath.match(/\/(.*)\./)[1]}`)),$l}async function l2(e,t){return $l?i1<t.face.emotion.skipFrames&&t.videoOptimized&&u2.length>0?(i1++,u2):(t.videoOptimized?i1=0:i1=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=St.resizeBilinear(e,[t.face.emotion.inputSize,t.face.emotion.inputSize],!1),[a,s,i]=an(r,3,3);r.dispose();let o=W(a,c2[0]),l=W(s,c2[1]),c=W(i,c2[2]);a.dispose(),s.dispose(),i.dispose();let u=Kh([o,l,c]);o.dispose(),l.dispose(),c.dispose();let h=U(()=>u.sub(.5).mul(2));u.dispose();let d=[];if(t.face.emotion.enabled){let p;if(t.profile){let f=await Bo(()=>$l.predict(h));p=f.result.dataSync(),f.result.dispose(),Pc("emotion",f)}else{let f=await $l.predict(h);p=f.dataSync(),Ce(f)}for(let f=0;f<p.length;f++)T6*p[f]>t.face.emotion.minConfidence&&d.push({score:Math.min(.99,Math.trunc(100*T6*p[f])/100),emotion:Fre[f]});d.sort((f,m)=>m.score-f.score)}h.dispose(),u2=d,n(d)})):null}var Dl;async function E6(e){return Dl||(Dl=await Yn(e.face.embedding.modelPath),Ue(`load model: ${e.face.embedding.modelPath.match(/\/(.*)\./)[1]}`)),Dl}function Mre(e,t){if((e==null?void 0:e.length)!==(t==null?void 0:t.length))return 0;let n=2,r=10*e.map((a,s)=>a-t[s]).reduce((a,s)=>a+s**n,0)**(1/n);return Math.trunc(1e3*(1-r))/1e3}async function C6(e,t){return Dl?new Promise(async n=>{let r=St.resizeBilinear(e,[t.face.embedding.inputSize,t.face.embedding.inputSize],!1),a=[];if(t.face.embedding.enabled)if(t.profile){let s=await Bo(()=>Dl.predict({img_inputs:r}));a=[...s.result.dataSync()],s.result.dispose(),Pc("emotion",s)}else{let s=await Dl.predict({img_inputs:r});a=[...s.dataSync()],Ce(s)}r.dispose(),n(a)}):null}var R6={};Kr(R6,{PoseNet:()=>F6,load:()=>h2});var $re=[-123.15,-115.9,-103.06];function Dre(e){let[t,n,r,a]=e;return{offsets:t,heatmap:n,displacementFwd:r,displacementBwd:a}}function Ore(e){let[t,n,r,a]=e;return{offsets:r,heatmap:a,displacementFwd:t,displacementBwd:n}}var zre=class{constructor(e){this.model=e}predict(e,t){return U(()=>{let n=(t.body.modelType==="ResNet"?e.toFloat().add($re):e.toFloat().div(127.5).sub(1)).expandDims(0),r=this.model.predict(n).map(s=>s.squeeze([0])),a=t.body.modelType==="ResNet"?Ore(r):Dre(r);return{heatmapScores:a.heatmap.sigmoid(),offsets:a.offsets,displacementFwd:a.displacementFwd,displacementBwd:a.displacementBwd}})}dispose(){this.model.dispose()}};function d2(e){return Math.floor(e/2)}var Pre=class{constructor(e,t){this.priorityQueue=new Array(e),this.numberOfElements=-1,this.getElementValue=t}enqueue(e){this.priorityQueue[++this.numberOfElements]=e,this.swim(this.numberOfElements)}dequeue(){let e=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,e}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(e){for(;e>0&&this.less(d2(e),e);)this.exchange(e,d2(e)),e=d2(e)}sink(e){for(;2*e<=this.numberOfElements;){let t=2*e;if(t<this.numberOfElements&&this.less(t,t+1)&&t++,!this.less(e,t))break;this.exchange(e,t),e=t}}getValueAt(e){return this.getElementValue(this.priorityQueue[e])}less(e,t){return this.getValueAt(e)<this.getValueAt(t)}exchange(e,t){let n=this.priorityQueue[e];this.priorityQueue[e]=this.priorityQueue[t],this.priorityQueue[t]=n}};function Lre(e,t,n,r,a,s){let[i,o]=s.shape,l=!0,c=Math.max(n-a,0),u=Math.min(n+a+1,i);for(let h=c;h<u;++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 Wre(e,t,n){let[r,a,s]=n.shape,i=new Pre(r*a*s,({score:o})=>o);for(let o=0;o<r;++o)for(let l=0;l<a;++l)for(let c=0;c<s;++c){let u=n.get(o,l,c);u<e||Lre(c,u,o,l,t,n)&&i.enqueue({score:u,part:{heatmapY:o,heatmapX:l,id:c}})}return i}var Ol=ru(kf()),Bre=ru(kf());function M6(e,t,n,r){return{y:r.get(e,t,n),x:r.get(e,t,n+Bre.NUM_KEYPOINTS)}}function $6(e,t,n){let{heatmapY:r,heatmapX:a,id:s}=e,{y:i,x:o}=M6(r,a,s,n);return{x:e.heatmapX*t+o,y:e.heatmapY*t+i}}function D6(e,t,n){return e<t?t:e>n?n:e}function Vre(e,t,n,r){let a=n-e,s=r-t;return a*a+s*s}function O6(e,t){return{x:e.x+t.x,y:e.y+t.y}}var p2=ru(kf());function Ure(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 Hre(e,t,n,r){return{y:r.get(e,t,n),x:r.get(e,t,n+p2.NUM_KEYPOINTS)}}function jre(e,t){let n=[];for(let r=0;r<p2.NUM_KEYPOINTS;r++){let a=e.get(r,0).valueOf(),s=e.get(r,1).valueOf(),{x:i,y:o}=Hre(a,s,r,t);n.push(o),n.push(i)}return fr(n,[p2.NUM_KEYPOINTS,2])}function Gre(e,t,n){return U(()=>e.toTensor().mul(Se(t,"int32")).toFloat().add(jre(e,n)))}function qre(e,t){return U(()=>{let n=e.div(Se(t,"int32"));return e.sub(n.mul(Se(t,"int32")))})}function Xre(e){let[t,n,r]=e.shape;return U(()=>{let a=e.reshape([t*n,r]).argMax(0),s=a.div(Se(n,"int32")).expandDims(1),i=qre(a,n).expandDims(1);return ct([s,i],1)})}var z6=Ol.poseChain.map(([e,t])=>[Ol.partIds[e],Ol.partIds[t]]),f2=z6.map(([,e])=>e),P6=z6.map(([e])=>e);function Kre(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 m2(e,t,n,r){return{y:D6(Math.round(e.y/t),0,n-1),x:D6(Math.round(e.x/t),0,r-1)}}function L6(e,t,n,r,a,s,i,o=2){let[l,c]=r.shape,u=m2(t.position,s,l,c),h=Kre(e,u,i),d=O6(t.position,h);for(let m=0;m<o;m++){let A=m2(d,s,l,c),y=M6(A.y,A.x,n,a);d=O6({x:A.x*s,y:A.y*s},{x:y.x,y:y.y})}let p=m2(d,s,l,c),f=r.get(p.y,p.x,n);return{position:d,part:Ol.partNames[n],score:f}}function Zre(e,t,n,r,a,s){let i=t.shape[2],o=f2.length,l=new Array(i),{part:c,score:u}=e,h=$6(c,r,n);l[c.id]={score:u,part:Ol.partNames[c.id],position:h};for(let d=o-1;d>=0;--d){let p=f2[d],f=P6[d];l[p]&&!l[f]&&(l[f]=L6(d,l[p],f,t,n,r,s))}for(let d=0;d<o;++d){let p=P6[d],f=f2[d];l[p]&&!l[f]&&(l[f]=L6(d,l[p],f,t,n,r,a))}return l}async function Jre(e,t,n){let r=0,a=Xre(e),s=await Promise.all([e.buffer(),t.buffer(),a.buffer()]),i=s[0],o=s[1],l=s[2],c=Gre(l,n.body.outputStride,o),u=await c.buffer(),h=Array.from(Ure(i,l)).map((p,f)=>(r+=p,{position:{y:u.get(f,0),x:u.get(f,1)},part:Ol.partNames[f],score:p})),d=h.filter(p=>p.score>n.body.scoreThreshold);return a.dispose(),c.dispose(),{keypoints:d,score:r/h.length}}var Yre=1;function W6(e,t,{x:n,y:r},a){return e.some(({keypoints:s})=>{let i=s[a].position;return Vre(r,n,i.y,i.x)<=t})}function Qre(e,t,n){return n.reduce((r,{position:a,score:s},i)=>(W6(e,t,a,i)||(r+=s),r),0)/n.length}function eae(e,t,n,r,a){let s=[],i=Wre(a.body.scoreThreshold,Yre,e),o=a.body.nmsRadius^2;for(;s.length<a.body.maxDetections&&!i.empty();){let l=i.dequeue(),c=$6(l.part,a.body.outputStride,t);if(W6(s,o,c,l.part.id))continue;let u=Zre(l,e,t,a.body.outputStride,n,r),h=Qre(s,o,u);h>a.body.scoreThreshold&&s.push({keypoints:u,score:h})}return s}async function tae(e){return Promise.all(e.map(t=>t.buffer()))}function nae(e,t,n){return{score:e.score,keypoints:e.keypoints.map(({score:r,part:a,position:s})=>({score:r,part:a,position:{x:s.x*n,y:s.y*t}}))}}function rae(e,[t,n]){let r=e.squeeze(0),a=r.resizeBilinear([t,n]);return r.dispose(),a}function B6(e,[t,n],[r,a]){return e.map(s=>nae(s,t/r,n/a))}async function aae(e,t,n){return new Promise(async r=>{let a=e.shape[1],s=e.shape[2],i=await tae([t.heatmapScores,t.offsets,t.displacementFwd,t.displacementBwd]),o=i[0],l=i[1],c=i[2],u=i[3],h=await eae(o,l,c,u,n),d=B6(h,[a,s],[n.body.inputSize,n.body.inputSize]);r(d)})}async function sae(e,t,n){return new Promise(async r=>{let a=e.shape[1],s=e.shape[2],i=[await Jre(t.heatmapScores,t.offsets,n)],o=B6(i,[a,s],[n.body.inputSize,n.body.inputSize]);r(o)})}var F6=class{constructor(e){this.baseModel=e}async estimatePoses(e,t){let n=rae(e,[t.body.inputSize,t.body.inputSize]),r=this.baseModel.predict(n,t),a=t.body.maxDetections<2?await sae(e,r,t):await aae(e,r,t);return r.heatmapScores.dispose(),r.offsets.dispose(),r.displacementFwd.dispose(),r.displacementBwd.dispose(),n.dispose(),a}dispose(){this.baseModel.dispose()}};async function h2(e){let t=await Yn(e.body.modelPath),n=new zre(t);return Ue(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`),new F6(n)}var V6={};Kr(V6,{HandPose:()=>U6,load:()=>A2});function y2(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function o1(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function iae(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 St.cropAndResize(t,s,[0],n)}function oae(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 g2(e,t=1.5){let n=o1(e),r=y2(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 x2(e){let t=o1(e),n=y2(e),r=Math.max(...n)/2,a=[t[0]-r,t[1]-r],s=[t[0]+r,t[1]+r];return{startPoint:a,endPoint:s,palmLandmarks:e.palmLandmarks}}var lae=class{constructor(e,t,n){this.model=e,this.anchors=n.map(r=>[r.x_center,r.y_center]),this.anchorsTensor=fr(this.anchors),this.inputSizeTensor=Qt([t,t]),this.doubleInputSizeTensor=Qt([t*2,t*2])}normalizeBoxes(e){return U(()=>{let t=Me(e,[0,0],[-1,2]),n=Me(e,[0,2],[-1,2]),r=oe(Ne(t,this.inputSizeTensor),this.anchorsTensor),a=Ne(n,this.doubleInputSizeTensor),s=W(we(r,a),this.inputSizeTensor),i=W(oe(r,a),this.inputSizeTensor);return Jh([s,i],1)})}normalizeLandmarks(e,t){return U(()=>{let n=oe(Ne(e.reshape([-1,7,2]),this.inputSizeTensor),this.anchors[t]);return W(n,this.inputSizeTensor)})}async getBoxes(e,t){let n=this.model.predict(e),r=n.squeeze();n.dispose();let a=U(()=>er(Me(r,[0,0],[-1,1])).squeeze()),s=a.dataSync(),i=Me(r,[0,1],[-1,4]),o=this.normalizeBoxes(i);i.dispose();let l=await St.nonMaxSuppressionAsync(o,s,t.hand.maxHands,t.hand.iouThreshold,t.hand.scoreThreshold),c=l.arraySync();a.dispose(),l.dispose();let u=[];for(let h of c)if(s[h]>=t.hand.minConfidence){let d=Me(o,[h,0],[1,-1]),p=Me(r,[h,5],[1,14]),f=U(()=>this.normalizeLandmarks(p,h).reshape([-1,2]));p.dispose(),u.push({box:d,palmLandmarks:f,confidence:s[h]})}return r.dispose(),o.dispose(),u}async estimateHandBounds(e,t){let n=e.shape[1],r=e.shape[2],a=U(()=>e.resizeBilinear([t.hand.inputSize,t.hand.inputSize]).div(127.5).sub(1)),s=await this.getBoxes(a,t);a.dispose();let i=[];if(!s||s.length===0)return i;for(let o of s){let l=o.box.dataSync(),c=l.slice(0,2),u=l.slice(2,4),h=o.palmLandmarks.arraySync();o.box.dispose(),o.palmLandmarks.dispose(),i.push(oae({startPoint:c,endPoint:u,palmLandmarks:h,confidence:o.confidence},[r/t.hand.inputSize,n/t.hand.inputSize]))}return i}};function uae(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function cae(e,t){let n=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return uae(n)}var H6=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function _i(e,t){let n=0;for(let r=0;r<e.length;r++)n+=e[r]*t[r];return n}function hae(e,t){let n=[];for(let r=0;r<e.length;r++)n.push(e[r][t]);return n}function j6(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(_i(e[a],hae(t,s)))}return n}function G6(e,t){let n=Math.cos(e),r=Math.sin(e),a=[[n,-r,0],[r,n,0],[0,0,1]],s=H6(t[0],t[1]),i=j6(s,a),o=H6(-t[0],-t[1]);return j6(i,o)}function dae(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],n=[e[0][2],e[1][2]],r=[-_i(t[0],n),-_i(t[1],n)];return[t[0].concat(r[0]),t[1].concat(r[1]),[0,0,1]]}function q6(e,t){return[_i(e,t[0]),_i(e,t[1])]}var pae=5,X6=1.65,K6=[0,5,9,13,17,1,2],fae=0,mae=2,Aae=class{constructor(e,t,n){this.handDetector=e,this.landmarkDetector=t,this.inputSize=n,this.storedBoxes=[],this.skipped=0,this.detectedHands=0}getBoxForPalmLandmarks(e,t){let n=e.map(a=>q6([...a,1],t)),r=this.calculateLandmarksBoundingBox(n);return g2(x2(r),pae)}getBoxForHandLandmarks(e){let t=this.calculateLandmarksBoundingBox(e),n=g2(x2(t),X6);n.palmLandmarks=[];for(let r=0;r<K6.length;r++)n.palmLandmarks.push(e[K6[r]].slice(0,2));return n}transformRawCoords(e,t,n,r){let a=y2(t),s=[a[0]/this.inputSize,a[1]/this.inputSize,(a[0]+a[1])/this.inputSize/2],i=e.map(d=>[s[0]*(d[0]-this.inputSize/2),s[1]*(d[1]-this.inputSize/2),s[2]*d[2]]),o=G6(n,[0,0]),l=i.map(d=>[...q6(d,o),d[2]]),c=dae(r),u=[...o1(t),1],h=[_i(u,c[0]),_i(u,c[1])];return l.map(d=>[d[0]+h[0],d[1]+h[1],d[2]])}async estimateHands(e,t){let n=!1,r;(this.skipped===0||this.skipped>t.hand.skipFrames||!t.hand.landmarks||!t.videoOptimized)&&(r=await this.handDetector.estimateHandBounds(e,t),this.skipped=0),t.videoOptimized&&this.skipped++,r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==t.hand.maxHands||!t.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(n=!0));let a=[];for(let s=0;s<this.storedBoxes.length;s++){let i=this.storedBoxes[s];if(i)if(t.hand.landmarks){let o=t.hand.rotation?cae(i.palmLandmarks[fae],i.palmLandmarks[mae]):0,l=o1(i),c=[l[0]/e.shape[2],l[1]/e.shape[1]],u=t.hand.rotation?St.rotateWithOffset(e,o,0,c):e.clone(),h=G6(-o,l),d=n?this.getBoxForPalmLandmarks(i.palmLandmarks,h):i,p=iae(d,u,[this.inputSize,this.inputSize]),f=p.div(255);p.dispose(),u.dispose();let[m,A]=await this.landmarkDetector.predict(f);f.dispose();let y=m.dataSync()[0];if(m.dispose(),y>=t.hand.minConfidence){let g=q(A,[-1,3]),w=g.arraySync();A.dispose(),g.dispose();let x=this.transformRawCoords(w,d,o,h),_=this.getBoxForHandLandmarks(x);this.storedBoxes[s]=_;let I={landmarks:x,confidence:y,box:{topLeft:_.startPoint,bottomRight:_.endPoint}};a.push(I)}else this.storedBoxes[s]=null;A.dispose()}else{let o=g2(x2(i),X6),l={confidence:i.confidence,box:{topLeft:o.startPoint,bottomRight:o.endPoint}};a.push(l)}}return this.storedBoxes=this.storedBoxes.filter(s=>s!==null),this.detectedHands=a.length,a}calculateLandmarksBoundingBox(e){let t=e.map(s=>s[0]),n=e.map(s=>s[1]),r=[Math.min(...t),Math.min(...n)],a=[Math.max(...t),Math.max(...n)];return{startPoint:r,endPoint:a}}},yae=[{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}],w2={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]},U6=class{constructor(e){this.handPipeline=e}static getAnnotations(){return w2}async estimateHands(e,t){let n=await this.handPipeline.estimateHands(e,t);if(!n)return[];let r=[];for(let a of n){let s={};if(a.landmarks)for(let o of Object.keys(w2))s[o]=w2[o].map(l=>a.landmarks[l]);let i=a.box?[Math.max(0,a.box.topLeft[0]),Math.max(0,a.box.topLeft[1]),Math.min(e.shape[2],a.box.bottomRight[0])-a.box.topLeft[0],Math.min(e.shape[1],a.box.bottomRight[1])-a.box.topLeft[1]]:0;r.push({confidence:a.confidence,box:i,landmarks:a.landmarks,annotations:s})}return r}};async function A2(e){let[t,n]=await Promise.all([e.hand.enabled?Yn(e.hand.detector.modelPath,{fromTFHub:e.hand.detector.modelPath.includes("tfhub.dev")}):null,e.hand.landmarks?Yn(e.hand.skeleton.modelPath,{fromTFHub:e.hand.skeleton.modelPath.includes("tfhub.dev")}):null]),r=new lae(t,e.hand.inputSize,yae),a=new Aae(r,n,e.hand.inputSize),s=new U6(a);return e.hand.enabled&&Ue(`load model: ${e.hand.detector.modelPath.match(/\/(.*)\./)[1]}`),e.hand.landmarks&&Ue(`load model: ${e.hand.skeleton.modelPath.match(/\/(.*)\./)[1]}`),s}var gae=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},xae=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[35][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 a=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]));a>10&&t.push({face:n,gesture:`mouth ${Math.trunc(a)}% open`});let s=e[n].mesh[152][2];Math.abs(s)>10&&t.push({face:n,gesture:`head ${s<0?"up":"down"}`})}return t},wae=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){if(!e[n].annotations||!e[n].annotations.leftEyeIris||!e[n].annotations.rightEyeIris)continue;let r=e[n].annotations.leftEyeIris[3][0]-e[n].annotations.leftEyeIris[1][0],a=e[n].annotations.leftEyeIris[4][1]-e[n].annotations.leftEyeIris[2][1],s=Math.abs(r*a),i=e[n].annotations.rightEyeIris[3][0]-e[n].annotations.rightEyeIris[1][0],o=e[n].annotations.rightEyeIris[4][1]-e[n].annotations.rightEyeIris[2][1],l=Math.abs(i*o);Math.abs(s-l)/Math.max(s,l)<.25&&t.push({iris:n,gesture:"looking at camera"})}return t},_ae=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){let r=[];for(let[a,s]of Object.entries(e[n].annotations))a!=="palmBase"&&r.push({name:a.toLowerCase(),position:s[0]});if(r&&r.length>0){let a=r.reduce((i,o)=>i.position[2]<o.position[2]?i:o),s=r.reduce((i,o)=>i.position[1]<o.position[1]?i:o);t.push({hand:n,gesture:`${a.name} forward ${s.name} up`})}}return t},bae=ru(E4()),Et=null,Jt=null;function Z6(e,t){let n;if(e instanceof Qe)n=Nr(e);else{let r=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,a=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0,s=r,i=a;if(t.filter.width>0?s=t.filter.width:t.filter.height>0&&(s=r*(t.filter.height/a)),t.filter.height>0?i=t.filter.height:t.filter.width>0&&(i=a*(t.filter.width/r)),!s||!i)return Ue("Human: invalid input",e),null;(!Et||Et.width!==s||Et.height!==i)&&(Et=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(s,i):document.createElement("canvas"),Et.width!==s&&(Et.width=s),Et.height!==i&&(Et.height=i));let o=Et.getContext("2d");if(e instanceof ImageData?o.putImageData(e,0,0):o.drawImage(e,0,0,r,a,0,0,Et.width,Et.height),t.filter.enabled){if((!this.fx||!Jt||Et.width!==Jt.width||Et.height!==Jt.height)&&(Jt=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(Et.width,Et.height):document.createElement("canvas"),Jt.width!==Et.width&&(Jt.width=Et.width),Jt.height!==Et.height&&(Jt.height=Et.height),this.fx=bn.flags.IS_BROWSER?new bae.GLImageFilter({canvas:Jt}):null),!this.fx)return Et;this.fx.reset(),this.fx.addFilter("brightness",t.filter.brightness),t.filter.contrast!==0&&this.fx.addFilter("contrast",t.filter.contrast),t.filter.sharpness!==0&&this.fx.addFilter("sharpen",t.filter.sharpness),t.filter.blur!==0&&this.fx.addFilter("blur",t.filter.blur),t.filter.saturation!==0&&this.fx.addFilter("saturation",t.filter.saturation),t.filter.hue!==0&&this.fx.addFilter("hue",t.filter.hue),t.filter.negative&&this.fx.addFilter("negative"),t.filter.sepia&&this.fx.addFilter("sepia"),t.filter.vintage&&this.fx.addFilter("brownie"),t.filter.sepia&&this.fx.addFilter("sepia"),t.filter.kodachrome&&this.fx.addFilter("kodachrome"),t.filter.technicolor&&this.fx.addFilter("technicolor"),t.filter.polaroid&&this.fx.addFilter("polaroid"),t.filter.pixelate!==0&&this.fx.addFilter("pixelate",t.filter.pixelate),this.fx.apply(Et)}else Jt=Et;let l;if(Jt.data){let u=[Jt.height,Jt.width,3];l=Sf(Jt.data,u,"int32")}else if(t.backend==="webgl"||Jt instanceof ImageData)l=ku.fromPixels(Jt);else{let u=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(s,i):document.createElement("canvas");u.width=s,u.height=i;let h=u.getContext("2d");h==null||h.drawImage(Jt,0,0);let d=h==null?void 0:h.getImageData(0,0,s,i);l=ku.fromPixels(d)}let c=l.toFloat();n=c.expandDims(0),l.dispose(),c.dispose()}return{tensor:n,canvas:t.filter.return?Jt:null}}var vae={backend:"webgl",wasmPath:"../assets/",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",inputSize:256,rotation:!1,maxFaces:10,skipFrames:11,minConfidence:.5,iouThreshold:.2,scoreThreshold:.5},mesh:{enabled:!0,modelPath:"../models/facemesh.json",inputSize:192,returnRawData:!1},iris:{enabled:!0,modelPath:"../models/iris.json",inputSize:64},age:{enabled:!0,modelPath:"../models/age-ssrnet-imdb.json",inputSize:64,skipFrames:31},gender:{enabled:!0,minConfidence:.1,modelPath:"../models/gender-ssrnet-imdb.json",inputSize:64,skipFrames:41},emotion:{enabled:!0,inputSize:64,minConfidence:.2,skipFrames:21,modelPath:"../models/emotion-large.json"},embedding:{enabled:!1,inputSize:112,modelPath:"../models/mobilefacenet.json"}},body:{enabled:!0,modelPath:"../models/posenet.json",inputSize:257,maxDetections:10,scoreThreshold:.5,nmsRadius:20,outputStride:16,modelType:"MobileNet"},hand:{enabled:!0,rotation:!1,inputSize:256,skipFrames:12,minConfidence:.1,iouThreshold:.1,scoreThreshold:.5,maxHands:1,landmarks:!0,detector:{modelPath:"../models/handdetect.json"},skeleton:{modelPath:"../models/handskeleton.json"}}},_2=`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==`,b2=`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`,kae="0.20.2",ft=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function zl(...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]=zl(s,i):n[a]=i}),n),{})}var J6=class{constructor(e={}){this.tf=M2,this.version=kae,this.config=zl(vae,e),this.fx=null,this.state="idle",this.numTensors=0,this.analyzeMemoryLeaks=!1,this.checkSanity=!1,this.firstRun=!0,this.perf={},this.models={facemesh:null,posenet:null,handpose:null,iris:null,age:null,gender:null,emotion:null},this.facemesh=_6,this.age=I6,this.gender=N6,this.emotion=S6,this.body=R6,this.hand=V6}profile(){return this.config.profile?k6:{}}analyze(...e){if(!this.analyzeMemoryLeaks)return;let t=Ln().state.numTensors,n=this.numTensors;this.numTensors=t;let r=t-n;r!==0&&Ue(...e,r)}sanity(e){if(!this.checkSanity)return null;if(!e)return"input is not defined";if(bn.flags.IS_NODE&&!(e instanceof Qe))return"input must be a tensor";try{qh()}catch(t){return"backend not loaded"}return null}simmilarity(e,t){return this.config.face.embedding.enabled?Mre(e,t):0}async load(e=null){this.state="load";let t=ft();e&&(this.config=zl(this.config,e)),this.firstRun&&(Ue(`version: ${this.version} TensorFlow/JS version: ${V2}`),await this.checkBackend(!0),bn.flags.IS_BROWSER&&(Ue("configuration:",this.config),Ue("tf flags:",bn.flags)));let n=this.config.face.detector.modelPath.includes("faceboxes")?b6:_6;this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.posenet,this.models.handpose]=await Promise.all([this.models.face||(this.config.face.enabled?n.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?e2(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?n2(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?o2(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?E6(this.config):null),this.models.posenet||(this.config.body.enabled?h2(this.config):null),this.models.handpose||(this.config.hand.enabled?A2(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await n.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await e2(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await n2(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await o2(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await E6(this.config)),this.config.body.enabled&&!this.models.posenet&&(this.models.posenet=await h2(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await A2(this.config))),this.firstRun&&(Ue("tf engine state:",Ln().state.numBytes,"bytes",Ln().state.numTensors,"tensors"),this.firstRun=!1);let r=Math.trunc(ft()-t);r>(this.perf.load||0)&&(this.perf.load=r)}async checkBackend(e=!1){if(this.config.backend&&this.config.backend!==""&&e||qh()!==this.config.backend){let t=ft();this.state="backend",Ue("setting backend:",this.config.backend),this.config.backend==="wasm"&&(Ue("settings wasm path:",this.config.wasmPath),S0(this.config.wasmPath),await Q().getAsync("WASM_HAS_SIMD_SUPPORT")||Ue("warning: wasm simd support is not enabled")),this.config.backend==="humangl"&&lre();try{await H2(this.config.backend)}catch(n){Ue("error: cannot set backend:",this.config.backend,n)}if(U2(),qh()==="webgl"){this.config.deallocate&&(Ue("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),bn.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1)),bn.set("WEBGL_FORCE_F16_TEXTURES",!0),bn.set("WEBGL_PACK_DEPTHWISECONV",!0);let n=await Rf().getGPGPUContext().gl;Ue(`gl version:${n.getParameter(n.VERSION)} renderer:${n.getParameter(n.RENDERER)}`)}await j2(),this.perf.backend=Math.trunc(ft()-t)}}async detectFace(e){var t,n,r,a,s,i;let o,l,c,u,h,d=[];this.state="run:face",o=ft();let p=await((t=this.models.face)==null?void 0:t.estimateFaces(e,this.config));this.perf.face=Math.trunc(ft()-o);for(let f of p){if(this.analyze("Get Face"),!f.image||f.image.isDisposedInternal){Ue("Face object is disposed:",f.image);continue}this.analyze("Start Age:"),this.config.async?l=this.config.face.age.enabled?t2(f.image,this.config):{}:(this.state="run:age",o=ft(),l=this.config.face.age.enabled?await t2(f.image,this.config):{},this.perf.age=Math.trunc(ft()-o)),this.analyze("Start Gender:"),this.config.async?c=this.config.face.gender.enabled?r2(f.image,this.config):{}:(this.state="run:gender",o=ft(),c=this.config.face.gender.enabled?await r2(f.image,this.config):{},this.perf.gender=Math.trunc(ft()-o)),this.analyze("Start Emotion:"),this.config.async?u=this.config.face.emotion.enabled?l2(f.image,this.config):{}:(this.state="run:emotion",o=ft(),u=this.config.face.emotion.enabled?await l2(f.image,this.config):{},this.perf.emotion=Math.trunc(ft()-o)),this.analyze("End Emotion:"),this.analyze("Start Embedding:"),this.config.async?h=this.config.face.embedding.enabled?C6(f.image,this.config):{}:(this.state="run:embedding",o=ft(),h=this.config.face.embedding.enabled?await C6(f.image,this.config):{},this.perf.embedding=Math.trunc(ft()-o)),this.analyze("End Emotion:"),this.config.async&&([l,c,u,h]=await Promise.all([l,c,u,h])),this.analyze("Finish Face:"),!this.config.face.iris.enabled&&((n=f==null?void 0:f.annotations)==null?void 0:n.leftEyeIris)&&((r=f==null?void 0:f.annotations)==null?void 0:r.rightEyeIris)&&(delete f.annotations.leftEyeIris,delete f.annotations.rightEyeIris);let m=((a=f.annotations)==null?void 0:a.leftEyeIris)&&((s=f.annotations)==null?void 0:s.rightEyeIris)?11.7*Math.max(Math.abs(f.annotations.leftEyeIris[3][0]-f.annotations.leftEyeIris[1][0]),Math.abs(f.annotations.rightEyeIris[4][1]-f.annotations.rightEyeIris[2][1])):0;d.push({confidence:f.confidence,box:f.box,mesh:f.mesh,boxRaw:f.boxRaw,meshRaw:f.meshRaw,annotations:f.annotations,age:l.age,gender:c.gender,genderConfidence:c.confidence,emotion:u,embedding:h,iris:m!==0?Math.trunc(m)/100:0}),(i=f.image)==null||i.dispose(),this.analyze("End Face")}return this.analyze("End FaceMesh:"),this.config.async&&(this.perf.face&&delete this.perf.face,this.perf.age&&delete this.perf.age,this.perf.gender&&delete this.perf.gender,this.perf.emotion&&delete this.perf.emotion),d}async image(e,t={}){var n;this.state="image",this.config=zl(this.config,t);let r=Z6(e,this.config);return(n=r==null?void 0:r.tensor)==null||n.dispose(),r==null?void 0:r.canvas}async detect(e,t={}){return new Promise(async n=>{var r,a,s,i;this.state="config";let o;this.config=zl(this.config,t),this.state="check";let l=this.sanity(e);l&&(Ue(l,e),n({error:l}));let c,u,h,d=ft();await this.checkBackend(),await this.load(),this.config.scoped&&Ln().startScope(),this.analyze("Start Scope:"),o=ft();let p=Z6(e,this.config);if(!p||!p.tensor){Ue("could not convert input to tensor"),n({error:"could not convert input to tensor"});return}this.perf.image=Math.trunc(ft()-o),this.analyze("Get Image:"),this.config.async?(h=this.config.face.enabled?this.detectFace(p.tensor):[],this.perf.face&&delete this.perf.face):(this.state="run:face",o=ft(),h=this.config.face.enabled?await this.detectFace(p.tensor):[],this.perf.face=Math.trunc(ft()-o)),this.analyze("Start Body:"),this.config.async?(c=this.config.body.enabled?(r=this.models.posenet)==null?void 0:r.estimatePoses(p.tensor,this.config):[],this.perf.body&&delete this.perf.body):(this.state="run:body",o=ft(),c=this.config.body.enabled?await((a=this.models.posenet)==null?void 0:a.estimatePoses(p.tensor,this.config)):[],this.perf.body=Math.trunc(ft()-o)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(u=this.config.hand.enabled?(s=this.models.handpose)==null?void 0:s.estimateHands(p.tensor,this.config):[],this.perf.hand&&delete this.perf.hand):(this.state="run:hand",o=ft(),u=this.config.hand.enabled?await((i=this.models.handpose)==null?void 0:i.estimateHands(p.tensor,this.config)):[],this.perf.hand=Math.trunc(ft()-o)),this.analyze("End Hand:"),this.config.async&&([h,c,u]=await Promise.all([h,c,u])),p.tensor.dispose(),this.config.scoped&&Ln().endScope(),this.analyze("End Scope:");let f=[];this.config.gesture.enabled&&(o=ft(),f=[...xae(h),...gae(c),..._ae(u),...wae(h)],this.config.async?this.perf.gesture&&delete this.perf.gesture:this.perf.gesture=Math.trunc(ft()-o)),this.perf.total=Math.trunc(ft()-d),this.state="idle",n({face:h,body:c,hand:u,gesture:f,performance:this.perf,canvas:p.canvas})})}async warmupBitmap(){let e=(r,a="application/octet-stream")=>fetch(`data:${a};base64,${r}`).then(s=>s.blob()),t,n;switch(this.config.warmup){case"face":t=await e(_2);break;case"full":t=await e(b2);break;default:t=null}if(t){let r=await createImageBitmap(t);n=await this.detect(r,this.config),r.close()}return n}async warmupCanvas(){return new Promise(e=>{let t,n=0;switch(this.config.warmup){case"face":n=256,t="data:image/jpeg;base64,"+_2;break;case"full":n=1200,t="data:image/jpeg;base64,"+b2;break;default:t=null}let r=new Image(n,n);r.onload=()=>{let a=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(n,n):document.createElement("canvas");a.width=n,a.height=n;let s=a.getContext("2d");s==null||s.drawImage(r,0,0);let i=s==null?void 0:s.getImageData(0,0,n,n);this.detect(i,this.config).then(o=>e(o))},t?r.src=t:e(null)})}async warmupNode(){let e=s=>Buffer.from(s,"base64"),t=this.config.warmup==="face"?e(_2):e(b2),n=(void 0).decodeJpeg(t),r=n.expandDims(0);Ce(n);let a=await this.detect(r,this.config);return Ce(r),a}async warmup(e){let t=ft();e&&(this.config=zl(this.config,e));let n=this.config.videoOptimized;this.config.videoOptimized=!1;let r;typeof createImageBitmap=="function"?r=await this.warmupBitmap():typeof Image!="undefined"?r=await this.warmupCanvas():r=await this.warmupNode(),this.config.videoOptimized=n;let a=ft();return Ue("Warmup",this.config.warmup,Math.round(a-t),"ms",r),r}};async function Iae(e,t,n){if(!e)return;let r=t.getContext("2d");r.font=n.baseFont,r.fillStyle=n.baseLabel;let a=1;for(let s=0;s<e.length;s++){let[i,o]=Object.entries(e[s]);if(o.length>1&&o[1].length>0){let l=i[1]>0?`#${i[1]}`:"",c=`${i[0]} ${l}: ${o[1]}`;r.fillStyle="black",r.fillText(c,8,2+a*n.baseLineHeight),r.fillStyle=n.baseLabel,r.fillText(c,6,0+a*n.baseLineHeight),a+=1}}}async function Nae(e,t,n,r){if(!e)return;let a=t.getContext("2d");for(let s of e){a.font=n.baseFont,a.strokeStyle=n.baseColor,a.fillStyle=n.baseColor,a.lineWidth=n.baseLineWidth,a.beginPath(),n.drawBoxes&&a.rect(s.box[0],s.box[1],s.box[2],s.box[3]);let i=[];if(s.genderConfidence&&i.push(`${s.gender||""} ${Math.trunc(100*s.genderConfidence)}% confident`),s.age&&i.push(`age: ${s.age||""}`),s.iris&&i.push(`iris distance: ${s.iris}`),s.emotion&&s.emotion.length>0){let o=s.emotion.map(l=>`${Math.trunc(100*l.score)}% ${l.emotion}`);i.push(o.join(" "))}i.length===0&&i.push("face"),a.fillStyle=n.baseLabel;for(let o=0;o<i.length;o++)a.fillStyle="black",a.fillText(i[o],s.box[0]+1,s.box[1]-(i.length-o)*n.baseLineHeight+6),a.fillStyle=n.baseLabel,a.fillText(i[o],s.box[0]+0,s.box[1]-(i.length-o)*n.baseLineHeight+5);if(a.fillStyle=n.baseColor,a.stroke(),a.lineWidth=1,s.mesh){if(n.drawPoints)for(let o of s.mesh)a.fillStyle=n.useDepth?`rgba(${127.5+2*o[2]}, ${127.5-2*o[2]}, 255, 0.5)`:n.baseColor,a.beginPath(),a.arc(o[0],o[1],2,0,2*Math.PI),a.fill();if(n.drawPolygons){for(let o=0;o<r.length/3;o++){let l=[r[o*3+0],r[o*3+1],r[o*3+2]].map(u=>s.mesh[u]),c=new Path2D;c.moveTo(l[0][0],l[0][1]);for(let u of l)c.lineTo(u[0],u[1]);c.closePath(),a.strokeStyle=n.useDepth?`rgba(${127.5+2*l[0][2]}, ${127.5-2*l[0][2]}, 255, 0.3)`:n.baseColor,a.stroke(c),n.fillPolygons&&(a.fillStyle=n.useDepth?`rgba(${127.5+2*l[0][2]}, ${127.5-2*l[0][2]}, 255, 0.3)`:n.baseColor,a.fill(c))}if(s.annotations&&s.annotations.leftEyeIris){a.strokeStyle=n.useDepth?"rgba(255, 200, 255, 0.3)":n.baseColor,a.beginPath();let o=Math.abs(s.annotations.leftEyeIris[3][0]-s.annotations.leftEyeIris[1][0])/2,l=Math.abs(s.annotations.leftEyeIris[4][1]-s.annotations.leftEyeIris[2][1])/2;a.ellipse(s.annotations.leftEyeIris[0][0],s.annotations.leftEyeIris[0][1],o,l,0,0,2*Math.PI),a.stroke(),n.fillPolygons&&(a.fillStyle=n.useDepth?"rgba(255, 255, 200, 0.3)":n.baseColor,a.fill())}if(s.annotations&&s.annotations.rightEyeIris){a.strokeStyle=n.useDepth?"rgba(255, 200, 255, 0.3)":n.baseColor,a.beginPath();let o=Math.abs(s.annotations.rightEyeIris[3][0]-s.annotations.rightEyeIris[1][0])/2,l=Math.abs(s.annotations.rightEyeIris[4][1]-s.annotations.rightEyeIris[2][1])/2;a.ellipse(s.annotations.rightEyeIris[0][0],s.annotations.rightEyeIris[0][1],o,l,0,0,2*Math.PI),a.stroke(),n.fillPolygons&&(a.fillStyle=n.useDepth?"rgba(255, 255, 200, 0.3)":n.baseColor,a.fill())}}}}}var Ba=[];async function Sae(e,t,n){if(!e)return;let r=t.getContext("2d");r.lineJoin="round";for(let a=0;a<e.length;a++){if(!Ba[a]&&n.buffered&&(Ba[a]={...e[a]}),r.fillStyle=n.baseColor,r.strokeStyle=n.baseColor,r.font=n.baseFont,r.lineWidth=n.baseLineWidth,n.drawPoints)for(let s=0;s<e[a].keypoints.length;s++)r.beginPath(),n.buffered?(Ba[a].keypoints[s].position.x=(Ba[a].keypoints[s].position.x+e[a].keypoints[s].position.x)/2,Ba[a].keypoints[s].position.y=(Ba[a].keypoints[s].position.y+e[a].keypoints[s].position.y)/2,r.arc(Ba[a].keypoints[s].position.x,Ba[a].keypoints[s].position.y,2,0,2*Math.PI)):r.arc(e[a].keypoints[s].position.x,e[a].keypoints[s].position.y,2,0,2*Math.PI),r.fill();if(n.drawPolygons){let s=new Path2D,i,o;i=e[a].keypoints.find(l=>l.part==="leftShoulder"),i&&(s.moveTo(i.position.x,i.position.y),o=e[a].keypoints.find(l=>l.part==="rightShoulder"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="rightHip"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="leftHip"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="leftShoulder"),o&&s.lineTo(o.position.x,o.position.y)),i=e[a].keypoints.find(l=>l.part==="leftHip"),i&&(s.moveTo(i.position.x,i.position.y),o=e[a].keypoints.find(l=>l.part==="leftKnee"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="leftAnkle"),o&&s.lineTo(o.position.x,o.position.y)),i=e[a].keypoints.find(l=>l.part==="rightHip"),i&&(s.moveTo(i.position.x,i.position.y),o=e[a].keypoints.find(l=>l.part==="rightKnee"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="rightAnkle"),o&&s.lineTo(o.position.x,o.position.y)),i=e[a].keypoints.find(l=>l.part==="leftShoulder"),i&&(s.moveTo(i.position.x,i.position.y),o=e[a].keypoints.find(l=>l.part==="leftElbow"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="leftWrist"),o&&s.lineTo(o.position.x,o.position.y)),i=e[a].keypoints.find(l=>l.part==="rightShoulder"),i&&(s.moveTo(i.position.x,i.position.y),o=e[a].keypoints.find(l=>l.part==="rightElbow"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="rightWrist"),o&&s.lineTo(o.position.x,o.position.y)),r.stroke(s)}}}async function Tae(e,t,n){if(!e)return;let r=t.getContext("2d");r.lineJoin="round";for(let a of e){if(r.font=n.baseFont,r.lineWidth=n.baseLineWidth,n.drawBoxes&&(r.lineWidth=n.baseLineWidth,r.beginPath(),r.strokeStyle=n.baseColor,r.fillStyle=n.baseColor,r.rect(a.box[0],a.box[1],a.box[2],a.box[3]),r.fillStyle="black",r.fillText("hand",a.box[0]+3,1+a.box[1]+n.baseLineHeight,a.box[2]),r.fillStyle=n.baseLabel,r.fillText("hand",a.box[0]+2,0+a.box[1]+n.baseLineHeight,a.box[2]),r.stroke()),n.drawPoints&&a.landmarks&&a.landmarks.length>0)for(let s of a.landmarks)r.fillStyle=n.useDepth?`rgba(${127.5+2*s[2]}, ${127.5-2*s[2]}, 255, 0.5)`:n.baseColor,r.beginPath(),r.arc(s[0],s[1],2,0,2*Math.PI),r.fill();if(n.drawPolygons){let s=i=>{if(!!i)for(let o=0;o<i.length;o++)r.lineWidth=n.baseLineWidth,r.beginPath(),r.strokeStyle=n.useDepth?`rgba(${127.5+2*i[o][2]}, ${127.5-2*i[o][2]}, 255, 0.5)`:n.baseColor,r.moveTo(i[o>0?o-1:0][0],i[o>0?o-1:0][1]),r.lineTo(i[o][0],i[o][1]),r.stroke()};s(a.annotations.indexFinger),s(a.annotations.middleFinger),s(a.annotations.ringFinger),s(a.annotations.pinky),s(a.annotations.thumb)}}}var Lc={face:Nae,body:Sae,hand:Tae,gesture:Iae};var Wc=0,Y6=!1,wt={background:"darkslategray",hover:"lightgray",itemBackground:"black",itemColor:"white",buttonBackground:"lightblue",buttonHover:"lightgreen",checkboxOn:"lightgreen",checkboxOff:"lightcoral",rangeBackground:"lightblue",rangeLabel:"white",chartColor:"lightblue"};function Eae(){if(Y6)return;let e=`
:root { --rounded: 0.2rem; }
.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: ${wt.background}; border-radius: var(--rounded); border-color: black; border-style: solid; border-width: thin; }
.menu:hover { box-shadow: 0 0 8px ${wt.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: ${wt.itemBackground}; color: ${wt.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: ${wt.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: ${wt.buttonHover}; box-shadow: 4px 4px 4px 0 black; }
.menu-button:focus { outline: none; }
.menu-checkbox { width: 2.8rem; height: 1rem; background: ${wt.itemBackground}; margin: 0.5rem 0.5rem 0 0; position: relative; border-radius: var(--rounded); }
.menu-checkbox:after { content: 'OFF'; color: ${wt.checkboxOff}; position: absolute; right: 0.2rem; top: -0.4rem; font-weight: 800; font-size: 0.5rem; }
.menu-checkbox:before { content: 'ON'; color: ${wt.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: ${wt.checkboxOff};
border-radius: var(--rounded); transition: left 0.6s ease; }
input[type=checkbox] { visibility: hidden; }
input[type=checkbox]:checked + label { left: 1.4rem; background: ${wt.checkboxOn}; }
.menu-range { margin: 0.2rem 0.5rem 0 0; width: 3.5rem; background: transparent; color: ${wt.rangeBackground}; }
.menu-range:before { color: ${wt.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: ${wt.itemBackground}; border-radius: var(--rounded); border: 1px; }
input[type=range]::-moz-range-track { width: 100%; height: 1rem; cursor: pointer; background: ${wt.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: ${wt.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: ${wt.rangeBackground}; cursor: pointer; -webkit-appearance: none; }
.svg-background { fill:darkslategrey; cursor:pointer; opacity: 0.6; }
.svg-foreground { fill:white; cursor:pointer; opacity: 0.8; }
`,t=document.createElement("style");t.innerHTML=e,document.getElementsByTagName("head")[0].appendChild(t),Y6=!0}var Q6=class{constructor(t,n,r,a){a&&(wt={...wt,...a}),Eae(),this.createMenu(t,n,r),this.id=0,this.instance=Wc,Wc++,this._maxFPS=0,this.hidden=0}createMenu(t,n="",r={top:null,left:null,bottom:null,right:null}){this.menu=document.createElement("div"),this.menu.id=`menu-${Wc}`,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-${Wc}`,this.container.className="menu-container menu-container-fadein";let a=document.createElement("div");a.className="menu-title",a.id=`menu-title-${Wc}`;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",c=>{n[r]=parseInt(c.target.value)===parseFloat(c.target.value)?parseInt(c.target.value):parseFloat(c.target.value),c.target.setAttribute("value",c.target.value),o&&o(c.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&&(wt.chartColor=s);let i=document.createElement("div");return i.className="menu-item menu-chart-title",i.id=this.newID,i.innerHTML=`<font color=${wt.chartColor}>${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=wt.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 c=a.createLinearGradient(0,(i-n[l])*o,0,0);c.addColorStop(.1,wt.chartColor),c.addColorStop(.4,wt.background),a.fillStyle=c,a.fillRect(l*s,0,s-4,r.height),a.fillStyle=wt.background,a.font=`${s/1.5}px "Segoe UI"`,a.fillText(Math.round(n[l]),l*s+1,r.height-1,s-1)}}},Bc=Q6;var Cae=`
#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 7px 0 10px; background: darkslategray; border-radius: 0.2rem; 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; }
`,Rae=`
<div class="gl-box">
<svg viewBox="0 0 55 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="55" 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>
`,ev=class{constructor(t,n={}){this.css=Cae,this.svg=Rae,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(u,h)=>Promise.resolve(setTimeout(()=>{t.getError();let d=this.now()-u;h.forEach((p,f)=>{p&&(this.gpuAccums[f]+=d)})},0)),l=(u,h,d)=>{let p=h.now();u.apply(d,arguments),h.trackGPU&&h.finished.push(o(p,h.activeAccums.slice(0)))},c="drawElements";t[c]?t[c]=l(t[c],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,c,u)=>{let h=["gl-cpu","gl-gpu","gl-mem","gl-fps","gl-gpu-svg","gl-chart"],d={...h};return h.forEach(p=>d[p]=c.getElementsByClassName(p)),this.nodes=d,(p,f,m,A,y,g,w)=>{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=u[p]?u[p]:A?"mem: "+A.toFixed(0)+"mb":"",d["gl-fps"][p].innerHTML="FPS: "+y.toFixed(1),l(u[p],f,m,A,y,g,w)}})(this.paramLogger,this.dom,this.names),this.chartLogger=((l,c)=>{let u={"gl-chart":c.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+" "+(55*A/(m-1)).toFixed(1)+","+(45-d[y]*22/60/this.detected).toFixed(1))}u["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,c=performance&&performance.memory?performance.memory.usedJSHeapSize/(1<<20):0;this.paramLogger(i,o,l,c,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}},tv=ev;var Hr={},se=new J6(Hr),ie={baseColor:"rgba(173, 216, 230, 0.3)",baseBackground:"rgba(50, 50, 50, 1)",baseLabel:"rgba(173, 216, 230, 1)",baseFontProto:'small-caps {size} "Segoe UI"',baseLineWidth:12,crop:!0,columns:2,busy:!1,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",drawBoxes:!0,drawPoints:!1,drawPolygons:!0,fillPolygons:!1,useDepth:!0,console:!0,maxFPSframes:10,modelsPreload:!0,menuWidth:0,menuHeight:0,camera:{},detectFPS:[],drawFPS:[],buffered:!1,drawThread:null,detectThread:null,framesDraw:0,framesDetect:0,bench:!1},xe={},l1,bi,u1={};function Fae(...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 Dn(...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")}`;ie.console&&console.log(n,...e)}function Gn(e){document.getElementById("status").innerText=e}var vi;async function Mae(e){var n,r,a,s;if(document.getElementById("compare-container").style.display=se.config.face.embedding.enabled?"block":"none",!se.config.face.embedding.enabled||((n=e==null?void 0:e.face)==null?void 0:n.length)>0&&((r=e==null?void 0:e.face[0].embedding)==null?void 0:r.length)!==192)return;vi||(vi=e,document.getElementById("compare-canvas").getContext("2d").drawImage(vi.canvas,0,0,200,200));let t=se.simmilarity((a=vi==null?void 0:vi.face[0])==null?void 0:a.embedding,(s=e==null?void 0:e.face[0])==null?void 0:s.embedding);document.getElementById("simmilarity").innerText=`simmilarity: ${Math.trunc(1e3*t)/10}%`}var nv=performance.now();async function c1(e){let t=u1,n=document.getElementById("canvas");ie.drawFPS.push(1e3/(performance.now()-nv)),ie.drawFPS.length>ie.maxFPSframes&&ie.drawFPS.shift(),nv=performance.now(),await xe.process.updateChart("FPS",ie.detectFPS),(ie.buffered||!t.canvas)&&(t.canvas=await se.image(e,Hr));let r=n.getContext("2d");r.fillStyle=ie.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),await Lc.face(t.face,n,ie,se.facemesh.triangulation),await Lc.body(t.body,n,ie),await Lc.hand(t.hand,n,ie),await Lc.gesture(t.gesture,n,ie),await Mae(t);let a=se.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*ie.detectFPS.reduce((h,d)=>h+d,0)/ie.detectFPS.length)/10,c=Math.trunc(10*ie.drawFPS.reduce((h,d)=>h+d,0)/ie.drawFPS.length)/10,u=ie.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: ${ie.camera.name} | facing: ${ie.camera.facing} | screen: ${window.innerWidth} x ${window.innerHeight} camera: ${ie.camera.width} x ${ie.camera.height} ${o}<br>
backend: ${se.tf.getBackend()} | ${i}<br>
performance: ${Fae(t.performance)}ms FPS process:${l} refresh:${c}<br>
${u}<br>
`,ie.framesDraw++,ie.lastFrame=performance.now(),ie.buffered?ie.drawThread=requestAnimationFrame(()=>c1(e,n)):!ie.buffered&&ie.drawThread&&(Dn("stopping buffered refresh"),cancelAnimationFrame(ie.drawThread),ie.drawThread=null)}async function h1(){var c;if(ie.busy)return null;ie.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(Gn("setting up camera"),!navigator.mediaDevices)return a="camera access not supported",n.innerText+=`
${a}`,Dn(a),Gn(a),ie.busy=!1,a;let s,i={audio:!1,video:{facingMode:ie.facing?"user":"environment",resizeMode:ie.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(u){return u.name==="PermissionDeniedError"||u.name==="NotAllowedError"?a="camera permission denied":u.name==="SourceUnavailableError"?a="camera not available":a=`camera error: ${u.message||u}`,n.innerText+=`
${a}`,Gn(a),Dn("camera error:",u),ie.busy=!1,a}if(s)e.srcObject=s;else return ie.busy=!1,"camera stream empty";let o=s.getVideoTracks()[0],l=o.getSettings();return ie.camera={name:(c=o.label)==null?void 0:c.toLowerCase(),width:l.width,height:l.height,facing:l.facingMode==="user"?"front":"back"},new Promise(u=>{e.onloadeddata=async()=>{e.width=e.videoWidth,e.height=e.videoHeight,t.width=e.width,t.height=e.height,t.style.width=t.width>t.height?"100vw":"",t.style.height=t.width>t.height?"":"100vh",ie.menuWidth.input.setAttribute("value",e.width),ie.menuHeight.input.setAttribute("value",e.height);let h=Math.trunc(window.devicePixelRatio*(8+4*t.width/window.innerWidth));ie.baseFont=ie.baseFontProto.replace(/{size}/,`${h}px`),ie.baseLineHeight=h+2,r&&e.play(),r&&!ie.detectThread&&Vc(e,t),ie.busy=!1,Gn(""),u()}})}function rv(){if(!bi){let e=null;bi=new tv(e,{trackGPU:!1,chartHz:20,chartLen:20}),bi.begin()}}function $ae(e,t,n,r){l1||(Dn("creating worker thread"),l1=new Worker(ie.worker,{type:"module"}),l1.addEventListener("message",a=>{a.data.result.performance&&a.data.result.performance.total&&ie.detectFPS.push(1e3/a.data.result.performance.total),ie.detectFPS.length>ie.maxFPSframes&&ie.detectFPS.shift(),ie.bench&&(bi||rv(),bi.nextFrame(r)),document.getElementById("gl-bench")&&(document.getElementById("gl-bench").style.display=ie.bench?"block":"none"),u1=a.data.result,ie.framesDetect++,ie.drawThread||c1(e),ie.detectThread=requestAnimationFrame(s=>Vc(e,n,s))})),l1.postMessage({image:t.data.buffer,width:n.width,height:n.height,userConfig:Hr},[t.data.buffer])}function Vc(e,t,n){var a;if(!(e.srcObject&&e.srcObject.getVideoTracks()[0].readyState==="live"&&e.readyState>2&&!e.paused)&&e.srcObject){ie.drawThread&&cancelAnimationFrame(ie.drawThread),ie.detectThread&&cancelAnimationFrame(ie.detectThread),ie.drawThread=null,ie.detectThread=null,e.paused?Dn("camera paused"):e.srcObject.getVideoTracks()[0].readyState==="live"&&e.readyState<=2?setTimeout(()=>Vc(e,t),500):Dn(`camera not ready: track state: ${(a=e.srcObject)==null?void 0:a.getVideoTracks()[0].readyState} stream state: ${e.readyState}`),clearTimeout(ie.drawThread),ie.drawThread=null,Dn("frame statistics: process:",ie.framesDetect,"refresh:",ie.framesDraw),Dn("memory",se.tf.engine().memory());return}if(Gn(""),ie.useWorker){let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(t.width,t.height):document.createElement("canvas");s.width=t.width,s.height=t.height;let i=s.getContext("2d");i.drawImage(e,0,0,e.width,e.height,0,0,t.width,t.height);let o=i.getImageData(0,0,t.width,t.height);$ae(e,o,t,Hr,n)}else se.detect(e,Hr).then(s=>{s.performance&&s.performance.total&&ie.detectFPS.push(1e3/s.performance.total),ie.detectFPS.length>ie.maxFPSframes&&ie.detectFPS.shift(),ie.bench&&(bi||rv(),bi.nextFrame(n)),document.getElementById("gl-bench")&&(document.getElementById("gl-bench").style.display=ie.bench?"block":"none"),s.error?(Dn(s.error),document.getElementById("log").innerText+=`
Human error: ${s.error}`):(u1=s,ie.drawThread||c1(e),ie.framesDetect++,ie.detectThread=requestAnimationFrame(i=>Vc(e,t,i)))})}async function Dae(e){return new Promise(t=>{let n=new Image;n.onload=async()=>{Dn("Processing image:",n.src);let r=document.getElementById("canvas");n.width=n.naturalWidth,n.height=n.naturalHeight,r.width=se.config.filter.width&&se.config.filter.width>0?se.config.filter.width:n.naturalWidth,r.height=se.config.filter.height&&se.config.filter.height>0?se.config.filter.height:n.naturalHeight,u1=await se.detect(n,Hr),await c1(n);let s=document.createElement("canvas");s.className="thumbnail",s.width=window.innerWidth/(ie.columns+.1),s.height=r.height/(window.innerWidth/s.width),s.getContext("2d").drawImage(r,0,0,r.width,r.height,0,0,s.width,s.height),document.getElementById("samples-container").appendChild(s),n.src="",t(!0)},n.src=e})}async function av(){Hr.videoOptimized=!0,document.getElementById("samples-container").style.display="none",document.getElementById("canvas").style.display="block";let e=document.getElementById("video"),t=document.getElementById("canvas");if(e.srcObject!==null&&!e.paused)document.getElementById("play").style.display="block",document.getElementById("btnStart").className="button button-start",document.getElementById("btnStart").innerHTML="start<br>video",Gn("paused"),e.pause();else{let n=await h1();if(n)Gn(n);else{document.getElementById("play").style.display="none";for(let r of Object.values(xe))r.hide();Gn(""),document.getElementById("btnStart").className="button button-stop",document.getElementById("btnStart").innerHTML="pause<br>video",await e.play(),ie.detectThread||Vc(e,t)}}}async function Oae(){document.getElementById("play").style.display="none",Hr.videoOptimized=!1;let e=Math.trunc(window.devicePixelRatio*(8+4*ie.columns));ie.baseFont=ie.baseFontProto.replace(/{size}/,`${e}px`),ie.baseLineHeight=e+2,document.getElementById("canvas").style.display="none",document.getElementById("samples-container").style.display="block",Dn("Running detection of sample images"),Gn("processing images"),document.getElementById("samples-container").innerHTML="";for(let t of ie.samples)await Dae(t);Gn("")}function zae(){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"],xe.display=new Bc(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[0]}),xe.display.addBool("perf monitor",ie,"bench",t=>ie.bench=t),xe.display.addBool("buffered output",ie,"buffered",t=>ie.buffered=t),xe.display.addBool("crop & scale",ie,"crop",t=>{ie.crop=t,h1()}),xe.display.addBool("camera facing",ie,"facing",t=>{ie.facing=t,h1()}),xe.display.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.display.addBool("use 3D depth",ie,"useDepth"),xe.display.addBool("draw boxes",ie,"drawBoxes"),xe.display.addBool("draw polygons",ie,"drawPolygons"),xe.display.addBool("Fill Polygons",ie,"fillPolygons"),xe.display.addBool("draw points",ie,"drawPoints"),xe.image=new Bc(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[1]}),xe.image.addBool("enabled",se.config.filter,"enabled",t=>se.config.filter.enabled=t),ie.menuWidth=xe.image.addRange("image width",se.config.filter,"width",0,3840,10,t=>se.config.filter.width=parseInt(t)),ie.menuHeight=xe.image.addRange("image height",se.config.filter,"height",0,2160,10,t=>se.config.filter.height=parseInt(t)),xe.image.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.image.addRange("brightness",se.config.filter,"brightness",-1,1,.05,t=>se.config.filter.brightness=parseFloat(t)),xe.image.addRange("contrast",se.config.filter,"contrast",-1,1,.05,t=>se.config.filter.contrast=parseFloat(t)),xe.image.addRange("sharpness",se.config.filter,"sharpness",0,1,.05,t=>se.config.filter.sharpness=parseFloat(t)),xe.image.addRange("blur",se.config.filter,"blur",0,20,1,t=>se.config.filter.blur=parseInt(t)),xe.image.addRange("saturation",se.config.filter,"saturation",-1,1,.05,t=>se.config.filter.saturation=parseFloat(t)),xe.image.addRange("hue",se.config.filter,"hue",0,360,5,t=>se.config.filter.hue=parseInt(t)),xe.image.addRange("pixelate",se.config.filter,"pixelate",0,32,1,t=>se.config.filter.pixelate=parseInt(t)),xe.image.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.image.addBool("negative",se.config.filter,"negative",t=>se.config.filter.negative=t),xe.image.addBool("sepia",se.config.filter,"sepia",t=>se.config.filter.sepia=t),xe.image.addBool("vintage",se.config.filter,"vintage",t=>se.config.filter.vintage=t),xe.image.addBool("kodachrome",se.config.filter,"kodachrome",t=>se.config.filter.kodachrome=t),xe.image.addBool("technicolor",se.config.filter,"technicolor",t=>se.config.filter.technicolor=t),xe.image.addBool("polaroid",se.config.filter,"polaroid",t=>se.config.filter.polaroid=t),xe.process=new Bc(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[2]}),xe.process.addList("backend",["cpu","webgl","wasm","humangl"],se.config.backend,t=>se.config.backend=t),xe.process.addBool("async operations",se.config,"async",t=>se.config.async=t),xe.process.addBool("enable profiler",se.config,"profile",t=>se.config.profile=t),xe.process.addBool("memory shield",se.config,"deallocate",t=>se.config.deallocate=t),xe.process.addBool("use web worker",ie,"useWorker"),xe.process.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.process.addLabel("model parameters"),xe.process.addRange("max objects",se.config.face.detector,"maxFaces",1,50,1,t=>{se.config.face.detector.maxFaces=parseInt(t),se.config.body.maxDetections=parseInt(t),se.config.hand.maxHands=parseInt(t)}),xe.process.addRange("skip frames",se.config.face.detector,"skipFrames",0,50,1,t=>{se.config.face.detector.skipFrames=parseInt(t),se.config.face.emotion.skipFrames=parseInt(t),se.config.face.age.skipFrames=parseInt(t),se.config.hand.skipFrames=parseInt(t)}),xe.process.addRange("min confidence",se.config.face.detector,"minConfidence",0,1,.05,t=>{se.config.face.detector.minConfidence=parseFloat(t),se.config.face.gender.minConfidence=parseFloat(t),se.config.face.emotion.minConfidence=parseFloat(t),se.config.hand.minConfidence=parseFloat(t)}),xe.process.addRange("score threshold",se.config.face.detector,"scoreThreshold",.1,1,.05,t=>{se.config.face.detector.scoreThreshold=parseFloat(t),se.config.hand.scoreThreshold=parseFloat(t),se.config.body.scoreThreshold=parseFloat(t)}),xe.process.addRange("overlap",se.config.face.detector,"iouThreshold",.1,1,.05,t=>{se.config.face.detector.iouThreshold=parseFloat(t),se.config.hand.iouThreshold=parseFloat(t)}),xe.process.addBool("detection rotation",se.config.face.detector,"rotation",t=>{se.config.face.detector.rotation=t,se.config.hand.rotation=t}),xe.process.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.process.addButton("process sample images","process images",()=>Oae()),xe.process.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.process.addChart("FPS","FPS"),xe.models=new Bc(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[3]}),xe.models.addBool("face detect",se.config.face,"enabled",t=>se.config.face.enabled=t),xe.models.addBool("face mesh",se.config.face.mesh,"enabled",t=>se.config.face.mesh.enabled=t),xe.models.addBool("face iris",se.config.face.iris,"enabled",t=>se.config.face.iris.enabled=t),xe.models.addBool("face age",se.config.face.age,"enabled",t=>se.config.face.age.enabled=t),xe.models.addBool("face gender",se.config.face.gender,"enabled",t=>se.config.face.gender.enabled=t),xe.models.addBool("face emotion",se.config.face.emotion,"enabled",t=>se.config.face.emotion.enabled=t),xe.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.models.addBool("body pose",se.config.body,"enabled",t=>se.config.body.enabled=t),xe.models.addBool("hand pose",se.config.hand,"enabled",t=>se.config.hand.enabled=t),xe.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.models.addBool("gestures",se.config.gesture,"enabled",t=>se.config.gesture.enabled=t),xe.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.models.addBool("face compare",se.config.face.embedding,"enabled",t=>{se.config.face.embedding.enabled=t,vi=null}),document.getElementById("btnDisplay").addEventListener("click",t=>xe.display.toggle(t)),document.getElementById("btnImage").addEventListener("click",t=>xe.image.toggle(t)),document.getElementById("btnProcess").addEventListener("click",t=>xe.process.toggle(t)),document.getElementById("btnModel").addEventListener("click",t=>xe.models.toggle(t)),document.getElementById("btnStart").addEventListener("click",()=>av()),document.getElementById("play").addEventListener("click",()=>av())}async function Pae(){Dn("Demo starting ..."),Dn("Browser:",navigator==null?void 0:navigator.userAgent),zae(),document.getElementById("log").innerText=`Human: version ${se.version}`,ie.modelsPreload&&!ie.useWorker&&(Gn("loading"),await se.load(Hr)),ie.useWorker||(Gn("initializing"),await se.warmup(Hr)),Gn("human: ready"),document.getElementById("loader").style.display="none",document.getElementById("play").style.display="block",Dn("Demo ready...")}window.onload=Pae;window.onresize=h1;
/**
* @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
Reference in New Issue View Git Blame Copy Permalink