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i=C(e,"forgetBias","basicLSTMCell"),o=C(t,"lstmKernel","basicLSTMCell"),l=C(n,"lstmBias","basicLSTMCell"),c=C(r,"data","basicLSTMCell"),u=C(a,"c","basicLSTMCell"),h=C(s,"h","basicLSTMCell"),d=rt([c,h],1),p=Ge(d,o),f=se(p,l),m=f.shape[0],A=f.shape[1]/4,y=[m,A],g=Ee(f,[0,0],y),w=Ee(f,[0,A],y),b=Ee(f,[0,A*2],y),_=Ee(f,[0,A*3],y),x=se(P($n(g),dl(w)),P(u,$n(se(i,b)))),N=P(dl(x),$n(_));return[x,N]}var NS=O({basicLSTMCell_:IS});function SS(e,t,n){let r=C(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 D.runKernel(gu,s,i)}var qu=O({batchToSpaceND_:SS});function TS(e){let t;return e.rank===0||e.rank===1?t=H(e,[1,1,1,e.size]):e.rank===2?t=H(e,[1,1,e.shape[0],e.shape[1]]):e.rank===3?t=H(e,[1,e.shape[0],e.shape[1],e.shape[2]]):t=e,t}function ES(e,t,n,r,a,s){s==null&&(s=.001);let i=C(e,"x","batchNorm"),o=C(t,"mean","batchNorm"),l=C(n,"variance","batchNorm"),c;a!=null&&(c=C(a,"scale","batchNorm"));let u;r!=null&&(u=C(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:TS(i),scale:c,offset:u,mean:o,variance:l},d={varianceEpsilon:s},p=D.runKernel(Is,h,d);return H(p,i.shape)}var pi=O({batchNorm_:ES});function CS(e,t,n,r,a,s){let i=C(e,"x","batchNorm"),o=C(t,"mean","batchNorm"),l=C(n,"variance","batchNorm"),c;a!=null&&(c=C(a,"scale","batchNorm"));let u;return r!=null&&(u=C(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}.`),pi(i,o,l,u,c,s)}var zw=O({batchNorm2d_:CS});function RS(e,t,n,r,a,s){let i=C(e,"x","batchNorm"),o=C(t,"mean","batchNorm"),l=C(n,"variance","batchNorm"),c;a!=null&&(c=C(a,"scale","batchNorm"));let u;return r!=null&&(u=C(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}.`),pi(i,o,l,u,c,s)}var Pw=O({batchNorm3d_:RS});function MS(e,t,n,r,a,s){let i=C(e,"x","batchNorm"),o=C(t,"mean","batchNorm"),l=C(n,"variance","batchNorm"),c;a!=null&&(c=C(a,"scale","batchNorm"));let u;return r!=null&&(u=C(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}.`),pi(i,o,l,u,c,s)}var Lw=O({batchNorm4d_:MS});function FS(e,t,n){let r=C(e,"x","bincount"),a=C(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: ${a.shape}.`);let s={x:r,weights:a},i={size:n};return D.runKernel(Dh,s,i)}var Ww=O({bincount_:FS});function DS(e,t){let n=C(e,"broadcastTo","x"),r=n.shape;if(t.some(l=>!(l>0)||l%1!=0))throw new Error(`broadcastTo(): Invalid broadcast shape [${t}].`);if(t.lengthn.rank){let l=n.shape.slice();for(;l.length=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 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i=C(e,"x","dilation2d"),o=C(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=H(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=D.runKernel(bu,u,h);return c?H(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var dm=O({dilation2d_:rT});function aT(e,t){let n=e.length,r=[];for(let a=0;a1&&i===1&&r.unshift(s)}return r}function zt(e,t){let n=[];for(let r=0;r1)&&n.unshift(s)}return n}function At(e,t){let n=[],r=Math.max(e.length,t.length);for(let a=0;a"The first dimension of `a` must match the size of `condition`."),s.rank!==1&&rn(s.shape,l.shape,"Error in where: ");let c={condition:s,t:o,e:l};return D.runKernel(jo,c)}var Nn=O({where_:iT});function 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D.runKernel(mo,t)}var ml=O({elu_:cT});function hT(e){let t=C(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 D.runKernel(Ao,n)}var fm=O({erf_:hT});function dT(e){let t={x:C(e,"x","exp")};return D.runKernel(_s,t)}var Qn=O({exp_:dT});function pT(e,t=0){let n=C(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 D.runKernel(go,r,a)}var Qt=O({expandDims_:pT});function fT(e){let t={x:C(e,"x","expm1")};return D.runKernel(xo,t)}var mm=O({expm1_:fT});function mT(e,t){let n=C(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 D.runKernel(Ra,r,a)}var Wa=O({tile_:mT});function AT(e,t,n,r="float32"){t==null&&(t=e);let a=Be([e,t],r),s=e<=t?e:t;for(let o=0;o`Error in localResponseNormalization: x must 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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=R.computeOutShape(c.map(m=>m.shape),1);let h=c[0].shape[0]===1,d=jm(u,i,t[0].dtype,h),p=R.computeOutShape(o.map(m=>m.shape),s),f=n.makeTensorInfo(p,t[0].dtype,d);return c.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var SD={kernelName:co,backendName:"cpu",kernelFunc:Sl};function h_(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=R.convertConv2DDataFormat(l),d=R.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",b=new $t(d.outShape,a.dtype),_=v.computeStrides(a.shape),x=v.computeStrides(s.shape),N=_[0],T=w?_[1]:_[2],E=w?_[2]:1,F=w?1:_[1],$=b.strides[0],L=w?b.strides[1]:b.strides[2],V=w?b.strides[2]:1,j=w?1:b.strides[1],U=n.data.get(a.dataId).values,X=n.data.get(s.dataId).values,G=b.values;for(let ee=0;ee=d.inHeight)continue;let fe=he*x[0],pe=Y+oe*T;for(let ke=0;ke=d.inWidth)continue;let Qe=fe+Oe*x[1],et=pe+De*E,st=Qe;for(let Ke=0;Ke=c.inDepth)continue;let ee=X*E[0],Y=$+G*T[1];for(let ae=0;ae=c.inHeight)continue;let oe=ee+Q*E[1],fe=Y+he*T[2];for(let pe=0;pe=c.inWidth)continue;let De=oe+Fe*E[2],Qe=fe+Oe*c.inChannels,et=De;for(let st=0;stMath.cos(e)),WD={kernelName:gs,backendName:"cpu",kernelFunc:LD},BD=at(ho,e=>Math.cosh(e)),VD={kernelName:ho,backendName:"cpu",kernelFunc:BD};function 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M$(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=h_({inputs:{x:a,filter:s},backend:n,attrs:{strides:l,pad:c,dataFormat:u,dilations:h,dimRoundingMode:d}});if(i){let A=m;m=lc({inputs:{a:m,b:i},backend:n}),n.disposeIntermediateTensorInfo(A)}if(p){let A=m;m=Zm(n,m,p,o,f),n.disposeIntermediateTensorInfo(A)}return m}var F$={kernelName:ri,backendName:"cpu",kernelFunc:M$};function D$(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=d_({inputs:{x:a,filter:s},backend:n,attrs:{strides:l,pad:c,dataFormat:u,dilations:h,dimRoundingMode:d}});if(i){let A=m;m=lc({inputs:{a:m,b:i},backend:n}),n.disposeIntermediateTensorInfo(A)}if(p){let A=m;m=Zm(n,m,p,o,f),n.disposeIntermediateTensorInfo(A)}return m}var $$={kernelName:ai,backendName:"cpu",kernelFunc:D$};function O$(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]=R.prepareAndValidate(r,a);if(c===0)return n.makeTensorInfo(l,r.dtype,[]);let d=Be([c,u],r.dtype),p=n.data.get(a.dataId).values,f=n.data.get(r.dataId).values;for(let m=0;m=s/u)throw new Error(`Invalid indices: ${A} does not index into ${r.shape}`);for(let g=0;ge>=t?1:0),B$=Ht(Ns,W$,null,"bool"),V$={kernelName:Ns,backendName:"cpu",kernelFunc:B$};function j$(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=f_(o,!0,n),c=yt({inputs:{x:l},backend:n,attrs:{shape:r.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(l),c}var U$={kernelName:qh,backendName:"cpu",kernelFunc:j$},H$=at(ko,e=>Number.isFinite(e)?1:0,"bool"),G$={kernelName:ko,backendName:"cpu",kernelFunc:H$},q$=at(Io,e=>Math.abs(e)===Infinity?1:0,"bool"),X$={kernelName:Io,backendName:"cpu",kernelFunc:q$},K$=at(No,e=>Number.isNaN(e)?1:0,"bool"),Z$={kernelName:No,backendName:"cpu",kernelFunc:K$},Y$=Rt((e,t)=>e<=t?1:0),J$=Ht(To,Y$,null,"bool"),Q$={kernelName:To,backendName:"cpu",kernelFunc:J$};function eO(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=Wb(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var tO={kernelName:Kh,backendName:"cpu",kernelFunc:eO},nO=at(Eo,e=>Math.log1p(e)),rO={kernelName:Eo,backendName:"cpu",kernelFunc:nO},aO=Rt((e,t)=>e&&t),sO=Ht(Co,aO,null,"bool"),iO={kernelName:Co,backendName:"cpu",kernelFunc:sO},oO=at(vu,e=>e?0:1,"bool"),lO={kernelName:vu,backendName:"cpu",kernelFunc:oO},uO=Rt((e,t)=>e||t),cO=Ht(ku,uO,null,"bool"),hO={kernelName:ku,backendName:"cpu",kernelFunc:cO};function dO(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 b=h[y];w+=b*b}return w}for(let m=0;m`Error in maxPool: Either strides or dilations must be 1. 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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 Dl(r,yp):p=new Ha(r,yp);let f=this.runWebGLProgram(p,[{dataId:e,shape:r,dtype:s}],s),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(!J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&J().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,c;if(s!=="complex64"&&J().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(e);let p=this.texData.get(c.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...mc(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=R.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)&&Lr().removeDataId(e,this),this.pendingDeletes--),h}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(r=>v.decodeString(r))}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return Be(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t0}async time(e){let t=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,e();let a=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,r&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(a);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,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 J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:r,usage:a,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(t,r,a,s)));let 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 J().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=Lr().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=NW){let n=this.getCPUBackend();return!J().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&n==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."),this.warnedAboutCPUBackend=!0),n!=null&&e.every(r=>this.texData.get(r.dataId).texture==null&&v.sizeFromShape(r.shape)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 Lr().makeTensorFromDataId(r,e,t,this)}unpackTensor(e){let t=new bW(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new iW(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[_i(e.shape),...vi(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},a=[_i(t),...vi(t)],s=new x3(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=hp(r),i;n?i=new LP(s):i=new PP(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===pc.DENSE){let m=mc(e.outputShape);i.texShape=m.map(A=>A*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),v.sizeFromShape(s.shape)===0)return i.values=v.getTypedArrayFromDType(s.dtype,0),s;let o=[],l=t.map(m=>{if(m.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let A=this.texData.get(m.dataId);if(A.texture==null){if(!e.packedInputs&&v.sizeFromShape(m.shape)<=J().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:m.shape,texData:null,isUniform:!0,uniformValues:A.values};e.packedInputs&&(A.isPacked=!0,A.shape=m.shape)}else if(!!A.isPacked!=!!e.packedInputs)m=A.isPacked?this.unpackTensor(m):this.packTensor(m),o.push(m),A=this.texData.get(m.dataId);else if(A.isPacked&&!dc(A.shape,m.shape)){let y=m,g=m.shape;m.shape=A.shape,m=this.packedReshape(m,g),o.push(m),A=this.texData.get(m.dataId),y.shape=g}return this.uploadToGPU(m.dataId),{shape:m.shape,texData:A,isUniform:!1}});this.uploadToGPU(s.dataId);let c={shape:s.shape,texData:i,isUniform:!1},u=EL(e,l,c),h=this.getAndSaveBinary(u,()=>SL(this.gpgpu,e,l,c)),d=this.activeTimers!=null,p;d&&(p=this.startTimer()),TL(this.gpgpu,h,l,c,r),o.forEach(m=>this.disposeIntermediateTensorInfo(m)),d&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)}));let f=J().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let m=v.now();m-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=m)}if(!J().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&a===!1){let m=this.unpackTensor(s);return this.disposeIntermediateTensorInfo(s),m}return s}compileAndRun(e,t,n,r,a=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,r,a)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(J().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=z(()=>{if(!J().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=J().getBool("DEBUG");J().set("DEBUG",!1);let t=this.abs(ge(1e-8)).dataSync()[0];if(J().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?vW:kW}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=W_(n,o),t.texShape=u),a!=null){let h=hp(n),d,p=u[1],f=u[0],m=a instanceof Uint8Array;o?([p,f]=El(u[0],u[1]),d=new jP(h,[f,p],m)):d=new VP(h,[f,p],m);let A=this.makeTensorInfo([f,p],r);m?this.texData.get(A.dataId).usage=tr.PIXELS:this.texData.get(A.dataId).usage=tr.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(A.dataId),p,f,a);let y=!0,g=this.runWebGLProgram(d,[A],r,null,y),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=EW(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: ${a} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,r)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}};$l.nextDataId=0;function EW(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;rnew $l,2);var CW={forceHalfFloat:I3},N3=` if (isnan(a)) return a; if (isnan(b)) return b; `,Ol=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=` float binaryOperation(float a, float b) { ${e} } void main() { float a = getAAtOutCoords(); float b = getBAtOutCoords(); setOutput(binaryOperation(a, b)); } `}},gp=` result.r = isNaN.r > 0. ? NAN : result.r; result.g = isNaN.g > 0. ? NAN : result.g; result.b = isNaN.b > 0. ? NAN : result.b; result.a = isNaN.a > 0. ? NAN : result.a; `,yc=class{constructor(e,t,n,r=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=R.assertAndGetBroadcastShape(t,n);let a=this.outputShape.length,s="";if(r)if(a===0||v.sizeFromShape(this.outputShape)===1)s=` result.y = 0.; result.z = 0.; result.w = 0.; `;else if(s=` ${ot(a)} coords = getOutputCoords(); `,a===1)s+=` result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y; result.z = 0.; result.w = 0.; `;else{let i=pn("coords",a);s+=` bool nextRowOutOfBounds = (${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); ${s} setOutput(result); } `}};function Wn(e){let{inputs:t,backend:n}=e,{x:r}=t;return n.incRef(r.dataId),{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}var RW={kernelName:Ss,backendName:"webgl",kernelFunc:Wn};function Ga(e){let{inputs:t,backend:n}=e,{real:r,imag:a}=t,s=n.makeTensorInfo(r.shape,"complex64"),i=n.texData.get(s.dataId),o=Wn({inputs:{x:r},backend:n}),l=Wn({inputs:{x:a},backend:n});return i.complexTensorInfos={real:o,imag:l},s}var MW={kernelName:$h,backendName:"webgl",kernelFunc:Ga},S3="return (a < 0.) ? b * a : a;",T3=` vec4 aLessThanZero = vec4(lessThan(a, vec4(0.))); return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a); `;function FW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{alpha:s}=r,i=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new yc(T3,a.shape,i.shape):new Ol(S3,a.shape,i.shape),l=n.runWebGLProgram(o,[a,i],a.dtype);return n.disposeIntermediateTensorInfo(i),l}var DW={kernelName:Ts,backendName:"webgl",kernelFunc:FW},E3="return (a < 0.) ? b * a : a;",C3=` vec4 aLessThanZero = vec4(lessThan(a, vec4(0.))); return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a); `;function $W(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new yc(C3,r.shape,a.shape):new Ol(E3,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)}var OW={kernelName:Ws,backendName:"webgl",kernelFunc:$W},R3="if (isnan(x)) return x;",zW=` if (isnan(a)) return a; if (isnan(b)) return b; `,PW=` 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 Xe({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=J().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,u;return c?u=new Dl(i.shape,t):u=new Ha(i.shape,e),o.runWebGLProgram(u,[i],l)}}function nn({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[b,_]=w,x={dataId:b.dataId,dtype:b.dtype,shape:l.shape},N={dataId:_.dataId,dtype:_.dtype,shape:c.shape},T=new Ol(e,l.shape,c.shape);return u.runWebGLProgram(T,[x,N],ur(b.dtype,_.dtype))}),g=Ga({inputs:{real:A,imag:y},backend:u});return u.disposeIntermediateTensorInfo(A),u.disposeIntermediateTensorInfo(y),g}let h=s||ur(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=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return d?p=new yc(t,l.shape,c.shape,n):p=new Ol(e,l.shape,c.shape),u.runWebGLProgram(p,[l,c],h)}}function xp(e,t=!1){if(e==="linear")return t?yW:pW;if(e==="relu")return t?xW:mW;if(e==="elu")return t?gW:fW;if(e==="relu6")return t?wW:AW;if(e==="prelu")return t?C3:E3;if(e==="leakyrelu")return t?T3:S3;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var M3=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) { ${i} }`,A="result = activation(result);");let y=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let g="rc.x",w="rc.x";e[0]`The new shape (${l}) has ${c} elements and the old shape (${a.shape}) has ${o} elements. 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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 ${i} bestValue) { bestValue = candidate; bestIndex = inIdx; } } setOutput(float(bestIndex)); } `}},AB=class{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${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=ot(o),c=pn("coords",o),u,h;if(s===1){h=o+1;let N=ot(h);u=` ${N} sourceLocR = ${N}(${c.join()}, 0); ++${c[o-1]}; ${N} sourceLocG = ${N}(${c.join()}, 0); ++${c[o-2]}; ${N} sourceLocA = ${N}(${c.join()}, 0); --${c[o-1]}; ${N} sourceLocB = ${N}(${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(N=>"int "+N),m=pn("sourceLocR",h-1).concat("inIdx.r"),A=pn("sourceLocG",h-1).concat("inIdx.g"),y=pn("sourceLocB",h-1).concat("inIdx.b"),g=pn("sourceLocA",h-1).concat("inIdx.a"),w=n==="max"?"greaterThan":"lessThan",b=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.)`,x=r?"":` float getBestIndicesAChannel(${f.join()}) { return getChannel(getBestIndicesA(${d.join()}), vec2(${d.slice(-2).join()})); }`;this.userCode=` float getAChannel(${f.join()}) { return getChannel(getA(${d.join()}), vec2(${d.slice(-2).join()})); } ${x} void main() { ${l} coords = getOutputCoords(); bool hasNextCol = ${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; ${b} 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 B3(e,t,n,r=null){let a=t.shape[0],s=t.shape[1];r!=null&&(a=r.shape[0],s=r.shape[1]);let i=R.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new mB(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=B3(e,t,n,u);return e.disposeIntermediateTensorInfo(u),h}function V3(e,t,n,r=null){let a=r!=null?r.shape:t.shape,s=a[a.length-1],i=R.computeOptimalWindowSize(s),o=new AB(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=V3(e,t,n,c);return e.disposeIntermediateTensorInfo(c),u}return c}function j3(e,t,n,r){let a=[n];if(R.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),a,t.shape.length),!J().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],[i,o]=R.computeOutAndReduceShapes(t.shape,a),l=v.sizeFromShape(o),c=xe({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});s.push(c);let u=B3(e,c,r);s.push(u);let h=xe({inputs:{x:u},backend:e,attrs:{shape:i}});return s.forEach(d=>e.disposeIntermediateTensorInfo(d)),h}return V3(e,t,r)}function yB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=En({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let u=j3(n,l,i[0],"max");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var gB={kernelName:hs,backendName:"webgl",kernelFunc:yB};function xB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=En({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let u=j3(n,l,i[0],"min");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var wB={kernelName:Au,backendName:"webgl",kernelFunc:xB},bB=Nr+` if (abs(x) > 1.) { return NAN; } return asin(x); `,_B=Xe({opSnippet:bB}),vB={kernelName:so,backendName:"webgl",kernelFunc:_B},kB=Nr+"return log(x + sqrt(x * x + 1.0));",IB=Xe({opSnippet:kB}),NB={kernelName:io,backendName:"webgl",kernelFunc:IB},SB=Nr+` return atan(x); `,TB=Xe({opSnippet:SB}),EB={kernelName:oo,backendName:"webgl",kernelFunc:TB},CB=zW+` return atan(a, b); `,RB=` vec4 result = atan(a, b); vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0)); `+PW+` return result; `,MB=nn({opSnippet:CB,packedOpSnippet:RB}),FB={kernelName:uo,backendName:"webgl",kernelFunc:MB},DB=Nr+` if ((x < -1.0) || (x > 1.0)) return NAN; return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,$B=Xe({opSnippet:DB}),OB={kernelName:lo,backendName:"webgl",kernelFunc:$B},gc=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) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let N=">=";this.userCode=` const ivec2 strides = ivec2(${i}, ${o}); const ivec2 pads = ivec2(${d}, ${p}); void main() { ivec4 coords = getOutputCoords(); int batch = coords[0]; int d = coords[3]; ivec2 xRCCorner = coords.yz * strides - pads; int xRCorner = xRCCorner.x; int xCCorner = xRCCorner.y; // max/min x(?, ?, d) to get y(yR, yC, d). // ? = to be determined float minMaxValue = 0.0; float minMaxValueFound = 0.0; int minMaxPosition = 0; float avgValue = 0.0; for (int wR = 0; wR < ${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 ${N} 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 b=Math.floor(s/4)*4,_=s%4,x=` if (${f}) { avgValue += dot(values, ones); } else { minMaxValue = ${g}(values, minMaxValue); } `;this.userCode=` const ivec2 strides = ivec2(${i}, ${o}); const ivec2 pads = ivec2(${d}, ${p}); const float initializationValue = ${y}; const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0); float count = 0.0; float getValue(int batch, int xR, int xC, int d) { if (xC < 0 || xC >= ${e.inWidth}) { return initializationValue; } count += 1.0; return getX(batch, xR, xC, d); } void main() { ivec4 coords = getOutputCoords(); int batch = coords[0]; int d = coords[3]; ivec2 xRCCorner = coords.yz * strides - pads; int xRCorner = xRCCorner.x; int xCCorner = xRCCorner.y; // max/min x(?, ?, d) to get y(yR, yC, d). // ? = to be determined vec4 minMaxValue = vec4(${y}); float avgValue = 0.0; count = 0.0; for (int wR = 0; wR < ${u}; wR += ${l}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC < ${b}; wC += 4) { int xC = xCCorner + wC * ${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) ); ${x} } int xC = xCCorner + ${b}; if (${_===1}) { vec4 values = vec4( getValue(batch, xR, xC, d), initializationValue, initializationValue, initializationValue ); ${x} } else if (${_===2}) { vec4 values = vec4( getValue(batch, xR, xC, d), getValue(batch, xR, xC + ${c}, d), initializationValue, initializationValue ); ${x} } else if (${_===3}) { vec4 values = vec4( getValue(batch, xR, xC, d), getValue(batch, xR, xC + ${c}, d), getValue(batch, xR, xC + 2 * ${c}, d), initializationValue ); ${x} } } setOutput(${w}); } `}},yA=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,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 E=">=";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 ${E} 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 * ${f} + wC`}; } } } } setOutput(float(minMaxPosition)); } `;return}let b="max",_=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(_="avgValue / count");let x=Math.floor(s/4)*4,N=s%4,T=` if (${g}) { avgValue += dot(values, ones); } else { minMaxValue = ${b}(values, minMaxValue); } `;this.userCode=` const ivec3 strides = ivec3(${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 < ${x}; wC += 4) { int xC = xCCorner + wC * ${h}; vec4 values = vec4( getValue(batch, xD, xR, xC, ch), getValue(batch, xD, xR, xC + ${h}, ch), getValue(batch, xD, xR, xC + 2 * ${h}, ch), getValue(batch, xD, xR, xC + 3 * ${h}, ch) ); ${T} } int xC = xCCorner + ${x}; if (${N===1}) { vec4 values = vec4( getValue(batch, xD, xR, xC, ch), initializationValue, initializationValue, initializationValue ); ${T} } else if (${N===2}) { vec4 values = vec4( getValue(batch, xD, xR, xC, ch), getValue(batch, xD, xR, xC + ${h}, ch), initializationValue, initializationValue ); ${T} } else if (${N===3}) { vec4 values = vec4( getValue(batch, xD, xR, xC, ch), getValue(batch, xD, xR, xC + ${h}, ch), getValue(batch, xD, xR, xC + 2 * ${h}, ch), initializationValue ); ${T} } } setOutput(${_}); } } `}};function zB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;Tl(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=R.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return Wn({inputs:{x:a},backend:n});let h=new gc(u,"avg",!1);return n.runWebGLProgram(h,[a],"float32")}var PB={kernelName:ds,backendName:"webgl",kernelFunc:zB};function LB(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=R.computePool3DInfo(a.shape,s,i,u,o,l,c),d=new yA(h,"avg",!1);return n.runWebGLProgram(d,[a],"float32")}var WB={kernelName:yu,backendName:"webgl",kernelFunc:LB},BB=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 >= ${e.outWidth}.0 || fract(dyC) > 0.0) { continue; } int idyC = int(dyC); float dyValue = getDy(b, idyR, idyC, d); dotProd += dyValue * avgMultiplier; } } setOutput(dotProd); } `}},VB=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.effectiveFilterDepth,h=e.effectiveFilterHeight,d=e.effectiveFilterWidth,p=u-1-e.padInfo.front,f=h-1-e.padInfo.top,m=d-1-e.padInfo.left,A=1/(t*n*r);this.userCode=` const ivec3 pads = ivec3(${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 jB(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=R.computePool3DInfo(i.shape,o,l,h,c,u),p=new VB(d);return n.runWebGLProgram(p,[a],i.dtype)}var UB={kernelName:Fh,backendName:"webgl",kernelFunc:jB};function HB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;Tl([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:c}=r,u=R.computePool2DInfo(i.shape,o,l,1,c),h=new BB(u);return n.runWebGLProgram(h,[a],i.dtype)}var GB={kernelName:Mh,backendName:"webgl",kernelFunc:HB};function qB(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;return bp({a,b:s,transposeA:i,transposeB:o,backend:n})}var XB={kernelName:ps,backendName:"webgl",kernelFunc:qB},KB=class{constructor(e,t,n,r,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="0.0";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=` void main() { float x = getXAtOutCoords(); float mean = getMeanAtOutCoords(); float variance = getVarianceAtOutCoords(); float offset = ${i}; float scale = ${o}; float inv = scale * inversesqrt(variance + float(${s})); setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1))); } `}},ZB=class{constructor(e,t,n,r,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=` void main() { vec4 offset = ${i}; vec4 scale = ${o}; vec4 x = getXAtOutCoords(); vec4 mean = getMeanAtOutCoords(); vec4 variance = getVarianceAtOutCoords(); vec4 inv = scale * inversesqrt(variance + vec4(${s})); setOutput((x - mean) * inv + offset); } `}},YB=({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=J().getBool("WEBGL_PACK_NORMALIZATION")?new ZB(r.shape,a.shape,s.shape,u,h,l):new KB(r.shape,a.shape,s.shape,u,h,l);return t.runWebGLProgram(d,c,c[0].dtype)},JB={kernelName:Is,backendName:"webgl",kernelFunc:YB},eV=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ot(this.rank),n=`uniform int start[${this.rank}];`,r=QB(this.rank),a,s=e.map((i,o)=>`sourceLoc.${gA[o]} = start[${o}] + coords.${gA[o]};`);a=` ${t} sourceLoc; 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${n} }`:a?w=`float activation(float a) { float b = getLeakyreluAlphaAtOutCoords(); ${n} }`:w=` float activation(float x) { ${n} } `,b="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; ${_} ${b} setOutput(result); } `}},SV=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.filterDepth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=` const ivec3 strides = ivec3(${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); } `}},TV=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=dn(),A=h==="channelsLast",y=A?0:1,g=A?1:2,w="";for(let b=0;b<=1;b++)for(let _=0;_<=1;_++)w+=` blockIndex = rc.y + ${_}; pos = rc.x + ${b}; 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[${b*2+_}] = getChannel( getA(d0, int(innerDims.x), int(innerDims.y)), innerDims); } else { innerDims = vec2(d0, d1); result[${b*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 Z3({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>P3,w=l[2]%2!=0&&!!c.isPacked;if(g||!J().getBool("WEBGL_LAZILY_UNPACK")||!J().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!w){let b=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],_=xe({inputs:{x:e},backend:r,attrs:{shape:[1,b,n.inChannels]}}),x=xe({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),N=bp({a:_,b:x,transposeA:f,transposeB:m,backend:r,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});A=xe({inputs:{x:N},backend:r,attrs:{shape:n.outShape}}),y.push(_),y.push(x),y.push(N)}else{let b=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),_={dataId:e.dataId,shape:[1,b,n.inChannels],dtype:e.dtype},x=c.shape;c.shape=c.shape.slice(),c.shape[c.shape.length-2]++,v.assert(dc(c.shape,_.shape),()=>`packed reshape ${c.shape} to ${_.shape} isn't free`);let N=xe({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(N);let T=bp({a:_,b:N,backend:r,transposeA:f,transposeB:m,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),E=r.texData.get(T.dataId);v.assert(E.isPacked,()=>"batchMatMul result is expected to be packed"),c.shape=x,E.shape=n.outShape,A=Wn({inputs:{x:T},backend:r}),A.shape=n.outShape,y.push(T)}for(let b of y)r.disposeIntermediateTensorInfo(b);return A}function Y3({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:c,inChannels:u,outWidth:h,outHeight:d,dataFormat:p}=n,f=p==="channelsLast",m=l*c*u,A=d*h,y=[m,A],g=!0,w=!1,b=[],_=xe({inputs:{x:e},backend:r,attrs:{shape:e.shape.slice(1)}}),x=xe({inputs:{x:t},backend:r,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});b.push(_),b.push(x);let N=new TV(y,_.shape,n),T=r.runWebGLProgram(N,[_],"float32"),E=xe({inputs:{x:T},backend:r,attrs:{shape:[1,y[0],y[1]]}});b.push(T),b.push(E);let F=a!=null,$=s!=null,L=o==="leakyrelu",V=o?xp(o,!0):null,j=new M3(E.shape,x.shape,[1,A,n.outChannels],g,w,F,V,$,L),U=[E,x];if(a&&U.push(a),$&&U.push(s),L){let Y=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));U.push(Y),b.push(Y)}let X=r.runWebGLProgram(j,U,"float32"),G=f?[1,d,h,n.outChannels]:[1,n.outChannels,d,h],ee=xe({inputs:{x:X},backend:r,attrs:{shape:G}});b.push(X);for(let Y of b)r.disposeIntermediateTensorInfo(Y);return ee}function EV(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=R.convertConv2DDataFormat(l),d=R.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=Z3({x:a,filter:s,convInfo:d,backend:n});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)p=Y3({x:a,filter:s,convInfo:d,backend:n});else{let m=new K3(d);p=n.runWebGLProgram(m,[a,s],"float32")}let f=xe({inputs:{x:p},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(p),f}var CV={kernelName:As,backendName:"webgl",kernelFunc:EV},RV=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); } `}},MV=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=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); } `}},FV=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 >= ${e.inWidth}) { continue; } float dyValue = getDy(b, yF, yR, yC, d2); float xValue = getX(b, xF, xR, xC, d1); dotProd += (xValue * dyValue); } } } } setOutput(dotProd); } `}},DV=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,c=r-1-e.padInfo.left;this.userCode=` const ivec3 pads = ivec3(${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 $V(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:c,filterShape:u}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,u,i,1,o,c,!1,h),p=new RV(d);return n.runWebGLProgram(p,[a,s],"float32")}var OV={kernelName:Oh,backendName:"webgl",kernelFunc:$V};function zV(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=R.convertConv2DDataFormat(c),d=R.computeConv2DInfo(i,s.shape,o,1,l,u,!1,h),p=new MV(d);return n.runWebGLProgram(p,[a,s],"float32")}var PV={kernelName:ys,backendName:"webgl",kernelFunc:zV};function LV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=R.computeConv3DInfo(a.shape,s.shape,i,l,o),u=new SV(c);return n.runWebGLProgram(u,[a,s],"float32")}var WV={kernelName:wu,backendName:"webgl",kernelFunc:LV};function BV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r,c=R.computeConv3DInfo(a.shape,l,i,1,o),u=new FV(c);return n.runWebGLProgram(u,[a,s],"float32")}var VV={kernelName:zh,backendName:"webgl",kernelFunc:BV};function jV(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r,c=R.computeConv3DInfo(l,s.shape,o,1,i),u=new DV(c);return n.runWebGLProgram(u,[a,s],"float32")}var UV={kernelName:Ph,backendName:"webgl",kernelFunc:jV},HV=R3+` return cos(x); `,GV=Xe({opSnippet:HV}),qV={kernelName:gs,backendName:"webgl",kernelFunc:GV},XV=` float e2x = exp(-x); return (e2x + 1.0 / e2x) / 2.0; `,KV=Xe({opSnippet:XV}),ZV={kernelName:ho,backendName:"webgl",kernelFunc:KV},YV=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) * ${p}`],[g,w,b]=h>1?[`${(o-1)/(h-1)}`,"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=` const float height_ratio = float(${m}); const float width_ratio = float(${g}); void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int y = coords[1]; int x = coords[2]; int d = coords[3]; // get box vals float y1 = getBoxes(b,0); float x1 = getBoxes(b,1); float y2 = getBoxes(b,2); float x2 = getBoxes(b,3); // get image in batch index int bInd = round(getBoxInd(b)); if(bInd < 0 || bInd >= ${s}) { return; } float height_scale = ${A}; float width_scale = ${w}; float in_y = ${y}; if( in_y < 0.0 || in_y > ${p} ) { setOutput(float(${a})); return; } float in_x = ${b}; if( in_x < 0.0 || in_x > ${f} ) { setOutput(float(${a})); return; } vec2 sourceFracIndexCR = vec2(in_x,in_y); if(${d} == 1) { // Compute the four integer indices. ivec2 sourceFloorCR = ivec2(sourceFracIndexCR); ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR)); float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d); float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d); float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d); float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d); vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR); float top = topLeft + (topRight - topLeft) * fracCR.x; float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x; float newValue = top + (bottom - top) * fracCR.y; setOutput(newValue); } else { // Compute the coordinators of nearest neighbor point. ivec2 sourceNearestCR = ivec2(floor( sourceFracIndexCR + vec2(0.5,0.5))); float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d); setOutput(newValue); } } `}},JV=e=>{let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:c}=r,u=new YV(a.shape,s.shape,o,l,c);return n.runWebGLProgram(u,[a,s,i],"float32")},QV={kernelName:po,backendName:"webgl",kernelFunc:JV},e7=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let r=e.length,a=t?"0.0":`getX(${J3(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() { ${ot(r)} coords = getOutputCoords(); int end = ${Q3(r,"coords")}; float val = ${a}; int pow2 = int(pow(2.0, index)); if (${i}) { int idx = ${o}; ${Q3(r,"coords")} = idx; val += getX(${J3(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 J3(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 ${e} is not yet supported`)}function Q3(e,t){if(e===1)return`${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 ${e} is not yet supported`)}function ej(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r,l=a.shape.length,c=R.getAxesPermutation([s],l),u=a;c!=null&&(u=En({inputs:{x:a},backend:n,attrs:{perm:c}}));let h=R.getInnerMostAxes(1,l)[0];if(h!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${a.shape.length-1} but got axis=${s}`);let d=u.shape[h],p=Wn({inputs:{x:u},backend:n});for(let f=0;f<=Math.ceil(Math.log2(d))-1;f++){let m=new e7(u.shape,!1,o),A=m.getCustomSetupFunc(f),y=p;p=n.runWebGLProgram(m,[p],p.dtype,A),n.disposeIntermediateTensorInfo(y)}if(i){let f=new e7(u.shape,i,o),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(c!=null){let f=R.getUndoAxesPermutation(c),m=En({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(u),m}return p}var tj={kernelName:xs,backendName:"webgl",kernelFunc:ej};function nj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.readSync(a.dataId),c=n.readSync(s.dataId),u=A3(l,c,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}else if(a.shape.length===2){let l=n.bufferSync(a),c=n.bufferSync(s),u=RL(l,c,i,o);return n.makeTensorInfo(u.shape,s.dtype,u.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var rj={kernelName:Lh,backendName:"webgl",kernelFunc:nj},aj=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 sj(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 aj(f,s,i);return n.runWebGLProgram(m,[a],a.dtype)}var ij={kernelName:fo,backendName:"webgl",kernelFunc:sj},t7=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); } `}},n7=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 b=0;b= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) { xTexelR${b}C${x} = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if(xCOffset + 1 >= ${i}) { xTexelR${b}C${x}.zw = vec2(0.); } } else { xTexelR${b}C${x} = vec4(0.); } xCOffset = xC + 1 - 2; if(xR >= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) { vec4 previous = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if(xCOffset + 1 >= ${i}) { previous.zw = vec2(0.); } xR${b}C${x} = vec4(previous.zw, xTexelR${b}C${x}.xy); } else { xR${b}C${x} = vec4(0, 0, xTexelR${b}C${x}.xy); } `:A+=` if(xR >= 0 && xR < ${s} && xC >= 0 && xC < ${i}) { xTexelR${b}C${x} = getX(batch, xR, xC, d1); } else { xTexelR${b}C${x} = vec4(0.); } xR${b}C${x} = xTexelR${b}C${x}; `,x+1= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) { xTexelR${b}C${x+2} = getX(batch, xR, xCOffset, d1); } `,d>1&&(A+=` xCOffset -= 2; if(xR >= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) { xTexelR${b}C${x} = getX(batch, xR, xCOffset, d1); } else { xTexelR${b}C${x} = vec4(0.); } `),A+=` xR${b}C${x+1} = vec4( xTexelR${b}C${x}.zw, xTexelR${b}C${x+2}.xy); `):A+=` xCOffset = xC + ${N}; if(xR >= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) { xTexelR${b}C${x+2} = getX(batch, xR, xCOffset, d1); } xR${b}C${x+1} = xTexelR${b}C${x+2}; `}}else x= 0 && xR < ${s}) { `,l%2==1?(A+=` xCOffset = xC + 1 - ${u}; if(xCOffset >= 0 && xCOffset < ${i}) { xTexelR${b}C${x} = getX(batch, xR, xCOffset, d1); } else { xTexelR${b}C${x} = vec4(0.); } if(xC + 1 >= 0 && xC + 1 < ${i}) { xTexelR${b}C${x+2} = getX(batch, xR, xC + 1, d1); } else { xTexelR${b}C${x+2} = vec4(0.); } xR${b}C${x} = vec4( xTexelR${b}C${x}.zw, xTexelR${b}C${x+2}.zw); `,x+1= 0 && xCOffset < ${i}) { final = getX(batch, xR, xCOffset, d1); } xR${b}C${x+1} = vec4(xTexelR${b}C${x+2}.xy, final.xy); `)):(A+=` if(xC >= 0 && xC < ${i}) { xTexelR${b}C${x} = getX(batch, xR, xC, d1); } else { xTexelR${b}C${x} = vec4(0.); } xCOffset = xC + ${u}; if(xCOffset >= 0 && xCOffset < ${i}) { xTexelR${b}C${x+2} = getX(batch, xR, xCOffset, d1); } else { xTexelR${b}C${x+2} = vec4(0.); } xR${b}C${x} = vec4( xTexelR${b}C${x}.xy, xTexelR${b}C${x+2}.xy); `,x+1`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let h=R.computeConv2DInfo(a.shape,s.shape,i,u,o,c,!0),d;return J().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?d=new n7(h):d=new t7(h),n.runWebGLProgram(d,[a,s],"float32")}var lj={kernelName:ws,backendName:"webgl",kernelFunc:oj},uj=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 >= ${e.inWidth}) { continue; } float dyValue = getDy(b, yR, yC, d2); float xValue = getX(b, xR, xC, d1); dotProd += (xValue * dyValue); } } } setOutput(dotProd); } `}},cj=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=` const ivec2 pads = ivec2(${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 * ${o} + dm; float xValue = getDy(batch, idyR, idyC, d2); float wValue = getW(wRPerm, wCPerm, d1, dm); dotProd += xValue * wValue; } } } setOutput(dotProd); } `}};function hj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,filterShape:u}=r,h=R.computeConv2DInfo(a.shape,u,i,o,l,c,!0),d=new uj(h);return n.runWebGLProgram(d,[a,s],"float32")}var dj={kernelName:Wh,backendName:"webgl",kernelFunc:hj};function pj(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,inputShape:u}=r,h=R.computeConv2DInfo(u,s.shape,i,o,l,c,!0),d=new cj(h);return n.runWebGLProgram(d,[a,s],"float32")}var fj={kernelName:Bh,backendName:"webgl",kernelFunc:pj},mj=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=` void main() { ivec2 coords = getOutputCoords(); float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0; setOutput(val); } `}};function Aj(e){let{inputs:t,backend:n}=e,{x:r}=t,a=[...r.shape,...r.shape],s=v.sizeFromShape(r.shape),i=xe({inputs:{x:r},backend:n,attrs:{shape:[s]}}),o=new mj(s),l=n.runWebGLProgram(o,[i],i.dtype),c=xe({inputs:{x:l},backend:n,attrs:{shape:a}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),c}var yj={kernelName:Vh,backendName:"webgl",kernelFunc:Aj},gj=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:r,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:c}=e,{top:u,left:h}=r;this.userCode=` const ivec2 strides = ivec2(${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 xj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=R.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),u,h=new gj(c);u=n.runWebGLProgram(h,[a,s],"float32");let d=xe({inputs:{x:u},backend:n,attrs:{shape:c.outShape}});return n.disposeIntermediateTensorInfo(u),d}var wj={kernelName:bu,backendName:"webgl",kernelFunc:xj},bj="return (x >= 0.0) ? x : (exp(x) - 1.0);",_j=` 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; `,vj=Xe({opSnippet:bj,packedOpSnippet:_j}),kj={kernelName:mo,backendName:"webgl",kernelFunc:vj},Ij="return (b >= 1.0) ? a : a * (b + 1.0);",Nj=` vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.))); return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0)))); `,Sj=e=>{let{inputs:t,backend:n}=e,{dy:r,y:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new yc(Nj,r.shape,a.shape):new Ol(Ij,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)},Tj={kernelName:Hh,backendName:"webgl",kernelFunc:Sj},Ej=` return vec4(equal(a, b)); `,Cj="return float(a == b);",Rj=nn({opSnippet:Cj,packedOpSnippet:Ej,dtype:"bool"}),Mj={kernelName:yo,backendName:"webgl",kernelFunc:Rj},Fj=` // Error function is calculated approximately with elementary function. // See "Handbook of Mathematical Functions with Formulas, // Graphs, and Mathematical Tables", Abramowitz and Stegun. float p = ${R.ERF_P}; float a1 = ${R.ERF_A1}; float a2 = ${R.ERF_A2}; float a3 = ${R.ERF_A3}; float a4 = ${R.ERF_A4}; float a5 = ${R.ERF_A5}; float sign = sign(x); x = abs(x); float t = 1.0 / (1.0 + p * x); return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x)); `,Dj=Xe({opSnippet:Fj}),$j={kernelName:Ao,backendName:"webgl",kernelFunc:Dj},r7="return exp(x);",a7=Xe({opSnippet:r7,packedOpSnippet:r7,cpuKernelImpl:DL}),Oj={kernelName:_s,backendName:"webgl",kernelFunc:a7};function wA(e){let{inputs:t,attrs:n,backend:r}=e,{dim:a}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),xe({inputs:{x:s},backend:r,attrs:{shape:o}})}var zj={kernelName:go,backendName:"webgl",kernelFunc:wA},s7="return exp(x) - 1.0;",Pj=Xe({opSnippet:s7,packedOpSnippet:s7,cpuKernelImpl:$L}),Lj={kernelName:xo,backendName:"webgl",kernelFunc:Pj},i7=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}; 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void main() { // Input can be obtained from uniform value. setOutput(value); } `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}};function bA(e){let{backend:t,attrs:n}=e,{shape:r,value:a}=n,{dtype:s}=n;if(s=s||v.inferDtype(a),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(r));return i.fill(a),t.makeTensorInfo(r,s,i)}else{let i=new Vj(r,a),o=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[],s,o)}}var jj={kernelName:_u,backendName:"webgl",kernelFunc:bA},Uj=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); } `}},Hj={kernelName:wo,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,r=t,a=new Uj(n.shape);return r.runWebGLProgram(a,[n],n.dtype)}},l7="return floor(x);",Gj=Xe({opSnippet:l7,packedOpSnippet:l7,cpuKernelImpl:OL}),qj={kernelName:vs,backendName:"webgl",kernelFunc:Gj},Xj=` 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; } `,Kj=` 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); `,Zj=nn({opSnippet:Xj,packedOpSnippet:Kj,dtype:"int32"}),Yj={kernelName:ks,backendName:"webgl",kernelFunc:Zj},Jj=class{constructor(e){this.variableNames=["A"];let t=dn(),[n,r]=e;this.outputShape=e,this.userCode=` void main() { ivec3 coords = getOutputCoords(); 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} else if (depth == 3) { value = values.a; } result[row * 2 + col] = floor(value * 255.0 + 0.5); } } ${t.output} = result; } `}},tU={kernelName:od,backendName:"webgl",kernelFunc:eU},Pl;function eU(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,c]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],u=[c,l],h=[c,l,s];(o||i)&&(Pl==null&&(Pl=document.createElement("canvas").getContext("2d")),Pl.canvas.width=l,Pl.canvas.height=c,Pl.drawImage(a,0,0,l,c),a=Pl.canvas);let d=n.makeTensorInfo(u,"int32");n.texData.get(d.dataId).usage=tr.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),a);let p=J().getBool("WEBGL_PACK")?new Qj(h):new Jj(h),f=n.runWebGLProgram(p,[d],"int32");return n.disposeData(d.dataId),f}function nU(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=R.convertConv2DDataFormat(u),A=R.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=Z3({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)y=Y3({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else{let b=i!=null,_=o!=null,x=p==="leakyrelu",N=p?xp(p,!1):null,T=new K3(A,b,N,_,x),E=[a,s];if(i&&E.push(i),o&&E.push(o),x){let F=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));E.push(F),g.push(F)}y=n.runWebGLProgram(T,E,"float32")}let w=xe({inputs:{x:y},backend:n,attrs:{shape:A.outShape}});return g.push(y),g.forEach(b=>n.disposeIntermediateTensorInfo(b)),w}var rU={kernelName:ri,backendName:"webgl",kernelFunc:nU};function aU(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(R.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. 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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; `,UU=Xe({opSnippet:VU,packedOpSnippet:jU,cpuKernelImpl:BL}),HU={kernelName:Es,backendName:"webgl",kernelFunc:UU},GU="return log(1.0 + x);",qU=Xe({opSnippet:GU}),XU={kernelName:Eo,backendName:"webgl",kernelFunc:qU},KU="return float(a >= 1.0 && b >= 1.0);",ZU=` return vec4( vec4(greaterThanEqual(a, vec4(1.0))) * vec4(greaterThanEqual(b, vec4(1.0)))); `,YU=nn({opSnippet:KU,packedOpSnippet:ZU,dtype:"bool"}),JU={kernelName:Co,backendName:"webgl",kernelFunc:YU},QU="return float(!(x >= 1.0));",eH=Xe({opSnippet:QU}),tH={kernelName:vu,backendName:"webgl",kernelFunc:eH},nH="return float(a >= 1.0 || b >= 1.0);",rH=` return min( vec4(greaterThanEqual(a, vec4(1.0))) + vec4(greaterThanEqual(b, vec4(1.0))), vec4(1.0)); `,aH=nn({opSnippet:nH,packedOpSnippet:rH,dtype:"bool"}),sH={kernelName:ku,backendName:"webgl",kernelFunc:aH},iH=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 * ${o}; setOutput(val); } `}},oH=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${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); } `}},lH=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r,c=J().getBool("WEBGL_PACK_NORMALIZATION")?new oH(a.shape,s,i,o,l):new iH(a.shape,s,i,o,l);return n.runWebGLProgram(c,[a],a.dtype)},uH={kernelName:Iu,backendName:"webgl",kernelFunc:lH},cH=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); } `}},hH=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 cH(a.shape,o,l,c,u);return n.runWebGLProgram(h,[a,s,i],a.dtype)},dH={kernelName:Zh,backendName:"webgl",kernelFunc:hH};function pH(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=xe({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=Si(i,e.dtype,"max",r),l=xe({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}function u7(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=R.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 x=0;x`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=R.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return Wn({inputs:{x:a},backend:n});let h=new gc(u,"max",!1);return n.runWebGLProgram(h,[a],a.dtype)}var wH={kernelName:Ms,backendName:"webgl",kernelFunc:xH};function bH(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=R.computePool3DInfo(a.shape,s,i,u,o,c,l),d=new yA(h,"max",!1);return n.runWebGLProgram(d,[a],a.dtype)}var _H={kernelName:Nu,backendName:"webgl",kernelFunc:bH},vH=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 * ${s} + wC; float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0); dotProd += dyValue * mask; } } setOutput(dotProd); } `}},kH=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,c=e.effectiveFilterWidth,u=o-1-e.padInfo.front,h=l-1-e.padInfo.top,d=c-1-e.padInfo.left,p=o*l*c-1;this.userCode=` const ivec3 pads = ivec3(${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 IH(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=R.computePool3DInfo(i.shape,o,l,h,c,u),p=new yA(d,"max",!0),f=n.runWebGLProgram(p,[i],i.dtype),m=new kH(d),A=n.runWebGLProgram(m,[a,f],i.dtype);return n.disposeIntermediateTensorInfo(f),A}var NH={kernelName:Jh,backendName:"webgl",kernelFunc:IH};function SH(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;Tl([s,i],"maxPoolGrad");let{filterSize:l,strides:c,pad:u,dimRoundingMode:h}=r,d=R.computePool2DInfo(o.shape,l,c,1,u,h),p=!0,f=new gc(d,"max",p),m=n.runWebGLProgram(f,[o],o.dtype),A=new vH(d),y=n.runWebGLProgram(A,[a,m],o.dtype);return n.disposeIntermediateTensorInfo(m),y}var TH={kernelName:Yh,backendName:"webgl",kernelFunc:SH};function EH(e,t,n,r){let a=new gc(n,"max",!1),s=r.runWebGLProgram(a,[e],"float32");a=new gc(n,"max",!0,!0,t);let i=r.runWebGLProgram(a,[e],"float32");return[s,i]}var CH={kernelName:Qh,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(R.eitherStridesOrDilationsAreOne(s,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${c}'`);let u=R.computePool2DInfo(r.shape,a,s,c,i),[h,d]=EH(r,o,u,l);return[h,d]}};function RH(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=xe({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=Si(i,"float32","mean",r),l=xe({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}var MH={kernelName:Fs,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=R.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,b=new Array(o);for(let N=0;Nc[0]+e[u]+c[1]);let r=e.length,a=ot(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})); } `}},WH=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=ot(r),s=t.map(p=>p[0]).join(","),i=t.map((p,f)=>p[0]+e[f]).join(","),o=pn("rc",r),l=pn("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); } `}},BH=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{paddings:a,mode:s}=n,i=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new WH(r.shape,a,s):new LH(r.shape,a,s);return t.runWebGLProgram(i,[r],r.dtype)},VH={kernelName:Su,backendName:"webgl",kernelFunc:BH},jH=`if (b == 0.0) return NAN; return mod(a, b);`,UH=` vec4 result = mod(a, b); vec4 isNaN = vec4(equal(b, vec4(0.0))); `+gp+` return result; `,HH=nn({opSnippet:jH,packedOpSnippet:UH}),GH={kernelName:Ro,backendName:"webgl",kernelFunc:HH},qH=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)}}},XH=` if (a == b) { return 1.0; }; return a / b;`,KH=` // 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; `,c7=nn({opSnippet:XH,packedOpSnippet:KH,checkOutOfBounds:!0}),ZH={kernelName:bs,backendName:"webgl",kernelFunc:c7},h7="return a - b;",d7=nn({opSnippet:h7,packedOpSnippet:h7,supportsComplex:!0,cpuKernelImpl:JL}),YH={kernelName:Qs,backendName:"webgl",kernelFunc:d7};function p7(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{dim:s}=r,i=v.parseAxisParam([s],a.shape),o=u7({inputs:{x:a},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=R.expandShapeToKeepDim(o.shape,i),c=xe({inputs:{x:o},backend:n,attrs:{shape:l}}),u=d7({inputs:{a,b:c},backend:n}),h=a7({inputs:{x:u},backend:n}),d=AA({inputs:{x:h},backend:n,attrs:{axis:i,keepDims:!1}}),p=xe({inputs:{x:d},backend:n,attrs:{shape:l}}),f=c7({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 JH={kernelName:Ys,backendName:"webgl",kernelFunc:p7};function QH(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r,l=o?a:p7({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),c=l.shape[0],u=l.shape[1],h=new qH(c,u,s),d=h.getCustomSetupFunc(i),p=n.runWebGLProgram(h,[l],"int32",d);return o||n.disposeIntermediateTensorInfo(l),p}var eG={kernelName:ed,backendName:"webgl",kernelFunc:QH},f7="return -x;";function tG(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){let s=n.texData.get(r.dataId),[i,o]=GL(s.values,r.shape,r.dtype);return n.makeTensorInfo(o,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Dl(r.shape,f7):a=new Ha(r.shape,f7),n.runWebGLProgram(a,[r],r.dtype)}var nG={kernelName:Mo,backendName:"webgl",kernelFunc:tG},rG=Hr.nonMaxSuppressionV3Impl;function aG(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=r,c=n.readSync(a.dataId),u=n.readSync(s.dataId),{selectedIndices:h}=rG(c,u,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var sG={kernelName:Do,backendName:"webgl",kernelFunc:aG},iG=Hr.nonMaxSuppressionV4Impl;function oG(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),{selectedIndices:d,validOutputs:p}=iG(u,h,i,o,l,c);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var lG={kernelName:$o,backendName:"webgl",kernelFunc:oG},uG=Hr.nonMaxSuppressionV5Impl;function cG(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),d=i,p=o,f=l,m=c,{selectedIndices:A,selectedScores:y}=uG(u,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var hG={kernelName:Oo,backendName:"webgl",kernelFunc:cG},dG=class{constructor(e,t,n,r){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=` void main() { ivec2 coords = getOutputCoords(); int index = round(getIndices(coords.x)); setOutput(mix(float(${r}), float(${n}), float(index == coords.y))); } `}},pG=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 dG(l,s,i,o),u=xe({inputs:{x:a},backend:n,attrs:{shape:[l]}}),h=n.runWebGLProgram(c,[u],a.dtype);n.disposeIntermediateTensorInfo(u);let d=[...a.shape,s],p=xe({inputs:{x:h},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(h),p},fG={kernelName:zs,backendName:"webgl",kernelFunc:pG};function Ip(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="complex64"){let a=wc({inputs:{input:r},backend:n}),s=Ip({inputs:{x:a},backend:n}),i=kp({inputs:{input:r},backend:n}),o=Ip({inputs:{x:i},backend:n}),l=Ga({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return bA({attrs:{shape:r.shape,dtype:r.dtype,value:r.dtype==="string"?"":0},backend:n})}var mG={kernelName:el,backendName:"webgl",kernelFunc:Ip};function m7(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=wc({inputs:{input:r},backend:n}),s=m7({inputs:{x:a},backend:n}),i=kp({inputs:{input:r},backend:n}),o=Ip({inputs:{x:i},backend:n}),l=Ga({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return bA({attrs:{shape:r.shape,dtype:r.dtype,value:1},backend:n})}var AG={kernelName:zo,backendName:"webgl",kernelFunc:m7};function yG(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return wA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(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=wA({inputs:{input:u},backend:n,attrs:{dim:a}});return o.push(h),h}),c=X3({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(u=>n.disposeIntermediateTensorInfo(u)),c}var gG={kernelName:Po,backendName:"webgl",kernelFunc:yG},xG=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=ot(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}; uniform float value; void main() { int outC = getOutputCoords(); if (outC < start || outC >= end) { setOutput(value); } else { setOutput(getX(outC - start)); } } `;return}this.userCode=` ${a} start = ${a}(${s}); ${a} end = ${a}(${i}); uniform float value; void main() { ${a} outC = getOutputCoords(); if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) { setOutput(value); } else { ${a} coords = outC - start; setOutput(getX(${o})); } } `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},wG=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=ot(r),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=pn("rc",r),l=pn("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{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},A7=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r,o=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new wG(a.shape,s,i):new xG(a.shape,s,i),l=o.getCustomSetupFunc(i);return n.runWebGLProgram(o,[a],a.dtype,l)},bG={kernelName:Ps,backendName:"webgl",kernelFunc:A7},_G=` 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); `,vG=` // 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)); `+gp+` return result; `,kG=nn({opSnippet:_G,packedOpSnippet:vG}),IG={kernelName:Ls,backendName:"webgl",kernelFunc:kG};function NG(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=R.getAxesPermutation(u,o),d=a;h!=null&&(d=En({inputs:{x:a},backend:n,attrs:{perm:h}}),u=R.getInnerMostAxes(u.length,o),l.push(d)),R.assertAxesAreInnerMostDims("prod",u,o);let p;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:A,outDtype:y}=qL(d.shape,d.dtype,f,u);p=n.makeTensorInfo(A,y,m)}else{let[f,m]=R.computeOutAndReduceShapes(d.shape,u),A=v.sizeFromShape(m),y=xe({inputs:{x:d},backend:n,attrs:{shape:[-1,A]}}),g=dd(a.dtype),w=Si(y,g,"prod",n);p=xe({inputs:{x:w},backend:n,attrs:{shape:f}}),l.push(y),l.push(w)}if(i){l.push(p);let f=R.expandShapeToKeepDim(p.shape,c);p=xe({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var SG={kernelName:Lo,backendName:"webgl",kernelFunc:NG},y7=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=XL(r,a,s,i);return t.makeTensorInfo([o.length],i,o)},TG={kernelName:Tu,backendName:"webgl",kernelFunc:y7},EG="return 1.0 / x;",CG=Xe({opSnippet:EG}),RG={kernelName:Wo,backendName:"webgl",kernelFunc:CG},MG=Nr+` return (x < 0.0) ? 0.0 : x; `,FG=` 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; `,DG=Xe({opSnippet:MG,packedOpSnippet:FG}),$G={kernelName:Bs,backendName:"webgl",kernelFunc:DG},OG=Nr+` return (x < 0.0) ? 0.0 : min(6.0, x); `,zG=` 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; `,PG=Xe({opSnippet:OG,packedOpSnippet:zG}),LG={kernelName:js,backendName:"webgl",kernelFunc:PG},WG=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); } `}},BG=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 VG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=J().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new BG(a.shape,l,c,s,i):new WG(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],"float32")}var jG={kernelName:Vs,backendName:"webgl",kernelFunc:VG},UG=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 HG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new UG(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var GG={kernelName:rd,backendName:"webgl",kernelFunc:HG},qG=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 + ${h}))); float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d); setOutput(newValue); } `}};function XG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=new qG(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],a.dtype)}var KG={kernelName:Eu,backendName:"webgl",kernelFunc:XG},ZG=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=` void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int d = coords[3]; int r = coords[1]; int c = coords[2]; float accumulator = 0.0; const float heightScale = float(${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), ${n} ? float(round(sourceFracCol)) : float(floor(sourceFracCol)))); if (r == sourceNearestRow && c == sourceNearestCol) { accumulator += getDy(b, dyR, dyC, d); } } } // End loop over dy setOutput(accumulator); } `}};function YG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new ZG(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var JG={kernelName:nd,backendName:"webgl",kernelFunc:YG},QG=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=` void main() { int coord = getOutputCoords(); setOutput(getX(${e[0]} - coord - 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n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),g}var dq={kernelName:Vo,backendName:"webgl",kernelFunc:hq},pq=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let r,a;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)a="resRC",r="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let c=0;c= 1.0) { setOutput(getA(${a})); } else { setOutput(getB(${a})); } } `}};function fq(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t,i=new pq(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(i,[r,a,s],ur(a.dtype,s.dtype))}var mq={kernelName:jo,backendName:"webgl",kernelFunc:fq},Aq=` // Stable and Attracting Fixed Point (0, 1) for Normalized Weights. // see: https://arxiv.org/abs/1706.02515 float scaleAlpha = ${R.SELU_SCALEALPHA}; float scale = ${R.SELU_SCALE}; return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0); 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r=n.length,a=ot(n.length),s=ot(n.length),i="";if(r===1)i="coords * strides + begin";else{let o=0;i=n.map((l,c)=>(o++,n.length===1?`coords * strides[${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 Yq(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}=un.sliceInfo(a.shape,s,i,o,l,c,u,h,d),w=xe({inputs:{x:a},backend:n,attrs:{shape:y}}),b;if(p){let x=xc({inputs:{x:w},backend:n,attrs:{begin:f,size:A}});b=xe({inputs:{x},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(x)}else if(g.some(x=>x===0))b=n.makeTensorInfo(g,a.dtype,[]);else if(n.shouldExecuteOnCPU([w])){let 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iX(a.shape,s);return n.runWebGLProgram(i,[a],a.dtype)}var oX={kernelName:Ra,backendName:"webgl",kernelFunc:w7};function lX(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{k:s,sorted:i}=r,o=n.readSync(a.dataId),[l,c]=eW(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 uX={kernelName:Jo,backendName:"webgl",kernelFunc:lX},cX=class{constructor(e,t,n,r,a,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=n==="nearest"?1:2,o;switch(r){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=` float mapCoord(float outCoord, float len) { float inCoord = outCoord; if(${o} == 2) { if (inCoord < 0.0) { if (len <= 1.0) { inCoord = 0.0; } else { float sz2 = 2.0 * len; if (inCoord < sz2) { inCoord = sz2 * float(int(float(-inCoord / sz2))) + inCoord; } inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0; } } else if (inCoord > len - 1.0) { if (len <= 1.0) { inCoord = 0.0; } else { float sz2 = 2.0 * len; inCoord -= sz2 * float(int(float(inCoord / sz2))); if (inCoord >= len) { inCoord = sz2 - inCoord - 1.0; } } } return clamp(inCoord, 0.0, len - 1.0); } else if (${o} == 3) { if (inCoord < 0.0) { if (len <= 1.0) { inCoord = 0.0; } else { float sz = len - 1.0; inCoord += len * (float(int(float(-inCoord / sz))) + 1.0); } } else if (inCoord > len - 1.0) { if (len <= 1.0) { inCoord = 0.0; } else { float sz = len - 1.0; inCoord -= len * float(int(float(inCoord / sz))); } } return clamp(inCoord, 0.0, len - 1.0); } else if (${o} == 4) { return clamp(outCoord, 0.0, len - 1.0); } else { return outCoord; } } float readWithFillValue(int batch, int coordY, int coordX, int channel) { float outputValue; if (0 <= coordY && coordY < ${e} && 0 <= coordX && coordX < ${t}) { outputValue = getImage(batch, coordY, coordX, channel); } else { outputValue = float(${a}); } return outputValue; } void main() { ivec4 coords = getOutputCoords(); float outputValue; int batch = coords[0]; int x = coords[2]; int y = coords[1]; int channel = coords[3]; float xf = float(x); float yf = float(y); float a1 = getTransforms(batch, 0); float a2 = getTransforms(batch, 1); float a3 = getTransforms(batch, 2); float b1 = getTransforms(batch, 3); float b2 = getTransforms(batch, 4); float b3 = getTransforms(batch, 5); float c1 = getTransforms(batch, 6); float c2 = getTransforms(batch, 7); float projection = c1 * xf + c2 * yf + 1.0; if (projection == 0.0) { outputValue = float(${a}); } else { float inX = (a1 * xf + a2 * yf + a3) / projection; float inY = (b1 * xf + b2 * yf + b3) / projection; float mapX = mapCoord(inX, float(${t})); float mapY = mapCoord(inY, float(${e})); if (${i} == 1) { int coordY = int(round(mapY)); int coordX = int(round(mapX)); outputValue = readWithFillValue(batch, coordY, coordX, channel); } else { float yFloor = floor(mapY); float xFloor = floor(mapX); float yCeil = yFloor + 1.0; float xCeil = xFloor + 1.0; float valueYFloor = (xCeil - mapX) * readWithFillValue(batch, int(yFloor), int(xFloor), channel) + (mapX - xFloor) * readWithFillValue(batch, int(yFloor), int(xCeil), channel); float valueYCeil = (xCeil - mapX) * readWithFillValue(batch, int(yCeil), int(xFloor), channel) + (mapX - xFloor) * readWithFillValue(batch, int(yCeil), int(xCeil), channel); outputValue = (yCeil - mapY) * valueYFloor + (mapY - yFloor) * valueYCeil; } } setOutput(outputValue); } `}};function hX(e){let{inputs:t,backend:n,attrs:r}=e,{image:a,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:c}=r,[u,h,d,p]=a.shape,[f,m]=c!=null?c:[h,d],A=[u,f,m,p],y=new cX(h,d,i,o,l,A);return n.runWebGLProgram(y,[a,s],"float32")}var dX={kernelName:sd,backendName:"webgl",kernelFunc:hX};function pX(e){let{inputs:t,attrs:n,backend:r}=e,{axis:a}=n,{x:s}=t;Tl(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}=tW(i,a,s.shape,s.dtype);return[r.makeTensorInfo(l,s.dtype,o),r.makeTensorInfo([c.length],"int32",c)]}var fX={kernelName:id,backendName:"webgl",kernelFunc:pX};function mX(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;mn.disposeIntermediateTensorInfo(m)),f}var AX={kernelName:Qo,backendName:"webgl",kernelFunc:mX},yX=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 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compiled before being used.");return this.model.evaluate(e,t,n)}async evaluateDataset(e,t){if(!this.built)throw new Er("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 Er("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 Er("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 Hl))throw new $e(`Sequential.fromConfig called on non-Sequential input: ${i}`);for(let o of a){let l=Mr(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}}};Hl.className="Sequential";re.registerClass(Hl);function mre(e){return new ya(e)}function Are(e){return new Hl(e)}function yre(e,t){return t==null&&(t={}),pre(e,t)}function jv(e){return Jv(e)}function gre(e,t){Ar.registerCallbackConstructor(e,t)}var Vn=class extends re.Serializable{getConfig(){return{}}},N6=class extends Vn{apply(e,t=1){return Zee(e,t)}};N6.className="elu";re.registerClass(N6);var S6=class extends Vn{apply(e){return Od(e)}};S6.className="selu";re.registerClass(S6);var T6=class extends Vn{apply(e){return Ur(e)}};T6.className="relu";re.registerClass(T6);var E6=class extends Vn{apply(e){return z(()=>xl(6,Ur(e)))}};E6.className="relu6";re.registerClass(E6);var C6=class extends Vn{apply(e){return e}};C6.className="linear";re.registerClass(C6);var R6=class extends Vn{apply(e){return $n(e)}};R6.className="sigmoid";re.registerClass(R6);var M6=class extends Vn{apply(e){return Jee(e)}};M6.className="hardSigmoid";re.registerClass(M6);var F6=class extends Vn{apply(e){return yl(e)}};F6.className="softplus";re.registerClass(F6);var D6=class extends Vn{apply(e){return Yee(e)}};D6.className="softsign";re.registerClass(D6);var $6=class extends Vn{apply(e){return dl(e)}};$6.className="tanh";re.registerClass($6);var dy=class extends Vn{apply(e,t=-1){return ac(e,t)}};dy.className="softmax";re.registerClass(dy);var O6=class extends Vn{apply(e,t=-1){return Ed(e,t)}};O6.className="logSoftmax";re.registerClass(O6);var z6=class extends Vn{apply(e,t=1){return z(()=>$n(e.mul(t)).mul(e))}};z6.className="swish";re.registerClass(z6);function Ya(e){return e.getClassName()}function py(e,t={}){return Ic(e,re.SerializationMap.getMap().classNameMap,t,"activation")}function Ja(e){if(e==null){let t={};return t.className="linear",t.config={},py(t)}if(typeof e=="string"){let t={};return t.className=e,t.config={},py(t)}else return e instanceof Vn?e:py(e)}function fy(e){if(e!=null&&typeof e!="object")throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${e}`)}var P6=class extends re.Serializable{},zc=class extends P6{constructor(e){super();fy(e),this.l1=e==null||e.l1==null?.01:e.l1,this.l2=e==null||e.l2==null?.01:e.l2,this.hasL1=this.l1!==0,this.hasL2=this.l2!==0}apply(e){return z(()=>{let t=Ct([1]);return this.hasL1&&(t=se(t,Te(P(this.l1,Ot(e))))),this.hasL2&&(t=se(t,Te(P(this.l2,Cc(e))))),t.asScalar()})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(e,t){return new e({l1:t.l1,l2:t.l2})}};zc.className="L1L2";re.registerClass(zc);function xre(e){return fy(e),new zc({l1:e!=null?e.l1:null,l2:0})}function wre(e){return fy(e),new zc({l2:e!=null?e.l2:null,l1:0})}var L6={l1l2:"L1L2"};function ut(e){return TA(e)}function W6(e,t={}){return Ic(e,re.SerializationMap.getMap().classNameMap,t,"regularizer")}function xt(e){if(e==null)return null;if(typeof e=="string"){let t={className:e in L6?L6[e]:e,config:{}};return W6(t)}else return e instanceof P6?e:W6(e)}var my=class extends qe{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null&&(this.maxValue=e.maxValue)}call(e,t){e=Pe(e);let n=Ur(e);return this.maxValue!=null&&(n=In(n,0,this.maxValue)),n}computeOutputShape(e){return e}getConfig(){let e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}};my.className="ReLU";re.registerClass(my);var Ay=class extends qe{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 Yu(n,this.alpha)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};Ay.className="LeakyReLU";re.registerClass(Ay);var yy=class extends qe{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=Bt(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=lt(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(Et(t),t==="channelsFirst"?nt(e,[0,2,3,1]):e))}function B6(e,t){return z(()=>(Et(t),t==="channelsFirst"?nt(e,[0,2,3,4,1]):e))}function bre(e,t,n,r=1,a="valid",s,i=1){return z(()=>{if(s==null&&(s=Tr()),Et(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=nt(e,[0,2,1])),a==="causal")throw new $e("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=bd(e,t,r,a==="same"?"same":"valid","NWC",i);return n!=null&&(o=Zr(o,n)),o})}function V6(e,t,n,r=[1,1],a="valid",s,i,o=null){return z(()=>{if(s==null&&(s=Tr()),Et(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=by(e,s);if(a==="causal")throw new $e("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=ja.conv2d({x:l,filter:t,strides:r,pad:a==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=nt(l,[0,3,1,2])),l})}function _re(e,t,n,r=[1,1,1],a="valid",s,i){return z(()=>{if(s==null&&(s=Tr()),Et(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=B6(e,s);if(a==="causal")throw new $e("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=cm(o,t,r,a==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Zr(o,n)),s==="channelsFirst"&&(o=nt(o,[0,4,1,2,3])),o})}var _y=class extends qe{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",_y.verifyArgs(t),this.rank=e,Gt(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new $e(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Gl(t.kernelSize,e,"kernelSize"),this.strides=Gl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,nr(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Et(this.dataFormat),this.activation=Ja(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=gt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Bt(t.biasConstraint),this.biasRegularizer=xt(t.biasRegularizer),this.activityRegularizer=xt(t.activityRegularizer),this.dilationRate=Gl(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(Xr("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!CA(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 ${JSON.stringify(e.kernelSize)}.`)}getConfig(){let e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:Ya(this.activation),useBias:this.useBias,biasInitializer:Nt(this.biasInitializer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),biasConstraint:Wt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Pc=class extends _y{constructor(e,t){super(e,t);this.kernel=null,Pc.verifyArgs(t),this.filters=t.filters,Gt(this.filters,"filters"),this.kernelInitializer=gt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Bt(t.kernelConstraint),this.kernelRegularizer=xt(t.kernelRegularizer)}build(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new B(`The channel dimension of the input should be defined. 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Found `None`.");let n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new qt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return z(()=>{let n=Pe(e);if(n.shape.length!==4)throw new B(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${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=e0(o,h,c,this.padding),f=e0(l,d,u,this.padding),m=[a,p,f,this.filters];this.dataFormat!=="channelsLast"&&(n=nt(n,[0,2,3,1]));let A=_d(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(A=nt(A,[0,3,1,2])),this.bias!=null&&(A=Zr(A,this.bias.read(),this.dataFormat)),this.activation!=null&&(A=this.activation.apply(A)),A})}computeOutputShape(e){e=lt(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]=e0(t[r],o,s,this.padding),t[a]=e0(t[a],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};vy.className="Conv2DTranspose";re.registerClass(vy);var j6=class extends Pc{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=Bt(t.depthwiseConstraint),this.pointwiseInitializer=gt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=xt(t.pointwiseRegularizer),this.pointwiseConstraint=Bt(t.pointwiseConstraint)}build(e){if(e=lt(e),e.length{e=Pe(e);let n;if(this.rank===1)throw new $e("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=nt(e,[0,2,3,1])),n=Tm(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Zr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=nt(n,[0,3,1,2])),n})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=Nt(this.depthwiseInitializer),e.pointwiseInitializer=Nt(this.pointwiseInitializer),e.depthwiseRegularizer=ut(this.depthwiseRegularizer),e.pointwiseRegularizer=ut(this.pointwiseRegularizer),e.depthwiseConstraint=Wt(this.depthwiseConstraint),e.pointwiseConstraint=Wt(this.pointwiseConstraint),e}};j6.className="SeparableConv";var ky=class extends j6{constructor(e){super(2,e)}};ky.className="SeparableConv2D";re.registerClass(ky);var n0=class extends Pc{constructor(e){super(1,e);n0.verifyArgs(e),this.inputSpec=[{ndim:3}]}getConfig(){let e=super.getConfig();return delete e.rank,delete e.dataFormat,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!CA(e.kernelSize,"number",1,1))throw new B(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};n0.className="Conv1D";re.registerClass(n0);var Iy=class extends qe{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 z(()=>{if(e=Pe(e),this.dataFormat==="channelsLast"){let n=Mp(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Mp(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Mp(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Mp(n,this.cropping[1][0],e.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let e={cropping:this.cropping,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};Iy.className="Cropping2D";re.registerClass(Iy);var Ny=class extends qe{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,Et(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,jee(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 z(()=>{let n=Pe(e),r=n.shape;if(this.dataFormat==="channelsFirst"){n=nt(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 nt(i,[0,3,1,2])}else{let a=this.size[0]*r[1],s=this.size[1]*r[2];return this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};Ny.className="UpSampling2D";re.registerClass(Ny);function vre(e,t,n=[1,1],r="valid",a,s){return z(()=>{a==null&&(a=Tr()),Et(a);let i=by(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=fl(i,t,n,r==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=nt(i,[0,3,1,2])),i})}var Sy=class extends _y{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=gt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Bt(e.depthwiseConstraint),this.depthwiseRegularizer=xt(e.depthwiseRegularizer)}build(e){if(e=lt(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 z(()=>{e=Pe(e);let n=vre(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Zr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=Fr(t,this.kernelSize[0],this.padding,this.strides[0]),s=Fr(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],r,a,s]:[e[0],a,s,r]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=Nt(this.depthwiseInitializer),e.depthwiseRegularizer=ut(this.depthwiseRegularizer),e.depthwiseConstraint=Wt(this.depthwiseRegularizer),e}};Sy.className="DepthwiseConv2D";re.registerClass(Sy);function U6(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 H6(e,t,n,r=!1,a,s,i=!1,o=!1){return z(()=>{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(Cr(2,l));if(t=nt(t,c),s!=null)throw new $e("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=Qt(a,-1)),a=nt(a,c)),r&&(t=Pn(t,0),a!=null&&(a=Pn(a,0)));let u=[],h,d=n,p=t.shape[0],f=dr(t),m;a!=null&&(m=dr(a));for(let y=0;ye(g,d));if(a==null)h=w[0],d=w[1];else{let b=z(()=>{let _=m[y],x=zn(_).sub(_),N=w[0].mul(_).add(d[0].mul(x)),T=d.map((E,F)=>w[1][F].mul(_).add(E.mul(x)));return{output:N,newStates:T}});h=b.output,d=b.newStates}o&&u.push(h)}let A;return o&&(A=cn(u,1)),[h,A,d]})}var Yr=class extends qe{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 r0({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 qt({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return Cr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){ZA(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],r;if(this.returnSequences?r=[e[0],e[1],n]:r=[e[0],n],this.returnState){let a=[];for(let s of t)a.push([e[0],s]);return[r].concat(a)}else return r}computeMask(e,t){return z(()=>{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;ni.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 qt({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){z(()=>{if(!this.stateful)throw new ma("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new 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)_e(this.states_),this.keptStates!=null&&(_e(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()):_e(this.states_);for(let r=0;rUt(r.clone()))})}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=U6(e,n,r,this.numConstants);e=a.inputs,n=a.initialState,r=a.constants;let s=[],i=[];if(n!=null){t.initialState=n,s=s.concat(n),this.stateSpec=[];for(let o of n)this.stateSpec.push(new qt({shape:o.shape}));i=i.concat(this.stateSpec)}if(r!=null&&(t.constants=r,s=s.concat(r),this.numConstants=r.length),s[0]instanceof Rr){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 z(()=>{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=H6((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 z(()=>{let t=Ct(e.shape);return t=Te(t,[1,2]),t=Ec(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?OA(t,[1,n]):t):this.cell.stateSize>1?[OA(t,[1,this.cell.stateSize])]:[t]})}get trainableWeights(){return this.trainable?this.cell.trainableWeights:[]}get nonTrainableWeights(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.cell!=null&&this.cell.setFastWeightInitDuringBuild(e)}getConfig(){let e=super.getConfig(),t={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};this.numConstants!=null&&(t.numConstants=this.numConstants);let n=this.cell.getConfig();return this.getClassName()===Yr.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let r=t.cell,a=Mr(r,n);return new e(Object.assign(t,{cell:a}))}};Yr.className="RNN";re.registerClass(Yr);var Mc=class extends qe{},a0=class extends Mc{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,Gt(this.units,"units"),this.activation=Ja(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=Bt(e.kernelConstraint),this.recurrentConstraint=Bt(e.recurrentConstraint),this.biasConstraint=Bt(e.biasConstraint),this.dropout=Bl([1,Ka([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Bl([1,Ka([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=lt(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 z(()=>{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;0zn(e),rate:this.dropout,training:r})),0zn(n),rate:this.recurrentDropout,training:r}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=Kr(P(e,s),this.kernel.read()):a=Kr(e,this.kernel.read()),this.bias!=null&&(a=Zr(a,this.bias.read())),i!=null&&(n=P(n,i));let o=se(a,Kr(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:Ya(this.activation),useBias:this.useBias,kernelInitializer:Nt(this.kernelInitializer),recurrentInitializer:Nt(this.recurrentInitializer),biasInitializer:Nt(this.biasInitializer),kernelRegularizer:ut(this.kernelRegularizer),recurrentRegularizer:ut(this.recurrentRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Wt(this.kernelConstraint),recurrentConstraint:Wt(this.recurrentConstraint),biasConstraint:Wt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};a0.className="SimpleRNNCell";re.registerClass(a0);var Ty=class extends Yr{constructor(e){e.cell=new a0(e),super(e)}call(e,t){return z(()=>{this.cell.dropoutMask!=null&&(_e(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_e(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return new e(t)}};Ty.className="SimpleRNN";re.registerClass(Ty);var s0=class extends Mc{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,Gt(this.units,"units"),this.activation=Ja(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ja(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=Bt(e.kernelConstraint),this.recurrentConstraint=Bt(e.recurrentConstraint),this.biasConstraint=Bt(e.biasConstraint),this.dropout=Bl([1,Ka([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Bl([1,Ka([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=lt(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 z(()=>{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],0zn(e),rate:this.dropout,training:n,count:3})),0zn(r),rate:this.recurrentDropout,training:n,count:3}));let a=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0{this.cell.dropoutMask!=null&&(_e(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_e(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Ey.className="GRU";re.registerClass(Ey);var Wc=class extends Mc{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,Gt(this.units,"units"),this.activation=Ja(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ja(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=Bt(e.kernelConstraint),this.recurrentConstraint=Bt(e.recurrentConstraint),this.biasConstraint=Bt(e.biasConstraint),this.dropout=Bl([1,Ka([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Bl([1,Ka([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=lt(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 mr{apply(i,o){let l=a.apply([s]),c=new Dp().apply([s]),u=a.apply([s*2]);return zv(zv(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 z(()=>{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 ${e.length}.`);let r=e[1],a=e[2];e=e[0],0zn(e),rate:this.dropout,training:n,count:4})),0zn(r),rate:this.recurrentDropout,training:n,count:4}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,c,u;0{this.cell.dropoutMask!=null&&(_e(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_e(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Cy.className="LSTM";re.registerClass(Cy);var r0=class extends Mc{constructor(e){super(e);this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return z(()=>{e=e;let n=e.slice(1),r=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?r.push(n.splice(0,i.stateSize.length)):r.push(n.splice(0,1));r.reverse();let a=[],s;for(let i=0;i{Ri(`RNNCell_${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(Mr(a,n));return new e({cells:r})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return YA(e)}setWeights(e){let t=[];for(let n of this.cells){let r=n.weights.length,a=e.splice(r);for(let s=0;sLv(t(),n),i=()=>Rc(s,t,r);return!a||a<=1?Ut(i().clone()):Array(a).fill(void 0).map(i).map(o=>Ut(o.clone()))}var kre=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{if(this.cell.dropoutMask!=null&&(_e(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_e(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 z(()=>{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){z(()=>{if(!this.stateful)throw new ma("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)];if(n[0]==null)throw new 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)_e(this.states_),this.keptStates!=null&&(_e(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). 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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 mr{apply(u,h){let d=l.apply([c]),p=jr([c]),f=l.apply([c*2]);return PA([d,p,f])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*a],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return z(()=>{if(e.length!==3)throw new B(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,r=e[0],a=e[1],s=e[2],i=4;0zn(r),rate:this.dropout,training:n,count:i}));let o=this.dropoutMask,l=(Y,ae,te)=>!ae||!ae[te]?Y:P(ae[te],Y),c=l(r,o,0),u=l(r,o,1),h=l(r,o,2),d=l(r,o,3);0zn(a),rate:this.recurrentDropout,training:n,count:i}));let p=this.recurrentDropoutMask,f=l(a,p,0),m=l(a,p,1),A=l(a,p,2),y=l(a,p,3),g=3,[w,b,_,x]=Pt(this.kernel.read(),i,g),[N,T,E,F]=this.useBias?Pt(this.bias.read(),i):[null,null,null,null];c=this.inputConv(c,w,N,this.padding),u=this.inputConv(u,b,T,this.padding),h=this.inputConv(h,_,E,this.padding),d=this.inputConv(d,x,F,this.padding);let[$,L,V,j]=Pt(this.recurrentKernel.read(),i,g);f=this.recurrentConv(f,$),m=this.recurrentConv(m,L),A=this.recurrentConv(A,V),y=this.recurrentConv(y,j);let U=this.recurrentActivation.apply(se(c,f)),X=this.recurrentActivation.apply(se(u,m)),G=se(P(X,s),P(U,this.activation.apply(se(h,A)))),ee=P(this.recurrentActivation.apply(se(d,y)),this.activation.apply(G));return[ee,ee,G]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=kre(e,["units"]),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,r)}inputConv(e,t,n,r){let a=ua(e,t,this.strides,r||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Zr(a,n,this.dataFormat):a}recurrentConv(e,t){return ua(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};i0.className="ConvLSTM2DCell";re.registerClass(i0);var Ry=class extends G6{constructor(e){let t=new i0(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};Ry.className="ConvLSTM2D";re.registerClass(Ry);var o0=class extends qe{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.invokeCallHook(e,t);let n=Pe(e);if(0Lv(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()}};o0.className="Dropout";re.registerClass(o0);var My=class extends o0{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};My.className="SpatialDropout1D";re.registerClass(My);var Fy=class extends qe{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,Gt(this.units,"units"),this.activation=Ja(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=Bt(e.kernelConstraint),this.biasConstraint=Bt(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=lt(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=lt(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=Sv(this.activation.getClassName()),a;return r!=null?a=Kr(n,this.kernel.read(),r,this.bias?this.bias.read():null):(a=Kr(n,this.kernel.read()),this.bias!=null&&(a=Zr(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:Ya(this.activation),useBias:this.useBias,kernelInitializer:Nt(this.kernelInitializer),biasInitializer:Nt(this.biasInitializer),kernelRegularizer:ut(this.kernelRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Wt(this.kernelConstraint),biasConstraint:Wt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Fy.className="Dense";re.registerClass(Fy);var Dy=class extends qe{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=lt(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)}). 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qe{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 z(()=>{this.invokeCallHook(e,t);let n=Pe(e);return Rc(()=>Fp(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};Xy.className="GaussianNoise";re.registerClass(Xy);var Ky=class extends qe{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 z(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.rate>0&&this.rate<1?Rc(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return n.mul(Fp(n.shape,1,r))},()=>n,t.training||!1):n})}};Ky.className="GaussianDropout";re.registerClass(Ky);var Zy=class extends qe{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return 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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 z(()=>{let n=t.training==null?!1:t.training,r=Pe(e),a=r.shape,s=a.length,i=Cr(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=Ti(1,s);l[o]=a[o];let c=i.slice();c.sort();let u=!v.arraysEqual(c,Cr(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 Vc(r,A,y,g,w,this.epsilon)}else return 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s==="max"?i=Qu(e,t,n,o):i=Gu(e,t,n,o),a==="channelsFirst"&&(i=nt(i,[0,3,1,2])),i})}function q6(e,t,n,r,a,s){return z(()=>{Et(a),Rv(s),nr(r),n==null&&(n=[1,1,1]),r==null&&(r="valid"),a==null&&(a=Tr()),s==null&&(s="max"),e=B6(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=bm(e,t,n,o):i=om(e,t,n,o),a==="channelsFirst"&&(i=nt(i,[0,4,1,2,3])),i})}var X6=class extends qe{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(Gt(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)}`);Gt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,nr(this.padding),this.inputSpec=[new qt({ndim:3})]}computeOutputShape(e){e=lt(e);let t=Fr(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return z(()=>{this.invokeCallHook(e,t),e=Ec(Pe(e),2);let n=this.poolingFunction(Pe(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return Va(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},e2=class extends X6{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Et(a),nr(r),l0(e,t,n,r,a,"max")}};e2.className="MaxPooling1D";re.registerClass(e2);var t2=class extends X6{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return 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t=Fr(t,this.poolSize[0],this.padding,this.strides[0]),n=Fr(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return z(()=>(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}},n2=class extends K6{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Et(a),nr(r),l0(e,t,n,r,a,"max")}};n2.className="MaxPooling2D";re.registerClass(n2);var r2=class extends K6{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Et(a),nr(r),l0(e,t,n,r,a,"avg")}};r2.className="AveragePooling2D";re.registerClass(r2);var Z6=class extends qe{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 ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];Gt(this.poolSize,"poolSize"),Gt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Et(this.dataFormat),nr(this.padding),this.inputSpec=[new qt({ndim:5})]}computeOutputShape(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[4]:e[3];return 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c}processChildNodes(e,t,n,r,a,s){e.children.forEach(i=>{let[o]=ga(i.name,n);a[o]||!s.has(i.name)||(i.op==="Merge"?i.inputNames.some(l=>!!Fn(l,r,n))&&(a[o]=!0,t.push({contexts:n.currentContext,node:i})):i.inputNames.every(l=>!!Fn(l,r,n))&&(a[o]=!0,t.push({contexts:n.currentContext,node:i})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let n=e[t],[r]=jn(t),a=this.graph.nodes[r];if(a.attrParams.shape&&a.attrParams.shape.value){let s=a.attrParams.shape.value,i=s.length===n.shape.length&&n.shape.every((o,l)=>s[l]===-1||s[l]===o);v.assert(i,()=>`The shape of dict['${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 ${n.dtype}`)})}mapInputs(e){let t={};for(let n in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let r=this._signature.inputs[n];t[r.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[r]=jn(n);return this.graph.nodes[r]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${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]=jn(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}},Kae=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]}},Zae="?tfjs-format=file",Yae="model.json",$4=class{constructor(e,t={}){this.modelUrl=e,this.loadOptions=t,this.version="n/a",t==null&&(this.loadOptions={}),this.resourceManager=new Kae}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=kn.browserHTTPRequest(e,this.loadOptions);else{let t=kn.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(kn.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${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}.${t.versions.minConsumer}`;let r=kn.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new N2(N4.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let a=N4.Instance.transformGraph(e.modelInitializer);this.initializer=new N2(a),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=kn.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${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 We)&&!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 ${e.length} input tensors.`);return this.inputNodes.reduce((t,n,r)=>(t[n]=e[r],t),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,n)=>(t[n]=[e[n]],t),{})}dispose(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}};async function ct(e,t={}){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");t==null&&(t={}),t.fromTFHub&&e.load==null&&(e.endsWith("/")||(e=e+"/"),e=`${e}${Yae}${Zae}`);let n=new $4(e,t);return await n.load(),n}var Jae="3.3.0",O4={};Me(O4,{CSVDataset:()=>P4,Dataset:()=>ql,FileDataSource:()=>L4,TextLineDataset:()=>z4,URLDataSource:()=>W4,array:()=>Qae,csv:()=>tse,func:()=>nse,generator:()=>rse,microphone:()=>sse,version_data:()=>ise,webcam:()=>ase,zip:()=>ese});var ose=Qi(Yg()),lse=Qi(Yg());function use(e,t){return d0(e,t)}function d0(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(Xl(e)){let s=Array.isArray(e)?[]:{};r.add(e);for(let i in e){let o=e[i],l=d0(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 cse(e,t=V4){return B4(e,t)}function B4(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(Xl(r)){let s=Array.isArray(r)?[]:{};n.add(r);for(let i in r){let o=e.map(c=>c[i]),l=B4(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 V4(e){return e===null?null:Xl(e[0])?{value:null,recurse:!0}:{value:e,recurse:!1}}async function j4(e,t){let n=new Map;d0(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 d0(e,t,n)}function Xl(e){return e!=null&&!ArrayBuffer.isView(e)&&(Array.isArray(e)||typeof e=="object"&&!(e instanceof We))}function dse(e){return e==null||hse(e)||Array.isArray(e)||typeof e=="object"&&e instanceof We||v.isTypedArray(e)}function hse(e){return e===null||typeof e!="object"&&typeof e!="function"}function fse(e){return use(e,pse)}function pse(e){return e instanceof We?{value:e.clone(),recurse:!1}:Xl(e)?{value:null,recurse:!0}:{value:e,recurse:!1}}var U4=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}},S2=class extends U4{constructor(){super(S2.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;rt===!0)}rowMajorBatch(e,t=!0){return new vse(this,e,t)}columnMajorBatch(e,t=!0,n=V4){return this.rowMajorBatch(e,t).map(r=>cse(r,n))}concatenate(e,t){return new G4(H4([this,e]),t)}take(e){return e<0||e==null?this:new _se(this,e)}skip(e){return e<0||e==null?this:new bse(this,e)}prefetch(e){return new X4(this,e)}shuffle(e,t){return new Tse(this,e,t)}serial(){return new wse(this)}},mse=class extends Xt{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:fse(e),done:!1}}},Ase=class extends Xt{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: ${e.message}`,e}}},wse=class extends Xt{constructor(e){super();this.upstream=e,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Serial`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){return this.upstream.next()}},bse=class extends Xt{constructor(e,t){super();this.upstream=e,this.maxCount=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Skip`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.count++ Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},vse=class extends Xt{constructor(e,t,n=!0){super();this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=n,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},kse=class extends Xt{constructor(e,t){super();this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;_e(e.value)}}},Ise=class extends Xt{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=vr.getTensorsInContainer(e.value),n=this.transform(e.value),r=vr.getTensorsInContainer(n);for(let a of t)vr.isTensorInList(a,r)||a.dispose();return{value:n,done:!1}}},Nse=class extends Xt{constructor(e,t){super();this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}},q4=class extends Xt{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=vr.getTensorsInContainer(e.value),n=await this.transform(e.value),r=vr.getTensorsInContainer(n);for(let a of t)vr.isTensorInList(a,r)||a.dispose();return{value:n,done:!1}}},E2=class extends Xt{constructor(){super();this.outputQueue=new S2,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}}},Sse=class extends E2{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=vr.getTensorsInContainer(e.value),n=this.transform(e.value),r=vr.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let a of t)vr.isTensorInList(a,r)||a.dispose();return!0}},G4=class extends Xt{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}},es;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(es||(es={}));var gse=class extends Xt{constructor(e,t=es.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 Xt?{value:s.next().then(i=>(t++,i.done&&n++,i.value)),recurse:!1}:{value:null,recurse:!0}}let a=await j4(this.iterators,r);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case es.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case es.SHORTEST:return{value:null,done:!0};case es.LONGEST:default:}return this.count++,{value:a,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},X4=class extends Xt{constructor(e,t){super();this.upstream=e,this.bufferSize=t,this.buffer=new U4(t)}summary(){return`${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()}},Tse=class extends X4{constructor(e,t,n){super(e,t);this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=lse.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}}},ql=class{constructor(){this.size=null}batch(e,t=!0){let n=this;v.assert(e>0,()=>`batchSize needs to be positive, but it is ${e}`);let r;return this.size===Infinity||this.size==null?r=this.size:t?r=Math.ceil(this.size/e):r=Math.floor(this.size/e),Un(async()=>(await n.iterator()).columnMajorBatch(e,t,Ese),r)}concatenate(e){let t=this,n;return this.size===Infinity||e.size===Infinity?n=Infinity:this.size!=null&&e.size!=null?n=this.size+e.size:n=null,Un(async()=>(await t.iterator()).concatenate(await e.iterator()),n)}filter(e){let t=this,n;return this.size===Infinity?n=Infinity:n=null,Un(async()=>(await t.iterator()).filter(r=>z(()=>e(r))),n)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return Un(async()=>(await t.iterator()).map(n=>z(()=>e(n))),this.size)}mapAsync(e){let t=this;return Un(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return Un(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,n;return this.size!=null&&e>0?n=this.size*e:e===0?n=0:this.size!=null&&(e===void 0||e<0)?n=Infinity:n=null,Un(async()=>{let r=T2(async()=>({value:await t.iterator(),done:!1}));return yse(r.take(e))},n)}skip(e){let t=this,n;return this.size!=null&&e>=0&&this.size>=e?n=this.size-e:this.size!=null&&(this.size(await t.iterator()).skip(e),n)}shuffle(e,t,n=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified. If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let r=this,a=ose.alea(t||v.now().toString());return Un(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,Un(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()}};ql.MAX_BUFFER_SIZE=1e4;function Un(e,t=null){return new class extends ql{constructor(){super(...arguments);this.size=t}async iterator(){return e()}}}function Qae(e){return Un(async()=>H4(e),e.length)}function ese(e){if(!Xl(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{let n=await j4(e,r=>{if(r instanceof ql)return{value:r.iterator(),recurse:!1};if(Xl(r))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return xse(n,es.SHORTEST)},t)}function Ese(e){if(e===null)return null;let t=e[0];return dse(t)?{value:Cse(e),recurse:!1}:{value:null,recurse:!0}}function Cse(e){if(e.length===0)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof We?cn(e):Ir(e)}var z4=class extends ql{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))}},p0='"',Hc=Symbol("out"),K4=Symbol("field"),f0=Symbol("quote"),C2=Symbol("quoteafterquote"),Z4=Symbol("quoteinquote"),P4=class extends ql{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 z4(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;a14||!Number.isInteger(t))throw new Error(`Invalid fftSize: it must be a power of 2 between 2 to 4 and 2 to 14, but got ${this.fftSize}`);if(this.numFrames=e.numFramesPerSpectrogram||43,this.sampleRateHz=e.sampleRateHz,this.columnTruncateLength=e.columnTruncateLength||this.fftSize,this.audioTrackConstraints=e.audioTrackConstraints,this.smoothingTimeConstant=e.smoothingTimeConstant||0,this.includeSpectrogram=e.includeSpectrogram!==!1,this.includeWaveform=e.includeWaveform===!0,!this.includeSpectrogram&&!this.includeWaveform)throw new Error("Both includeSpectrogram and includeWaveform are false. At least one type of data should be returned.")}summary(){return"microphone"}static async create(e={}){if(J().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new Y4(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),Ir(n,t)}},J4=class extends Xt{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=on([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=Tn([s,a,o,i],[1,4])}else this.cropBox=Tn([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(J().get("IS_NODE"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new J4(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=ui.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: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return z(()=>{let t=Qt(ye(e,"float32"),0),n;n=ze.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let r=n.shape;return H(n,r.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(e=>e.stop());try{this.webcamVideoElement.srcObject=null}catch(e){console.log(e),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},Q4=class{},e8=class extends Xt{split(e){return new Rse(this,e)}},Rse=class extends e8{constructor(e,t){super();this.upstream=e,this.impl=new Mse(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Mse=class extends E2{constructor(e,t){super();this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${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}},Dse=class extends Xt{decodeUTF8(){return new Fse(this)}},Fse=class extends e8{constructor(e){super();this.upstream=e,this.impl=new $se(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},$se=class extends E2{constructor(e){super();if(this.upstream=e,J().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=w9();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let n;return J().get("IS_BROWSER")?n=this.decoder.decode(t,{stream:!0}):n=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(n),!0}},t8=class extends Dse{constructor(e,t={}){super();this.file=e,this.options=t,v.assert(e instanceof Uint8Array||(J().get("IS_BROWSER")?e instanceof File||e instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=t.offset||0,this.chunkSize=t.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((e,t)=>{let n=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)e(new Uint8Array(this.file.slice(this.offset,n)));else{let r=new FileReader;r.onload=s=>{let i=r.result;if(i instanceof 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r=Ee(e,[0,1],[-1,2]),a=se(r,t),s=Ee(e,[0,3],[-1,2]),i=me(s,n),o=me(a,n),l=me(i,2),c=Ae(o,l),u=se(o,l),h=P(c,n),d=P(u,n);return pl([h,d],1)}var o8=class{constructor(t,n){this.model=t,this.anchorsData=Vse(t.inputs[0].shape[1]),this.anchors=Tn(this.anchorsData),this.inputSize=t.inputs[0].shape[2],this.config=n}async getBoundingBoxes(t){if(!t||t.isDisposedInternal||t.shape.length!==4||t.shape[1]<1||t.shape[2]<1)return null;let[n,r,a]=z(()=>{let d=t.resizeBilinear([this.inputSize,this.inputSize]).div(127.5).sub(.5),p=this.model.predict(d),f;if(Array.isArray(p)){let g=p.sort((x,N)=>x.size-N.size),w=rt([g[0],g[2]],2),b=rt([g[1],g[3]],2);f=rt([b,w],1).squeeze(0)}else f=p.squeeze();let m=Use(f,this.anchors,[this.inputSize,this.inputSize]),A=Ee(f,[0,0],[-1,1]),y=$n(A).squeeze();return[f,m,y]}),s=await ze.nonMaxSuppressionAsync(r,a,this.config.face.detector.maxFaces,this.config.face.detector.iouThreshold,this.config.face.detector.scoreThreshold),i=s.arraySync();s.dispose();let l=i.map(h=>Ee(r,[h,0],[1,-1])).map(h=>{let d=h.arraySync();return h.dispose(),d}),c=a.dataSync(),u=[];for(let h=0;hthis.config.face.detector.minConfidence){let f=jse(l[h]),m=this.anchorsData[d],A=z(()=>Ee(n,[d,i8-1],[1,-1]).squeeze().reshape([i8,-1]));u.push({box:f,landmarks:A,anchor:m,confidence:p})}}return n.dispose(),r.dispose(),a.dispose(),{boxes:u,scaleFactor:[t.shape[2]/this.inputSize,t.shape[1]/this.inputSize]}}};async function l8(e){let t=await ct(pt(e.modelBasePath,e.face.detector.modelPath),{fromTFHub:e.face.detector.modelPath.includes("tfhub.dev")}),n=new o8(t,e);return!t||!t.modelUrl?ue("load model failed:",e.face.detector.modelPath):e.debug&&ue("load model:",t.modelUrl),n}function u8(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 Gc(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function Kl(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function Zl(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 ze.cropAndResize(t,s,[0],n)}function N0(e,t=1.5){let n=Kl(e),r=Gc(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 S0(e){let t=Kl(e),n=Gc(e),a=Math.max(...n)/2,s=[t[0]-a,t[1]-a],i=[t[0]+a,t[1]+a];return{startPoint:s,endPoint:i,landmarks:e.landmarks}}var T0=[[1,0,0],[0,1,0],[0,0,1]];function Hse(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function K2(e,t){let n=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return Hse(n)}function c8(e,t){return[[1,0,e],[0,1,t],[0,0,1]]}function ts(e,t){let n=0;for(let r=0;rqc[e]),ooe=Xse.map(e=>qc[e]),loe=Kse.map(e=>qc[e]);var Y2=Qr.leftEyeLower0,J2=Qr.rightEyeLower0,Yl={leftBounds:[Y2[0],Y2[Y2.length-1]],rightBounds:[J2[0],J2[J2.length-1]]},C0={count:468,mouth:13,symmetryLine:[13,Qr.midwayBetweenEyes[0]]},f8={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},Jl={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function R0(e,t,n,r){for(let a=0;a[s[0]/this.meshSize*(h[0]-this.meshSize/2),s[1]/this.meshSize*(h[1]-this.meshSize/2),h[2]]),o=r!==0?E0(r,[0,0]):T0,l=r!==0?i.map(h=>[...p8(h,o),h[2]]):i,c=r!==0?d8(a):T0,u=[...Kl({startPoint:n.startPoint,endPoint:n.endPoint}),1];return l.map(h=>[h[0]+ts(u,c[0]),h[1]+ts(u,c[1]),h[2]])}getLeftToRightEyeDepthDifference(t){let n=t[Yl.leftBounds[0]][2],r=t[Yl.rightBounds[0]][2];return n-r}getEyeBox(t,n,r,a,s=!1){let i=S0(N0(this.calculateLandmarksBoundingBox([t[r],t[a]]),this.irisEnlarge)),o=Gc(i),l=ze.cropAndResize(n,[[i.startPoint[1]/this.meshSize,i.startPoint[0]/this.meshSize,i.endPoint[1]/this.meshSize,i.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return s&&_r.flags.IS_BROWSER&&(l=ze.flipLeftRight(l)),{box:i,boxSize:o,crop:l}}getEyeCoords(t,n,r,a=!1){let s=[];for(let i=0;i{let c=i;return l===2?c=a:l===4&&(c=s),[o[0],o[1],c]})}async predict(t,n){let r=!1,a;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.videoOptimized)&&(a=await this.boundingBoxDetector.getBoundingBoxes(t),this.skipped=0),n.videoOptimized&&this.skipped++,!n.videoOptimized||a&&a.boxes&&(!n.face.mesh.enabled||a.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let i of a.boxes)this.storedBoxes.push({startPoint:i.box.startPoint.dataSync(),endPoint:i.box.endPoint.dataSync(),landmarks:i.landmarks,confidence:i.confidence});this.storedBoxes.length>0&&(r=!0)}if(n.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),r){if(!a||!a.boxes||a.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let i=0;i{i.box.startPoint.dispose(),i.box.endPoint.dispose(),i.landmarks.dispose()});let s=z(()=>this.storedBoxes.map((i,o)=>{let l=i.confidence,c,u=0,h;if(n.face.detector.rotation&&n.face.mesh.enabled&&_r.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=C0.count?C0.symmetryLine:f8.symmetryLine;u=K2(i.landmarks[_],i.landmarks[x]);let N=Kl({startPoint:i.startPoint,endPoint:i.endPoint}),T=[N[0]/t.shape[2],N[1]/t.shape[1]],E=ze.rotateWithOffset(t,u,0,T);h=E0(-u,N),n.face.mesh.enabled?c=Zl({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.meshSize,this.meshSize]).div(255):c=Zl({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.boxSize,this.boxSize]).div(255)}else{h=T0;let _=t.clone();n.face.mesh.enabled?c=Zl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.meshSize,this.meshSize]).div(255):c=Zl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.boxSize,this.boxSize]).div(255)}if(!n.face.mesh.enabled)return{coords:null,box:i,faceConfidence:null,boxConfidence:l,confidence:i.confidence,image:c};let[,d,p]=this.meshDetector.predict(c),f=d.dataSync()[0];if(f=C0.count?C0.symmetryLine:f8.symmetryLine;u=K2(i.landmarks[_],i.landmarks[x]);let N=Kl({startPoint:i.startPoint,endPoint:i.endPoint}),T=[N[0]/t.shape[2],N[1]/t.shape[1]],E=ze.rotateWithOffset(t,u,0,T);h=E0(-u,N),c=Zl({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.meshSize,this.meshSize]).div(255)}let w={coords:g,box:i,faceConfidence:f,boxConfidence:l,image:c,rawCoords:A},b=S0(i);return this.storedBoxes[o]={...b,landmarks:y,confidence:i.confidence,faceConfidence:f},w}));return s=s.filter(i=>i!==null),n.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(i=>i.faceConfidence>n.face.detector.minConfidence)),this.detectedFaces=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s,landmarks:t}}};var tg=class{constructor(t,n,r,a){this.facePipeline=new Q2(t,n,r),this.config=a}async estimateFaces(t,n){let r=await this.facePipeline.predict(t,n),a=[];for(let s of r||[]){if(s.isDisposedInternal)continue;let i=s.coords?s.coords.arraySync():[],o=i.map(h=>[h[0]/t.shape[2],h[1]/t.shape[1],h[2]/this.facePipeline.meshSize]),l={};if(i&&i.length>0)for(let h of Object.keys(Qr))l[h]=Qr[h].map(d=>i[d]);let c=s.box?[Math.max(0,s.box.startPoint[0]),Math.max(0,s.box.startPoint[1]),Math.min(t.shape[2],s.box.endPoint[0])-Math.max(0,s.box.startPoint[0]),Math.min(t.shape[1],s.box.endPoint[1])-Math.max(0,s.box.startPoint[1])]:0,u=s.box?[s.box.startPoint[0]/t.shape[2],s.box.startPoint[1]/t.shape[1],(s.box.endPoint[0]-s.box.startPoint[0])/t.shape[2],(s.box.endPoint[1]-s.box.startPoint[1])/t.shape[1]]:[];a.push({confidence:Math.round(100*s.faceConfidence||100*s.boxConfidence||0)/100,boxConfidence:Math.round(100*s.boxConfidence)/100,faceConfidence:Math.round(100*s.faceConfidence)/100,box:c,boxRaw:u,mesh:i,meshRaw:o,annotations:l,image:s.image?s.image.clone():null}),s.coords&&s.coords.dispose(),s.image&&s.image.dispose()}return a}},Kt=[null,null,null];async function ng(e){return!Kt[0]&&e.face.enabled||!Kt[1]&&e.face.mesh.enabled||!Kt[2]&&e.face.iris.enabled?(Kt=await Promise.all([!Kt[0]&&e.face.enabled?l8(e):null,!Kt[1]&&e.face.mesh.enabled?ct(pt(e.modelBasePath,e.face.mesh.modelPath),{fromTFHub:e.face.mesh.modelPath.includes("tfhub.dev")}):null,!Kt[2]&&e.face.iris.enabled?ct(pt(e.modelBasePath,e.face.iris.modelPath),{fromTFHub:e.face.iris.modelPath.includes("tfhub.dev")}):null]),e.face.mesh.enabled&&(!Kt[1]||!Kt[1].modelUrl?ue("load model failed:",e.face.mesh.modelPath):e.debug&&ue("load model:",Kt[1].modelUrl)),e.face.iris.enabled&&(!Kt[2]||!Kt[1].modelUrl?ue("load model failed:",e.face.iris.modelPath):e.debug&&ue("load model:",Kt[2].modelUrl))):e.debug&&(ue("cached model:",Kt[0].model.modelUrl),ue("cached model:",Kt[1].modelUrl),ue("cached model:",Kt[2].modelUrl)),new tg(Kt[0],Kt[1],Kt[2],e)}var m8=zi,A8=qc;var dg={};br(dg,{PoseNet:()=>pg,load:()=>fg});function Zse(e){let[t,n,r,a]=e;return{offsets:t,heatmap:n,displacementFwd:r,displacementBwd:a}}var rg=class{constructor(t){this.model=t}predict(t){return z(()=>{let r=t.toFloat().div(127.5).sub(1).expandDims(0),s=this.model.predict(r).map(o=>o.squeeze([0])),i=Zse(s);return{heatmapScores:i.heatmap.sigmoid(),offsets:i.offsets,displacementFwd:i.displacementFwd,displacementBwd:i.displacementBwd}})}dispose(){this.model.dispose()}};function ag(e){return Math.floor(e/2)}var sg=class{constructor(t,n){this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=n}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,t}empty(){return this.numberOfElements===-1}size(){return this.numberOfElements+1}all(){return this.priorityQueue.slice(0,this.numberOfElements+1)}max(){return this.priorityQueue[0]}swim(t){for(;t>0&&this.less(ag(t),t);)this.exchange(t,ag(t)),t=ag(t)}sink(t){for(;2*t<=this.numberOfElements;){let n=2*t;if(nt){l=!1;break}if(!l)break}return l}function y8(e,t,n){let[r,a,s]=n.shape,i=new sg(r*a*s,({score:o})=>o);for(let o=0;o(e[t]=n,e),{}),Jse=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],Ioe=Jse.map(([e,t])=>[Xc[e],Xc[t]]),g8=[["nose","leftEye"],["leftEye","leftEar"],["nose","rightEye"],["rightEye","rightEar"],["nose","leftShoulder"],["leftShoulder","leftElbow"],["leftElbow","leftWrist"],["leftShoulder","leftHip"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["nose","rightShoulder"],["rightShoulder","rightElbow"],["rightElbow","rightWrist"],["rightShoulder","rightHip"],["rightHip","rightKnee"],["rightKnee","rightAnkle"]];function ig(e,t,n,r){return{y:r.get(e,t,n),x:r.get(e,t,n+eu)}}function M0(e,t,n){let{heatmapY:r,heatmapX:a,id:s}=e,{y:i,x:o}=ig(r,a,s,n);return{x:e.heatmapX*t+o,y:e.heatmapY*t+i}}function og(e,t,n){return en?n:e}function x8(e,t,n,r){let a=n-e,s=r-t;return a*a+s*s}function lg(e,t){return{x:e.x+t.x,y:e.y+t.y}}function w8(e,t){let n=t.shape[0],r=new Float32Array(n);for(let a=0;ae.toTensor().mul(ge(t,"int32")).toFloat().add(eie(e,n)))}function tie(e,t){return z(()=>{let n=e.div(ge(t,"int32"));return e.sub(n.mul(ge(t,"int32")))})}function _8(e){let[t,n,r]=e.shape;return z(()=>{let s=e.reshape([t*n,r]).argMax(0),i=s.div(ge(n,"int32")).expandDims(1),o=tie(s,n).expandDims(1);return rt([i,o],1)})}var v8=g8.map(([e,t])=>[Xc[e],Xc[t]]),ug=v8.map(([,e])=>e),k8=v8.map(([e])=>e),nie=16;function rie(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 cg(e,t,n,r){return{y:og(Math.round(e.y/t),0,n-1),x:og(Math.round(e.x/t),0,r-1)}}function I8(e,t,n,r,a,s,i,o=2){let[l,c]=r.shape,u=cg(t.position,s,l,c),h=rie(e,u,i),p=lg(t.position,h);for(let A=0;A=0;--d){let p=ug[d],f=k8[d];l[p]&&!l[f]&&(l[f]=I8(d,l[p],f,t,n,r,s))}for(let d=0;d(r+=f,{position:{y:u.get(m,0),x:u.get(m,1)},part:Ql[m],score:f})),p=d.filter(f=>f.score>n);return a.dispose(),c.dispose(),{keypoints:p,score:r/d.length}}var aie=1,T8=16;function E8(e,t,{x:n,y:r},a){return e.some(({keypoints:s})=>{let i=s[a].position;return x8(r,n,i.y,i.x)<=t})}function sie(e,t,n){return n.reduce((a,{position:s,score:i},o)=>(E8(e,t,s,o)||(a+=i),a),0)/n.length}function C8(e,t,n,r,a,s,i){let o=[],l=y8(i,aie,e),c=a^2;for(;o.lengthi&&o.push({keypoints:d,score:Math.round(100*p)/100})}return o}async function R8(e){return Promise.all(e.map(t=>t.buffer()))}function iie(e,t,n){return{score:e.score,keypoints:e.keypoints.map(({score:r,part:a,position:s})=>({score:r,part:a,position:{x:Math.trunc(s.x*n),y:Math.trunc(s.y*t)}}))}}function M8(e,[t,n]){let r=e.squeeze(0),a=r.resizeBilinear([t,n]);return r.dispose(),a}function hg(e,[t,n],[r,a]){return e.map(i=>iie(i,t/r,n/a))}var Pi;async function oie(e,t,n,r){return new Promise(async a=>{let s=await R8([t.heatmapScores,t.offsets,t.displacementFwd,t.displacementBwd]),i=s[0],o=s[1],l=s[2],c=s[3],u=await C8(i,o,l,c,n.body.nmsRadius,n.body.maxDetections,n.body.scoreThreshold),h=hg(u,[e.shape[1],e.shape[2]],[r,r]);a(h)})}async function lie(e,t,n,r){return new Promise(async a=>{let s=await S8(t.heatmapScores,t.offsets,n.body.scoreThreshold),i=hg([s],[e.shape[1],e.shape[2]],[r,r]);a(i)})}var pg=class{constructor(t){this.baseModel=t,this.inputSize=t.model.inputs[0].shape[1],this.inputSize<128&&(this.inputSize=257)}async estimatePoses(t,n){let r=M8(t,[this.inputSize,this.inputSize]),a=this.baseModel.predict(r,n),s=n.body.maxDetections<2?await lie(t,a,n,this.inputSize):await oie(t,a,n,this.inputSize);return a.heatmapScores.dispose(),a.offsets.dispose(),a.displacementFwd.dispose(),a.displacementBwd.dispose(),r.dispose(),s}dispose(){this.baseModel.dispose()}};async function fg(e){Pi?e.debug&&ue("cached model:",Pi.modelUrl):(Pi=await ct(pt(e.modelBasePath,e.body.modelPath)),!Pi||!Pi.modelUrl?ue("load model failed:",e.body.modelPath):e.debug&&ue("load model:",Pi.modelUrl));let t=new rg(Pi);return new pg(t)}var xg={};br(xg,{HandPose:()=>bg,load:()=>_g});function F0(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function Kc(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function F8(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 ze.cropAndResize(t,s,[0],n)}function D8(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 D0(e,t=1.5){let n=Kc(e),r=F0(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 $0(e){let t=Kc(e),n=F0(e),a=Math.max(...n)/2,s=[t[0]-a,t[1]-a],i=[t[0]+a,t[1]+a];return{startPoint:s,endPoint:i,palmLandmarks:e.palmLandmarks}}var mg=class{constructor(t,n,r){this.model=t,this.anchors=r.map(a=>[a.x_center,a.y_center]),this.anchorsTensor=Tn(this.anchors),this.inputSize=n,this.inputSizeTensor=on([n,n]),this.doubleInputSizeTensor=on([n*2,n*2])}normalizeBoxes(t){return z(()=>{let n=Ee(t,[0,0],[-1,2]),r=Ee(t,[0,2],[-1,2]),a=se(me(n,this.inputSizeTensor),this.anchorsTensor),s=me(r,this.doubleInputSizeTensor),i=P(Ae(a,s),this.inputSizeTensor),o=P(se(a,s),this.inputSizeTensor);return pl([i,o],1)})}normalizeLandmarks(t,n){return z(()=>{let r=se(me(t.reshape([-1,7,2]),this.inputSizeTensor),this.anchors[n]);return P(r,this.inputSizeTensor)})}async getBoxes(t,n){let r=this.model.predict(t),a=r.squeeze();r.dispose();let s=z(()=>$n(Ee(a,[0,0],[-1,1])).squeeze()),i=s.dataSync(),o=Ee(a,[0,1],[-1,4]),l=this.normalizeBoxes(o);o.dispose();let c=await ze.nonMaxSuppressionAsync(l,i,n.hand.maxHands,n.hand.iouThreshold,n.hand.scoreThreshold),u=c.arraySync();s.dispose(),c.dispose();let h=[];for(let d of u)if(i[d]>=n.hand.minConfidence){let p=Ee(l,[d,0],[1,-1]),f=Ee(a,[d,5],[1,14]),m=z(()=>this.normalizeLandmarks(f,d).reshape([-1,2]));f.dispose(),h.push({box:p,palmLandmarks:m,confidence:i[d]})}return a.dispose(),l.dispose(),h}async estimateHandBounds(t,n){let r=t.shape[1],a=t.shape[2],s=z(()=>t.resizeBilinear([this.inputSize,this.inputSize]).div(127.5).sub(1)),i=await this.getBoxes(s,n);s.dispose();let o=[];if(!i||i.length===0)return o;for(let l of i){let c=l.box.dataSync(),u=c.slice(0,2),h=c.slice(2,4),d=l.palmLandmarks.arraySync();l.box.dispose(),l.palmLandmarks.dispose(),o.push(D8({startPoint:u,endPoint:h,palmLandmarks:d,confidence:l.confidence},[a/this.inputSize,r/this.inputSize]))}return o}};function uie(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function $8(e,t){let n=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return uie(n)}var O8=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function ns(e,t){let n=0;for(let r=0;ryg([...s,1],n)),a=this.calculateLandmarksBoundingBox(r);return D0($0(a),hie)}getBoxForHandLandmarks(t){let n=this.calculateLandmarksBoundingBox(t),r=D0($0(n),L8);r.palmLandmarks=[];for(let a=0;a[i[0]*(p[0]-this.inputSize/2),i[1]*(p[1]-this.inputSize/2),i[2]*p[2]]),l=Ag(r,[0,0]),c=o.map(p=>[...yg(p,l),p[2]]),u=P8(a),h=[...Kc(n),1],d=[ns(h,u[0]),ns(h,u[1])];return c.map(p=>[p[0]+d[0],p[1]+d[1],p[2]])}async estimateHands(t,n){let r=!1,a;(this.skipped===0||this.skipped>n.hand.skipFrames||!n.hand.landmarks||!n.videoOptimized)&&(a=await 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n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s}}};var 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V8=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPalm","rightPalm","leftIndex","rightIndex","leftPinky","rightPinky","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","midHip","forehead","leftThumb","leftHand","rightThumb","rightHand"],j8=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","left:15","right:16","left:17","right:18","left:19","right:20","left:21","right:22","leftChest","rightChest","neck","forehead","left:27","right:28","left:29","right:30"];var An;async function kg(e){return An?e.debug&&ue("cached model:",An.modelUrl):(An=await ct(pt(e.modelBasePath,e.body.modelPath)),An.width=parseInt(An.signature.inputs["input_1:0"].tensorShape.dim[2].size),An.height=parseInt(An.signature.inputs["input_1:0"].tensorShape.dim[1].size),!An||!An.modelUrl?ue("load model failed:",e.body.modelPath):e.debug&&ue("load model:",An.modelUrl)),An}async function Ig(e,t){if(!An||!t.body.enabled)return null;let n={width:e.shape[2],height:e.shape[1]},r=ze.resizeBilinear(e,[An.width,An.height],!1),a=me(r,[255]);r.dispose();let s;if(t.profile){let u=await sn(()=>An.predict(a));s=u.result.find(h=>h.size===195||h.size===155).dataSync(),u.result.forEach(h=>h.dispose()),mn("blazepose",u)}else{let u=await An.predict(a);s=u.find(h=>h.size===195||h.size===155).dataSync(),u.forEach(h=>h.dispose())}a.dispose();let i=[],o=s.length===195?V8:j8,l=5;for(let u=0;uh.score>u?h.score:u,0),keypoints:i}]}var 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t){a.font=r.font,a.strokeStyle=r.color,a.fillStyle=r.color,r.drawBoxes&&(r.useRawBoxes?tu(a,e.width*s.boxRaw[0],e.height*s.boxRaw[1],e.width*s.boxRaw[2],e.height*s.boxRaw[3],r):tu(a,s.box[0],s.box[1],s.box[2],s.box[3],r));let i=[];if(i.push(`face confidence: ${Math.trunc(100*s.confidence)}%`),s.genderConfidence&&i.push(`${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(" "))}s.rotation&&s.rotation.angle&&s.rotation.angle.roll&&i.push(`roll: ${Math.trunc(100*s.rotation.angle.roll)/100} yaw:${Math.trunc(100*s.rotation.angle.yaw)/100} pitch:${Math.trunc(100*s.rotation.angle.pitch)/100}`),i.length===0&&i.push("face"),a.fillStyle=r.color;for(let o=i.length-1;o>=0;o--){let l=Math.max(s.box[0],0),c=o*r.lineHeight+s.box[1];r.shadowColor&&r.shadowColor!==""&&(a.fillStyle=r.shadowColor,a.fillText(i[o],l+5,c+16)),a.fillStyle=r.labelColor,a.fillText(i[o],l+4,c+15)}if(a.lineWidth=1,s.mesh&&s.mesh.length>0){if(r.drawPoints)for(let o of s.mesh)B0(a,o[0],o[1],o[2],r);if(r.drawPolygons){a.lineWidth=1;for(let o=0;os.mesh[c]);Dg(a,l,r)}if(s.annotations&&s.annotations.leftEyeIris){a.strokeStyle=r.useDepth?"rgba(255, 200, 255, 0.3)":r.color,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(),r.fillPolygons&&(a.fillStyle=r.useDepth?"rgba(255, 255, 200, 0.3)":r.color,a.fill())}if(s.annotations&&s.annotations.rightEyeIris){a.strokeStyle=r.useDepth?"rgba(255, 200, 255, 0.3)":r.color,a.beginPath();let 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null});eh.set(this,async(t=!1)=>{if(this.config.backend&&this.config.backend.length>0&&t||this.tf.getBackend()!==this.config.backend){let n=Ye();if(this.state="backend",this.config.backend&&this.config.backend.length>0){if(this.tf.ENV.flags.IS_BROWSER&&this.config.backend==="tensorflow"&&(this.config.backend="webgl"),this.tf.ENV.flags.IS_NODE&&(this.config.backend==="webgl"||this.config.backend==="wasm")&&(this.config.backend="tensorflow"),this.config.debug&&ue("setting backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&ue("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let r=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),a=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&ue(`wasm execution: ${r?"SIMD":"no SIMD"} ${a?"multithreaded":"singlethreaded"}`),r||ue("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&r8();try{await this.tf.setBackend(this.config.backend)}catch(r){ue("error: cannot set backend:",this.config.backend,r)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"||this.tf.getBackend()==="humangl"){this.tf.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),this.tf.ENV.set("WEBGL_PACK_DEPTHWISECONV",!0),this.config.deallocate&&(ue("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let r=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&ue(`gl version:${r.getParameter(r.VERSION)} renderer:${r.getParameter(r.RENDERER)}`)}await this.tf.ready(),this.perf.backend=Math.trunc(Ye()-n)}});H0.set(this,async()=>{let t=(a,s="application/octet-stream")=>fetch(`data:${s};base64,${a}`).then(i=>i.blob()),n,r;switch(this.config.warmup){case"face":n=await t(V0);break;case"full":n=await t(j0);break;default:n=null}if(n){let a=await createImageBitmap(n);r=await this.detect(a,this.config),a.close()}return r});G0.set(this,async()=>new Promise(t=>{let n,r=0;switch(this.config.warmup){case"face":r=256,n="data:image/jpeg;base64,"+V0;break;case"full":case"body":r=1200,n="data:image/jpeg;base64,"+j0;break;default:n=null}let a=new Image;a.onload=async()=>{let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(r,r):document.createElement("canvas");s.width=a.naturalWidth,s.height=a.naturalHeight;let i=s.getContext("2d");i==null||i.drawImage(a,0,0);let o=await this.detect(s,this.config);t(o)},n?a.src=n:t(null)}));q0.set(this,async()=>{var i;let t=o=>Buffer.from(o,"base64"),n=this.config.warmup==="face"?t(V0):t(j0),r=(i=void 0)==null?void 0:i.decodeJpeg(n),a=r.expandDims(0);this.tf.dispose(r);let s=await this.detect(a,this.config);return this.tf.dispose(a),s});this.tf=kh,this.draw=Fg,this.version=ek,this.config=Yn(ht,t),this.state="idle",os(this,nu,0),os(this,Jc,!1),os(this,Qc,!1),os(this,Wi,!0),this.perf={},this.models={face:null,posenet:null,blazepose:null,efficientpose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null,faceres:null},this.image=n=>Mg(n,this.config),this.classes={facemesh:eg,age:R2,gender:F2,emotion:P2,faceres:U2,body:this.config.body.modelPath.includes("posenet")?dg:vg,hand:xg,nanodet:Tg},this.faceTriangulation=m8,this.faceUVMap=A8,this.sysinfo=Xg()}profileData(){return this.config.profile?m0:{}}similarity(t,n){return this.config.face.description.enabled?G2(t,n):this.config.face.embedding.enabled?a8(t,n):0}enhance(t){return q2(t)}match(t,n,r=0){return s8(t,n,r)}async load(t={}){this.state="load";let n=Ye();t&&(this.config=Yn(this.config,t)),ir(this,Wi)&&(this.config.debug&&ue(`version: ${this.version}`),this.config.debug&&ue(`tfjs version: ${this.tf.version_core}`),this.config.debug&&ue("platform:",this.sysinfo.platform),this.config.debug&&ue("agent:",this.sysinfo.agent),await ir(this,eh).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&ue("configuration:",this.config),this.config.debug&&ue("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.efficientpose,this.models.nanodet,this.models.faceres]=await Promise.all([this.models.face||(this.config.face.enabled?ng(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?M2(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?z2(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?B2(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?V2(this.config):null),this.models.handpose||(this.config.hand.enabled?_g(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?fg(this.config):null),this.models.blazepose||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?kg(this.config):null),this.models.efficientpose||(this.config.body.enabled&&this.config.body.modelPath.includes("efficientpose")?Ng(this.config):null),this.models.nanodet||(this.config.object.enabled?Cg(this.config):null),this.models.faceres||(this.config.face.enabled&&this.config.face.description.enabled?H2(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await ng(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await M2(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await z2(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await B2(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await V2(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await _g(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await fg(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await kg(this.config)),this.config.body.enabled&&!this.models.efficientpose&&this.config.body.modelPath.includes("efficientpose")&&(this.models.efficientpose=await Ng(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await Cg(this.config)),this.config.face.enabled&&this.config.face.description.enabled&&!this.models.faceres&&(this.models.faceres=await H2(this.config))),ir(this,Wi)&&(this.config.debug&&ue("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),os(this,Wi,!1));let r=Math.trunc(Ye()-n);r>(this.perf.load||0)&&(this.perf.load=r)}async detect(t,n={}){return new Promise(async r=>{var A,y,g,w;this.state="config";let a;this.config=Yn(this.config,n),this.state="check";let s=ir(this,U0).call(this,t);s&&(ue(s,t),r({error:s}));let i=Ye();await ir(this,eh).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),this.analyze("Start Scope:");let o;t&&this.config.videoOptimized&&(t instanceof HTMLImageElement||t instanceof Image||t instanceof ImageData||t instanceof ImageBitmap||t instanceof We)&&(ue("disabling video optimization"),o=this.config.videoOptimized,this.config.videoOptimized=!1),a=Ye();let l=Mg(t,this.config);if(!l||!l.tensor){ue("could not convert input to tensor"),r({error:"could not convert input to tensor"});return}this.perf.image=Math.trunc(Ye()-a),this.analyze("Get Image:");let c,u,h,d,p;this.config.async?(h=this.config.face.enabled?X2(this,l.tensor):[],this.perf.face&&delete this.perf.face):(this.state="run:face",a=Ye(),h=this.config.face.enabled?await X2(this,l.tensor):[],p=Math.trunc(Ye()-a),p>0&&(this.perf.face=p)),this.analyze("Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?c=this.config.body.enabled?(A=this.models.posenet)==null?void 0:A.estimatePoses(l.tensor,this.config):[]:this.config.body.modelPath.includes("blazepose")?c=this.config.body.enabled?Ig(l.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(c=this.config.body.enabled?Sg(l.tensor,this.config):[]),this.perf.body&&delete this.perf.body):(this.state="run:body",a=Ye(),this.config.body.modelPath.includes("posenet")?c=this.config.body.enabled?await((y=this.models.posenet)==null?void 0:y.estimatePoses(l.tensor,this.config)):[]:this.config.body.modelPath.includes("blazepose")?c=this.config.body.enabled?await Ig(l.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(c=this.config.body.enabled?await Sg(l.tensor,this.config):[]),p=Math.trunc(Ye()-a),p>0&&(this.perf.body=p)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(u=this.config.hand.enabled?(g=this.models.handpose)==null?void 0:g.estimateHands(l.tensor,this.config):[],this.perf.hand&&delete this.perf.hand):(this.state="run:hand",a=Ye(),u=this.config.hand.enabled?await((w=this.models.handpose)==null?void 0:w.estimateHands(l.tensor,this.config)):[],p=Math.trunc(Ye()-a),p>0&&(this.perf.hand=p)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.config.async?(d=this.config.object.enabled?Rg(l.tensor,this.config):[],this.perf.object&&delete this.perf.object):(this.state="run:object",a=Ye(),d=this.config.object.enabled?await Rg(l.tensor,this.config):[],p=Math.trunc(Ye()-a),p>0&&(this.perf.object=p)),this.analyze("End Object:"),this.config.async&&([h,c,u,d]=await Promise.all([h,c,u,d])),_e(l.tensor),this.config.scoped&&this.tf.engine().endScope(),this.analyze("End Scope:");let f=[];this.config.gesture.enabled&&(a=Ye(),f=[...H8(h),...U8(c),...q8(u),...G8(h)],this.config.async?this.perf.gesture&&delete this.perf.gesture:this.perf.gesture=Math.trunc(Ye()-a)),o&&(this.config.videoOptimized=o),this.perf.total=Math.trunc(Ye()-i),this.state="idle";let m={face:h,body:c,hand:u,gesture:f,object:d,performance:this.perf,canvas:l.canvas};r(m)})}async warmup(t={}){let n=Ye();t&&(this.config=Yn(this.config,t));let r=this.config.videoOptimized;this.config.videoOptimized=!1;let a;typeof createImageBitmap=="function"?a=await ir(this,H0).call(this):typeof Image!="undefined"?a=await ir(this,G0).call(this):a=await ir(this,q0).call(this),this.config.videoOptimized=r;let s=Ye();return this.config.debug&&ue("Warmup",this.config.warmup,Math.round(s-n),"ms",a),a}};nu=new WeakMap,Jc=new WeakMap,Qc=new WeakMap,Wi=new WeakMap,U0=new WeakMap,eh=new WeakMap,H0=new WeakMap,G0=new WeakMap,q0=new WeakMap;export{bie as Human,bie as default}; /** * @license * Copyright 2017 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ /** * @license * Copyright 2018 Google LLC * * Use of this source code is governed by an MIT-style * license that can be found in the LICENSE file or at * https://opensource.org/licenses/MIT. * ============================================================================= */ /** * @license * Copyright 2018 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * * ============================================================================= */ /** * @license * Copyright 2018 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ /** * @license * Copyright 2019 Google LLC * * Use of this source code is governed by an MIT-style * license that can be found in the LICENSE file or at * https://opensource.org/licenses/MIT. * ============================================================================= */ /** * @license * Copyright 2019 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * * ============================================================================= */ /** * @license * Copyright 2019 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ /** * @license * Copyright 2020 Google Inc. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ /** * @license * Copyright 2020 Google LLC * * Use of this source code is governed by an MIT-style * license that can be found in the LICENSE file or at * https://opensource.org/licenses/MIT. * ============================================================================= */ /** * @license * Copyright 2020 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ /** * @license * Copyright 2020 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the License); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an AS IS BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ /** * @license * Copyright 2021 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ /** @license See the LICENSE file. */ //# sourceMappingURL=human.esm.js.map