"use strict";/*
  Human
  homepage: <https://github.com/vladmandic/human>
  author: <https://github.com/vladmandic>'
*/

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s=++this.pendingBackendInitId,r=n.then(a=>s<this.pendingBackendInitId?!1:(this.registry[e]=a,this.pendingBackendInit=null,!0)).catch(a=>(s<this.pendingBackendInitId||(this.pendingBackendInit=null,Va(`Initialization of backend ${e} failed`),Va(a.stack||a.message)),!1));return this.pendingBackendInit=r,{success:r,asyncInit:!0}}else return this.registry[e]=n,{success:!0,asyncInit:!1}}catch(n){return Va(`Initialization of backend ${e} failed`),Va(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw new Error(`${e} backend not found in registry`);this.backendName===e&&this.pendingBackendInit!=null&&this.pendingBackendInitId++,e in this.registry&&(this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e]),delete this.registryFactory[e],this.backendName===e&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)}getSortedBackends(){if(Object.keys(this.registryFactory).length===0)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((e,t)=>this.registryFactory[t].priority-this.registryFactory[e].priority)}initializeBackendsAndReturnBest(){let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let n=e[t],{success:s,asyncInit:r}=this.initializeBackend(n);if(r||s)return{name:n,asyncInit:r}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){let n=this.state.tensorInfo.get(t),s=n.backend,r=this.readSync(t),a=s.refCount(t);s.disposeData(t,!0),n.backend=e,e.move(t,r,n.shape,n.dtype,a),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(e,t){let n=null;if(t==null){if(typeof e!="function")throw new Error("Please provide a function to tidy()");t=e}else{if(typeof e!="string"&&!(e instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if(typeof t!="function")throw new 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s=this.backend.numDataIds(),r=0;n.forEach(i=>{r+=i.dtype==="complex64"?3:1});let a=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],o=s-t-r-a;if(o>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${o} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[],s=this.isTapeOn(),r=this.state.numBytes,a=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let o;this.backendName==null&&this.backend;let i,l=s3(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(s3(e)){let{kernelName:h,inputs:f,attrs:m}=e;this.backendName==null&&this.backend;let g=hm(h,this.backendName);M(g!=null,()=>`Cannot find registered kernel '${h}' for backend '${this.backendName}'`),o=()=>{let y=this.backend.numDataIds();i=g.kernelFunc({inputs:f,attrs:m,backend:this.backend});let x=Array.isArray(i)?i:[i];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(h,y,x);let A=x.map(b=>b.rank!=null?b:this.makeTensorFromTensorInfo(b));if(s){let b=this.getTensorsForGradient(h,f,A);n=this.saveTensorsForBackwardMode(b)}return A}}else{let{forwardFunc:h}=e,f=m=>{!s||(n=m.map(g=>this.keep(this.clone(g))))};o=()=>{let m=this.backend.numDataIds();i=this.tidy(()=>h(this.backend,f));let g=Array.isArray(i)?i:[i];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,m,g),g}}let{inputs:u,attrs:c}=e,p=s3(e)?null:e.backwardsFunc,d;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=o():(d=this.profiler.profileKernel(l,u,()=>o()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs)}),s&&this.addTapeNode(l,u,t,p,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-r,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-a,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map(h=>u[h]!=null?u[h].shape:null),outputShapes:t.map(h=>h.shape),kernelTimeMs:d.timeMs,extraInfo:d.extraInfo}),Array.isArray(i)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(n=>this.keep(this.clone(n)))}getTensorsForGradient(e,t,n){let s=m3(e);if(s!=null){let r=s.inputsToSave||[],a=s.outputsToSave||[],o;s.saveAllInputs?(M(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),o=Object.keys(t).map(l=>t[l])):o=r.map(l=>t[l]);let 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this.state.registeredVariables[r.name]=r,this.incRef(r,this.backend),r}trackTensor(e,t){this.state.numTensors++,e.dtype==="string"&&this.state.numStringTensors++;let n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*f3(e.dtype)),this.state.numBytes+=n,this.state.tensorInfo.has(e.dataId)||(this.state.numDataBuffers++,this.state.tensorInfo.set(e.dataId,{backend:t||this.backend,dtype:e.dtype,shape:e.shape,bytes:n})),e instanceof wp||this.track(e)}incRef(e,t){this.trackTensor(e,t),this.backend.incRef(e.dataId)}removeDataId(e,t){this.state.tensorInfo.has(e)&&this.state.tensorInfo.get(e).backend===t&&(this.state.tensorInfo.delete(e),this.state.numDataBuffers--)}disposeTensor(e){if(!this.state.tensorInfo.has(e.dataId))return;let t=this.state.tensorInfo.get(e.dataId);if(this.state.numTensors--,e.dtype==="string"&&(this.state.numStringTensors--,this.state.numBytes-=t.bytes),e.dtype!=="complex64"&&e.dtype!=="string"){let n=e.size*f3(e.dtype);this.state.numBytes-=n}t.backend.disposeData(e.dataId)&&this.removeDataId(e.dataId,t.backend)}disposeVariables(){for(let e in this.state.registeredVariables){let t=this.state.registeredVariables[e];this.disposeVariable(t)}}disposeVariable(e){this.disposeTensor(e),this.state.registeredVariables[e.name]!=null&&delete this.state.registeredVariables[e.name]}memory(){let e=this.backend.memory();return e.numTensors=this.state.numTensors,e.numDataBuffers=this.state.numDataBuffers,e.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(e.unreliable=!0,e.reasons==null&&(e.reasons=[]),e.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),e}async profile(e){this.state.profiling=!0;let t=this.state.numBytes,n=this.state.numTensors;this.state.activeProfile.kernels=[],this.state.activeProfile.result=await e(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max(...this.state.activeProfile.kernels.map(s=>s.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-n;for(let s of this.state.activeProfile.kernels)s.kernelTimeMs=await s.kernelTimeMs,s.extraInfo=await s.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>0&&this.state.kernelDepth===0}addTapeNode(e,t,n,s,r,a){let o={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:n,saved:r},i=m3(e);i!=null&&(s=i.gradFunc),s!=null&&(o.gradient=l=>(l=l.map((u,c)=>{if(u==null){let p=n[c],d=Vm(p.size,p.dtype);return this.makeTensor(d,p.shape,p.dtype)}return u}),s(l.length>1?l:l[0],r,a))),this.state.activeTape.push(o)}keep(e){return e.kept=!0,e}startTape(){this.state.gradientDepth===0&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(e){let t={track:[],name:"unnamed scope",id:this.state.nextScopeId++};e&&(t.name=e),this.state.scopeStack.push(t),this.state.activeScope=t}endScope(e){let t=Sy(e),n=new Set(t.map(r=>r.id));for(let r=0;r<this.state.activeScope.track.length;r++){let a=this.state.activeScope.track[r];!a.kept&&!n.has(a.id)&&a.dispose()}let s=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(r=>{!r.kept&&r.scopeId===s.id&&this.track(r)})}gradients(e,t,n,s=!1){if(M(t.length>0,()=>"gradients() received an empty list of xs."),n!=null&&n.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);let r=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));M(r instanceof tt,()=>"The result y returned by f() must be a tensor.");let a=rD(this.state.activeTape,t,r);if(!s&&a.length===0&&t.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.");return this.tidy("backward",()=>{let o={};o[r.id]=n==null?mD(r.shape):n,aD(o,a,l=>this.tidy(l),gD);let i=t.map(l=>o[l.id]);return this.state.gradientDepth===0&&(this.state.activeTape.forEach(l=>{for(let u of l.saved)u.dispose()}),this.state.activeTape=null),{value:r,grads:i}})}customGrad(e){return M(Za(e),()=>"The f passed in customGrad(f) must be a function."),(...t)=>{M(t.every(o=>o instanceof tt),()=>"The args passed in customGrad(f)(x1, x2,...) must all be tensors");let n,s={};t.forEach((o,i)=>{s[i]=o});let r=(o,i)=>(n=e(...t,i),M(n.value instanceof tt,()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"),M(Za(n.gradFunc),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."),n.value),a=(o,i)=>{let l=n.gradFunc(o,i),u=Array.isArray(l)?l:[l];M(u.length===t.length,()=>"The function f passed in customGrad(f) must 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sw=V({basicLSTMCell_:_P});function DP(e,t,n){let s=D(e,"x","batchToSpaceND"),r=t.reduce((i,l)=>i*l);M(s.rank>=1+t.length,()=>`input rank is ${s.rank} but should be > than blockShape.length ${t.length}`),M(n.length===t.length,()=>`crops.length is ${n.length} but should be equal to blockShape.length  ${t.length}`),M(s.shape[0]%r===0,()=>`input tensor batch is ${s.shape[0]} but is not divisible by the product of the elements of blockShape ${t.join(" * ")} === ${r}`);let a={x:s},o={blockShape:t,crops:n};return W.runKernel(il,a,o)}var lh=V({batchToSpaceND_:DP});function $P(e){let t;return e.rank===0||e.rank===1?t=U(e,[1,1,1,e.size]):e.rank===2?t=U(e,[1,1,e.shape[0],e.shape[1]]):e.rank===3?t=U(e,[1,e.shape[0],e.shape[1],e.shape[2]]):t=e,t}function PP(e,t,n,s,r,a){a==null&&(a=.001);let o=D(e,"x","batchNorm"),i=D(t,"mean","batchNorm"),l=D(n,"variance","batchNorm"),u;r!=null&&(u=D(r,"scale","batchNorm"));let c;s!=null&&(c=D(s,"offset","batchNorm")),M(i.rank===l.rank,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),M(c==null||i.rank===c.rank,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),M(u==null||i.rank===u.rank,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let d={x:$P(o),scale:u,offset:c,mean:i,variance:l},h={varianceEpsilon:a},f=W.runKernel(No,d,h);return U(f,o.shape)}var Bc=V({batchNorm_:PP});function FP(e,t,n,s,r,a){let o=D(e,"x","batchNorm"),i=D(t,"mean","batchNorm"),l=D(n,"variance","batchNorm"),u;r!=null&&(u=D(r,"scale","batchNorm"));let c;return s!=null&&(c=D(s,"offset","batchNorm")),M(o.rank===2,()=>`Error in batchNorm2D: x must be rank 2 but got rank ${o.rank}.`),M(i.rank===2||i.rank===1,()=>`Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank ${i.rank}.`),M(l.rank===2||l.rank===1,()=>`Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank ${l.rank}.`),u!=null&&M(u.rank===2||u.rank===1,()=>`Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank ${u.rank}.`),c!=null&&M(c.rank===2||c.rank===1,()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${c.rank}.`),Bc(o,i,l,c,u,a)}var tA=V({batchNorm2d_:FP});function OP(e,t,n,s,r,a){let o=D(e,"x","batchNorm"),i=D(t,"mean","batchNorm"),l=D(n,"variance","batchNorm"),u;r!=null&&(u=D(r,"scale","batchNorm"));let c;return s!=null&&(c=D(s,"offset","batchNorm")),M(o.rank===3,()=>`Error in batchNorm3D: x must be rank 3 but got rank ${o.rank}.`),M(i.rank===3||i.rank===1,()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${i.rank}.`),M(l.rank===3||l.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${l.rank}.`),u!=null&&M(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${u.rank}.`),c!=null&&M(c.rank===3||c.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${c.rank}.`),Bc(o,i,l,c,u,a)}var nA=V({batchNorm3d_:OP});function MP(e,t,n,s,r,a){let o=D(e,"x","batchNorm"),i=D(t,"mean","batchNorm"),l=D(n,"variance","batchNorm"),u;r!=null&&(u=D(r,"scale","batchNorm"));let c;return s!=null&&(c=D(s,"offset","batchNorm")),M(o.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${o.rank}.`),M(i.rank===4||i.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${i.rank}.`),M(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${l.rank}.`),u!=null&&M(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${u.rank}.`),c!=null&&M(c.rank===4||c.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${c.rank}.`),Bc(o,i,l,c,u,a)}var sA=V({batchNorm4d_:MP});function zP(e,t,n){let s=D(e,"x","bincount"),r=D(t,"weights","bincount");M(s.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${s.dtype}`),M(n>=0,()=>`size must be non-negative, but got ${n}.`),M(r.size===s.size||r.size===0,()=>`Error in bincount: weights must have the same size as input or0-length, but got input shape: ${s.shape}, weights shape: ${r.shape}.`);let a={x:s,weights:r},o={size:n};return W.runKernel(Hm,a,o)}var rA=V({bincount_:zP});function LP(e,t){let n=D(e,"s0","broadcastArgs","int32"),s=D(t,"s1","broadcastArgs","int32");if(n.rank!==1)throw new Error(`broadcastArgs(): first input must be a vector (rank=1). Has rank ${n.rank}`);if(s.rank!==1)throw new Error(`broadcastArgs(): second input must be a vector (rank=1). Has rank ${s.rank}`);let r={s0:n,s1:s};return W.runKernel(jm,r)}var rw=V({broadcastArgs_:LP});function BP(e,t){let n=D(e,"broadcastTo","x"),s=n.shape;if(t.some(u=>!(u>0)||u%1!==0))throw new Error(`broadcastTo(): Invalid broadcast shape [${t}].`);if(t.length<n.rank)throw new Error(`broadcastTo(): shape.length=${t.length} < input.rank=${n.rank}.`);if(t.length>n.rank){let u=n.shape.slice();for(;u.length<t.length;)u.unshift(1);n=U(n,u)}let r=n.shape,a=Array.from(t);for(let u=t.length-1;u>=0;u--)if(r[u]===t[u])a[u]=1;else if(n.shape[u]!==1)throw new Error(`broadcastTo(): [${s}] cannot be broadcast to [${t}].`);if(a.map((u,c)=>u>1?c:-1).filter(u=>u>=0).length===0)return Fn(n);let i={x:n},l={reps:a};return W.runKernel(ba,i,l)}var Uu=V({broadcastTo_:BP});function WP(e){let n={x:D(e,"x","ceil","float32")};return W.runKernel(go,n)}var aA=V({ceil_:WP});function VP(e,t,n){let s=D(e,"x","clipByValue");M(t<=n,()=>`Error in clip: min (${t}) must be less than or equal to max (${n}).`);let r={x:s},a={clipValueMin:t,clipValueMax:n};return W.runKernel(xa,r,a)}var fs=V({clipByValue_:VP});function UP(e){return Ct(e,0)}var oA=V({concat1d_:UP});function GP(e,t){return Ct(e,t)}var Xl=V({concat2d_:GP});function HP(e,t){return Ct(e,t)}var iA=V({concat3d_:HP});function jP(e,t){return Ct(e,t)}var lA=V({concat4d_:jP});function qP(e,t,n,s,r="NHWC",a=[1,1],o){let i=D(e,"x","conv2d","float32"),l=D(t,"filter","conv2d","float32"),u=i,c=!1;i.rank===3&&(c=!0,u=U(i,[1,i.shape[0],i.shape[1],i.shape[2]])),M(u.rank===4,()=>`Error in conv2d: input must be rank 4, but got rank ${u.rank}.`),M(l.rank===4,()=>`Error in conv2d: filter must be rank 4, but got rank ${l.rank}.`),rs("conv2d",s,o);let p=r==="NHWC"?u.shape[3]:u.shape[1];M(p===l.shape[2],()=>`Error in conv2d: depth of input (${p}) must match input depth for filter ${l.shape[2]}.`),M(Zr(n,a),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`);let d={x:u,filter:l},h={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:o},f=W.runKernel(yo,d,h);return c?U(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var fa=V({conv2d_:qP});function XP(e,t,n,s,r="NWC",a=1,o){let i=D(e,"x","conv1d"),l=D(t,"filter","conv1d"),u=i,c=!1;i.rank===2&&(c=!0,u=U(i,[1,i.shape[0],i.shape[1]])),M(u.rank===3,()=>`Error in conv1d: input must be rank 3, but got rank ${u.rank}.`),M(l.rank===3,()=>`Error in conv1d: filter must be rank 3, but got rank ${l.rank}.`),rs("conv1d",s,o),M(u.shape[2]===l.shape[1],()=>`Error in conv1d: depth of input (${u.shape[2]}) must match input depth for filter ${l.shape[1]}.`),M(Zr(n,a),()=>`Error in conv1D: Either stride or dilation must be 1. Got stride ${n} and dilation '${a}'`),M(r==="NWC",()=>`Error in conv1d: got dataFormat of ${r} but only NWC is currently supported.`);let p=U(l,[1,l.shape[0],l.shape[1],l.shape[2]]),d=U(u,[u.shape[0],1,u.shape[1],u.shape[2]]),g=fa(d,p,[1,n],s,"NHWC",[1,a],o);return c?U(g,[g.shape[2],g.shape[3]]):U(g,[g.shape[0],g.shape[2],g.shape[3]])}var g0=V({conv1d_:XP});function KP(e,t,n,s,r,a="NHWC",o){M(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let i=e,l=t,u=!1;t.rank===3&&(u=!0,l=U(t,[1,t.shape[0],t.shape[1],t.shape[2]]),i=[1,e[0],e[1],e[2]]),M(i.length===4,()=>`Error in conv2dDerInput: inShape must be length 4, but got length ${i.length}.`),M(l.rank===4,()=>`Error in conv2dDerInput: dy must be rank 4, but got rank ${l.rank}`),M(n.rank===4,()=>`Error in conv2dDerInput: filter must be rank 4, but got rank ${n.rank}`);let c=a==="NHWC"?i[3]:i[1],p=a==="NHWC"?l.shape[3]:l.shape[1];M(c===n.shape[2],()=>`Error in conv2dDerInput: depth of input (${c}) must match input depth for filter ${n.shape[2]}.`),M(p===n.shape[3],()=>`Error in conv2dDerInput: depth of output (${p}) must match output depth for filter ${n.shape[3]}.`),rs("conv2dDerInput",r,o);let d={dy:l,filter:n},h={strides:s,pad:r,dataFormat:a,dimRoundingMode:o,inputShape:i},f=W.runKernel(Ao,d,h);return u?U(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var uA=V({conv2DBackpropInput_:KP});function ZP(e,t,n,s,r,a){let o=D(e,"x","conv2dTranspose"),i=D(t,"filter","conv2dTranspose");return uA(n,o,i,s,r,"NHWC",a)}var y0=V({conv2dTranspose_:ZP});function YP(e,t,n,s,r="NDHWC",a=[1,1,1]){let o=D(e,"x","conv3d"),i=D(t,"filter","conv3d"),l=o,u=!1;o.rank===4&&(u=!0,l=U(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),M(l.rank===5,()=>`Error in conv3d: input must be rank 5, but got rank ${l.rank}.`),M(i.rank===5,()=>`Error in conv3d: filter must be rank 5, but got rank ${i.rank}.`),M(l.shape[4]===i.shape[3],()=>`Error in conv3d: depth of input (${l.shape[4]}) must match input depth for filter ${i.shape[3]}.`),M(Zr(n,a),()=>`Error in conv3D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`),M(r==="NDHWC",()=>`Error in conv3d: got dataFormat of ${r} but only NDHWC is currently supported.`);let c={x:l,filter:i},p={strides:n,pad:s,dataFormat:r,dilations:a},d=W.runKernel(Bp,c,p);return u?U(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var cA=V({conv3d_:YP});function JP(e,t,n,s,r){M(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let a=e,o=t,i=!1;t.rank===4&&(i=!0,o=U(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]]),a=[1,e[0],e[1],e[2],e[3]]);let l=a[4],u=o.shape[4];M(a.length===5,()=>`Error in conv3dDerInput: inShape must be length 5, but got length ${a.length}.`),M(o.rank===5,()=>`Error in conv3dDerInput: dy must be rank 5, but got rank ${o.rank}`),M(n.rank===5,()=>`Error in conv3dDerInput: filter must be rank 5, but got rank ${n.rank}`),M(l===n.shape[3],()=>`Error in conv3dDerInput: depth of input (${l}) must match input depth for filter ${n.shape[3]}.`),M(u===n.shape[4],()=>`Error in conv3dDerInput: depth of output (${u}) must match output depth for filter ${n.shape[4]}.`);let c={dy:o,filter:n},p={pad:r,strides:s,inputShape:a},d=W.runKernel(Km,c,p);return i?U(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var aw=V({conv3DBackpropInput_:JP});function QP(e,t,n,s,r){let a=D(e,"x","conv3dTranspose"),o=D(t,"filter","conv3dTranspose");return aw(n,a,o,s,r)}var dA=V({conv3dTranspose_:QP});function eF(e){let n={x:D(e,"x","cos","float32")};return W.runKernel(xo,n)}var uh=V({cos_:eF});function tF(e){let n={x:D(e,"x","cosh","float32")};return W.runKernel(bo,n)}var A0=V({cosh_:tF});function nF(e,t=0,n=!1,s=!1){let a={x:D(e,"x","cumprod")},o={axis:t,exclusive:n,reverse:s};return W.runKernel(ul,a,o)}var Cp=V({cumprod_:nF});function sF(e,t=0,n=!1,s=!1){let a={x:D(e,"x","cumsum")},o={axis:t,exclusive:n,reverse:s};return W.runKernel(vo,a,o)}var x0=V({cumsum_:sF});function rF(e,t,n,s=!1){let r=D(e,"x","denseBincount"),a=D(t,"weights","denseBincount");M(r.dtype==="int32",()=>`Error in denseBincount: input dtype must be int32, but got ${r.dtype}`),M(r.rank<=2,()=>`Error in denseBincount: input must be at most rank 2, but got rank ${r.rank}.`),M(n>=0,()=>`size must be non-negative, but got ${n}.`),M(a.size===r.size||a.size===0,()=>`Error in denseBincount: weights must have the same shape as x or 0-length, but got x shape: ${r.shape}, weights shape: ${a.shape}.`);let o={x:r,weights:a},i={size:n,binaryOutput:s};return W.runKernel(Zm,o,i)}var ow=V({denseBincount_:rF});function aF(e,t,n="NHWC"){let s=D(e,"x","depthToSpace","float32"),r=n==="NHWC"?s.shape[1]:s.shape[2],a=n==="NHWC"?s.shape[2]:s.shape[3],o=n==="NHWC"?s.shape[3]:s.shape[1];M(t>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${t}`),M(r*t>=0,()=>`Negative dimension size caused by overflow when multiplying
    ${r} and ${t}  for depthToSpace with input shape
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m=ce(L(pe(h,ce(Nn(f),this.epsilon)),-this.learningRate),o);o.assign(m)}),this.accBeta1.assign(L(this.accBeta1,this.beta1)),this.accBeta2.assign(L(this.accBeta2,this.beta2))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),this.accumulatedFirstMoment!=null&&ne(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedSecondMoment!=null&&ne(this.accumulatedSecondMoment.map(e=>e.variable))}async getWeights(){let e=[...this.accumulatedFirstMoment,...this.accumulatedSecondMoment];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e),J(()=>{this.accBeta1.assign(ga(this.beta1,this.iterations_+1)),this.accBeta2.assign(ga(this.beta2,this.iterations_+1))});let 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Error("getWeights() is not implemented for Adamax yet.")}async setWeights(e){throw new Error("setWeights() is not implemented for Adamax yet.")}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon,t.decay)}};X0.className="Adamax";oi(X0);var bh=class extends wa{constructor(e){super(),this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,s)=>{let r=Array.isArray(e)?e[s].tensor:e[n];if(r==null)return;let a=W.registeredVariables[n];J(()=>{let o=ce(L(this.c,r),a);a.assign(o)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=bn(Se(-e))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(e){if(e=await this.extractIterations(e),e.length!==0)throw new Error("SGD optimizer does 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Input received: ${e}`);for(let n=0;n<e.length;n++){let s=e[n],r=t[n];if(r==null)continue;let a=s.rank;if(r.ndim!=null&&a!==r.ndim)throw new j(`Input ${n} is incompatible with layer ${this.name}: expected ndim=${r.ndim}, found ndim=${a}`);if(r.maxNDim!=null&&a>r.maxNDim)throw new j(`Input ${n} is incompatible with layer ${this.name}: expected max_ndim=${r.maxNDim}, found ndim=${a}`);if(r.minNDim!=null&&a<r.minNDim)throw new j(`Input ${n} is incompatible with layer ${this.name}: expected min_ndim=${r.minNDim}, found ndim=${a}.`);if(r.dtype!=null&&s.dtype!==r.dtype)throw new j(`Input ${n} is incompatible with layer ${this.name} : expected dtype=${r.dtype}, found dtype=${s.dtype}.`);if(r.axes){let o=s.shape;for(let i in r.axes){let l=Number(i),u=r.axes[i],c=l>=0?o[l]:o[o.length+l];if(u!=null&&[u,null].indexOf(c)===-1)throw new j(`Input ${n} is incompatible with layer ${this.name}: expected axis ${l} of input shape to have value ${u} but got shape ${o}.`)}}if(r.shape!=null)for(let o=0;o<r.shape.length;++o){let i=r.shape[o],l=s.shape[o];if(i!=null&&l!=null&&i!==l)throw new j(`Input ${n} is incompatible with layer ${this.name}: expected shape=${r.shape}, found shape=${s.shape}.`)}}}call(e,t){return e}invokeCallHook(e,t){this._callHook!=null&&this._callHook(e,t)}setCallHook(e){this._callHook=e}clearCallHook(){this._callHook=null}apply(e,t){t=t||{},this.assertNotDisposed();let n=_t(e),s=!0;for(let a of n)if(!(a instanceof Cr)){s=!1;break}let r=!0;for(let a of n)if(a instanceof Cr){r=!1;break}if(s===r)throw new j("Arguments to apply() must be all SymbolicTensors or all Tensors");return Gi(this.name,()=>{if(!this.built){this.assertInputCompatibility(e);let a=[];for(let o of _t(e))a.push(o.shape);this.build(ps(a)),this.built=!0,this.initialWeights&&this.setWeights(this.initialWeights),this._refCount===null&&r&&(this._refCount=1)}if(this.assertInputCompatibility(e),r){let a=this.call(e,t),o=_t(a),i=[];for(let l of o)n.indexOf(l)!==-1&&(l=l.clone()),i.push(l);if(a=ps(i),this.activityRegularizer!=null)throw new He("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return a}else{let a=FV(e),o=this.computeOutputShape(a),i,l=OV(e);if(this.warnOnIncompatibleInputShape(Array.isArray(e)?a[0]:a),o!=null&&o.length>0&&Array.isArray(o[0])?i=o.map((u,c)=>new Cr(l,u,this,_t(e),t,this.name,c)):i=new Cr(l,o,this,_t(e),t,this.name),this.addInboundNode(e,i,null,null,a,o,t),this._refCount++,this.activityRegularizer!=null)throw new He("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return i}})}warnOnIncompatibleInputShape(e){if(this.batchInputShape!=null)if(e.length!==this.batchInputShape.length)console.warn(`The rank of the input tensor provided (shape: ${JSON.stringify(e)}) does not match that of the batchInputShape (${JSON.stringify(this.batchInputShape)}) of the layer ${this.name}`);else{let t=!1;this.batchInputShape.forEach((n,s)=>{n!=null&&e[s]!=null&&e[s]!==n&&(t=!0)}),t&&console.warn(`The shape of the input tensor (${JSON.stringify(e)}) does not match the expectation of layer ${this.name}: ${JSON.stringify(this.batchInputShape)}`)}}get outputShape(){if(this.inboundNodes==null||this.inboundNodes.length===0)throw new ia(`The layer ${this.name} has never been called and thus has no defined output shape.`);let e=[];for(let t of this.inboundNodes){let n=JSON.stringify(t.outputShapes);e.indexOf(n)===-1&&e.push(n)}if(e.length===1){let t=this.inboundNodes[0].outputShapes;return Array.isArray(t)&&Array.isArray(t[0])&&t.length===1?t[0]:t}else throw new ia(`The layer ${this.name} has multiple inbound nodes with different output shapes. 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Its own _trainableWeights must remain an empty Array.");if(!this.trainable)return[];let e=[];for(let t of this.layers)e=e.concat(t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.layers)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.layers)t.push(...n.trainableWeights);return t.concat(e)}return e}get weights(){return this.trainableWeights.concat(this.nonTrainableWeights)}loadWeights(e,t=!0){let n={},s=0;for(let a of this.layers)for(let o of a.weights){if(n[o.originalName]!=null)throw new j(`Duplicate weight name: ${o.originalName}`);n[o.originalName]=o,s++}let r=[];for(let a in e){let o=a;if(n[a]==null){let i=a.split("/");o=i.slice(0,-2).concat([i[i.length-1]]).join("/")}if(n[o]!=null)r.push([n[o],e[a]]);else if(t)throw new j(`Provided weight data has no target variable: ${a}`);delete n[o]}if(t){let a=[];for(let o in n)a.push(o);if(a.length>0)throw new j(`${a.length} of ${s} weights are not set: ${a}`)}r5(r)}updatedConfig(){let e=this.getConfig(),t={};return t.className=this.getClassName(),t.config=e,t.kerasVersion=`tfjs-layers ${f5}`,t.backend="TensorFlow.js",t}toJSON(e,t=!0){let n=M3(this.updatedConfig());return t?JSON.stringify(n):n}call(e,t){return J(()=>{e=_t(e);let n=new Wi;for(let s=0;s<this.inputs.length;++s)n.add(this.inputs[s],e[s]);return rp(this.outputs,n,t)})}computeMask(e,t){return J(()=>{e=_t(e);let n;return t==null?n=Qi(null,e.length):n=_t(t),this.runInternalGraph(e,n)[1]})}computeOutputShape(e){let t=Am(e);if(t.length!==this.inputLayers.length)throw new j(`Invalid inputShape argument ${e}: model has ${this.inputLayers.length} tensor inputs.`);let n={};for(let o=0;o<t.length;o++){let i=this.inputLayers[o],l=t[o],u=i.name+"_0_0";n[u]=l}let s=Object.keys(this.nodesByDepth).map(o=>parseInt(o,10)).sort(Bf);if(s.length>1)for(let o of s){let i=this.nodesByDepth[o];for(let l of i){let u=l.outboundLayer;if(this.inputLayers.map(f=>f.id).indexOf(u.id)!==-1)continue;let c=[];for(let f=0;f<l.inboundLayers.length;f++){let m=l.inboundLayers[f],g=l.nodeIndices[f],y=l.tensorIndices[f],x=`${m.name}_${g}_${y}`,A=n[x];c.push(A)}let p=u.computeOutputShape(ps(c)),d=Am(p),h=u.inboundNodes.indexOf(l);for(let f=0;f<d.length;f++){let m=`${u.name}_${h}_${f}`;n[m]=d[f]}}}let r=[],a=[];for(let o=0;o<this.outputLayers.length;o++){let i=this.outputLayers[o],l=this.outputLayersNodeIndices[o],u=this.outputLayersTensorIndices[o],c=`${i.name}_${l}_${u}`;a.push(c)}for(let o=0;o<a.length;o++){let i=a[o];Wr(i in n),r.push(n[i])}return ps(r)}runInternalGraph(e,t){t==null&&(t=Qi(null,e.length));let n={};for(let i=0;i<this.inputs.length;++i){let l=this.inputs[i],u=e[i],c=t[i];n[l.id]=[u,c]}let s=Object.keys(this.nodesByDepth).map(i=>parseInt(i,10)).sort(Bf);for(let i of s){let l=this.nodesByDepth[i];for(let u of l){let c=u.outboundLayer,p=u.inputTensors,d=u.outputTensors,h=new Array;for(let f of p)f.id in n&&h.push(n[f.id]);if(h.length===p.length){let f={},m,g,y,x;if(u.callArgs!=null&&(f=u.callArgs),h.length===1){let[A,b]=h[0];f.mask==null&&(f.mask=b),y=_t(c.call(A,f)),x=_t(c.computeMask(A,b)),m=[A],g=[b]}else m=h.map(A=>A[0]),g=h.map(A=>A[1]),f.mask==null&&(f.mask=g),y=_t(c.call(m,f)),x=_t(c.computeMask(m,g));if(c.activityRegularizer)throw new He("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(let A=0;A<d.length;++A){let b=d[A],w=y[A],k=x[A];n[b.id]=[w,k]}}}}let r=[],a=[],o=[];for(let i of this.outputs){Wr(i.id in n,`Could not compute output ${i.name} : ${i.id}`);let[l,u]=n[i.id];o.push(l.shape),r.push(l),a.push(u)}return[r,a,o]}buildNodeConversionMap(e){let t={},n;for(let s of this.layers){n=s instanceof Br?1:0;for(let r=0;r<s.inboundNodes.length;r++){let a=Br.nodeKey(s,r);this.containerNodes.has(a)&&(t[a]=n,n+=1)}}return t}getLayer(e,t){if(t!=null){if(this.layers.length<=t)throw new j(`Was asked to retrieve layer at index ${t}, but model only has ${this.layers.length} layer(s).`);return this.layers[t]}else if(e==null)throw new j("Provide either a layer name or layer index");for(let n of this.layers)if(n.name===e)return n;throw new j(`No such layer: ${e}`)}calculateLosses(){return J(()=>{let e=[];for(let t of this.layers)for(let n=0;n<t.inboundNodes.length;++n){let s=Br.nodeKey(t,n);this.containerNodes.has(s)&&e.push(...t.calculateLosses())}return e})}getConfig(){let e={name:this.name},t=this.buildNodeConversionMap(this.layers),n=[];for(let a of this.layers){let o=a.getClassName(),i=a.getConfig(),l=[];for(let c=0;c<a.inboundNodes.length;c++){let p=a.inboundNodes[c],d=Br.nodeKey(a,c),h={};if(this.containerNodes.has(d)){if(p.callArgs)try{JSON.stringify(p.callArgs),h=p.callArgs}catch(f){console.warn(`Layer ${a.name} was passed non-serializable keyword arguments: ${p.callArgs}. They will not be included in the serialized model (and thus will be missing at deserialization time).`),h={}}if(p.inboundLayers.length>0){let f=[];for(let m=0;m<p.inboundLayers.length;m++){let g=p.inboundLayers[m],y=p.nodeIndices[m],x=p.tensorIndices[m],A=Br.nodeKey(g,y),b=t[A];b==null&&(b=0),f.push([g.name,b,x,h])}l.push(f)}}}let u={};u.name=a.name,u.className=o,u.config=i,u.inboundNodes=l,n.push(u)}e.layers=n;let s=[];for(let a=0;a<this.inputLayers.length;a++){let o=this.inputLayers[a],i=this.inputLayersNodeIndices[a],l=Br.nodeKey(o,i);if(!this.containerNodes.has(l))continue;let u=t[l];u==null&&(u=0);let c=this.inputLayersTensorIndices[a];s.push([o.name,u,c])}e.inputLayers=s;let r=[];for(let a=0;a<this.outputLayers.length;a++){let o=this.outputLayers[a],i=this.outputLayersNodeIndices[a],l=Br.nodeKey(o,i);if(!this.containerNodes.has(l))continue;let u=t[l];u==null&&(u=0);let c=this.outputLayersTensorIndices[a];r.push([o.name,u,c])}return e.outputLayers=r,e}static fromConfig(e,t,n={},s=!1){let r={},a={};function o(m,g){m.name in a?a[m.name].push(g):a[m.name]=[g]}function i(m,g){let y=[],x;for(let A of g){let b=A[0],w=A[1],k=A[2];if(x=A[3]==null?{}:A[3],!(b in r)){o(m,g);return}let S=r[b];if(S.inboundNodes.length<=w){o(m,g);return}let E=S.inboundNodes[w];y.push(E.outputTensors[k])}y.length>0&&m.apply(ps(y),x)}function l(m){let g=m.name,y=Nr(m,t.customObjects!=null?t.customObjects:{});y.setFastWeightInitDuringBuild(s),r[g]=y,m.inboundNodes.forEach(A=>{if(!(A instanceof Array))throw new j(`Corrupted configuration, expected array for nodeData: ${A}`);o(y,A)})}let u=t.name,c=t.layers;for(let m of c)l(m);for(;!uV(a);)for(let m of c){let g=r[m.name];if(g.name in a){let y=a[g.name];delete a[g.name];for(let x of y)i(g,x)}}let p=[],d=[],h=t.inputLayers;for(let m of h){let g=m[0],y=m[1],x=m[2];Wr(g in r);let b=r[g].inboundNodes[y].outputTensors;p.push(b[x])}let f=t.outputLayers;for(let m of f){let g=m[0],y=m[1],x=m[2];Wr(g in r);let b=r[g].inboundNodes[y].outputTensors;d.push(b[x])}return new e({inputs:p,outputs:d,name:u})}get stateful(){if(this._stateful)throw new j("Container instance unexpectedly has _stateful = true. The statefulness of a Container is determined by the Layers it contains. Its _stateful property must remain the default false.");for(let e of this.layers)if(e.stateful)return!0;return!1}resetStates(){J(()=>{this.layers.forEach(e=>{e.stateful&&e.resetStates()})})}};function FU(e,t,n){let s=t.length;if(e==null||Array.isArray(e)&&e.length===0)return t.map(r=>null);if(s===1)return Array.isArray(e)&&e.length===1?e:typeof e=="object"&&t[0]in e?[e[t[0]]]:[e];if(Array.isArray(e)){if(e.length!==s)throw new Error(`Provided ${n} is an array of ${e.length} element(s), but the model has ${s} outputs. Make sure a set of weights is provided for each model output.`);return e}else if(typeof e=="object"&&Object.keys(e).length>0&&typeof e[Object.keys(e)[0]]=="object"){let r=[];return t.forEach(a=>{a in e?r.push(e[a]):r.push(null)}),r}else throw new Error(`The model has multiple (${s}) outputs, so ${n} must be either an array with ${s} elements or an object with ${t} keys. Provided ${n} not understood: ${JSON.stringify(e)}`)}function z8(e,t){return FU(e,t,"classWeight")}async function L8(e,t,n,s){if(t!=null||s!=null)throw new Error("Support sampleWeight is not implemented yet");if(n!=null){let r=J(()=>{if(e.shape.length===1)return Fn(e);if(e.shape.length===2){if(e.shape[1]>1)return Es(e,1);if(e.shape[1]===1)return U(e,[e.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${e.shape[1]}) during handling of class weights. The size is expected to be >= 1.`)}else throw new Error(`Unexpected rank of target (y) tensor (${e.rank}) during handling of class weights. The rank is expected to be 1 or 2.`)}),a=Array.from(await r.data());ne(r);let o=[];return a.forEach(i=>{if(n[i]==null)throw new Error(`classWeight must contain all classes in the training data. The class ${i} exists in the data but not in classWeight`);o.push(n[i])}),Ft(o,"float32")}else return null}function OU(e,t){return L(e,t)}var MU=32;function B8(e,t){let n,s,r=t;n=r.xs,s=r.ys,v.assert(n!=null&&s!=null,()=>`A Dataset iterator for fitDataset() is expected to generate objects of the form \`{xs: xVal, ys: yVal}\`, where the two values may be \`tf.Tensor\`, an array of Tensors, or a map of string to Tensor.  The provided Dataset instead generates ${t}`);let a=Uv("input",e.inputNames,n),o=Uv("output",e.outputNames,s),i=a[0].shape[0];v.assert(a.length===e.inputs.length,()=>`LayersModel has ${e.inputs.length} inputs, but the dataset provides ${a.length} inputs.  (Expected input keys: ${JSON.stringify(e.inputNames)})`),v.assert(o.length===e.outputs.length,()=>`LayersModel has ${e.outputs.length} outputs, but the dataset provides ${o.length} outputs.  (Expected output keys: ${JSON.stringify(e.outputNames)})`);for(let l=0;l<a.length;l++)v.assert(a[l].shape[0]===i,()=>`Batch size mismatch: input ${e.inputNames[l]} has ${a[l].shape[0]}; expected  ${i} based on input ${e.inputNames[0]}.`);for(let l=0;l<o.length;l++)v.assert(o[l].shape[0]===i,()=>`Batch size mismatch: output ${e.outputNames[l]} has ${o[l].shape[0]}; expected  ${i} based on input ${e.inputNames[0]}.`);return{xs:a,ys:o}}function Uv(e,t,n){if(n instanceof tt)return[n];if(Array.isArray(n))return v.assert(n.length===t.length,()=>`Received an array of ${n.length} Tensors, but expected ${t.length} to match the ${e} keys ${t}.`),n;{let s=[];for(let r of t){if(n[r]==null)throw new j(`The feature data generated by the dataset lacks the required ${e} key '${r}'.`);s.push(n[r])}return s}}function zU(e){if(e.length===3)throw new He("Validation with sample weights is not implemented yet.");return{xs:e[0],ys:e[1]}}async function LU(e,t,n){let s=n.batchesPerEpoch!=null;if(v.assert(e.optimizer!=null,()=>"You must compile a model before training/testing. Use LayersModel.compile(modelCompileConfig)."),v.assert(n!=null,()=>"For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call."),v.assert(n.epochs!=null&&n.epochs>0&&Number.isInteger(n.epochs),()=>`For fitDataset(), config.epochs is expected to be a positive integer, but got ${n.epochs}`),v.assert(!s||n.batchesPerEpoch>0&&Number.isInteger(n.batchesPerEpoch),()=>`For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${n.batchesPerEpoch}`),v.assert(n.validationSplit==null,()=>"`validationSplit` is not supported by `fitDataset()`. Use validationData instead."),e.isTraining)throw new Error("Cannot start training because another fit() call is ongoing.");e.isTraining=!0;try{let r=n.validationData!=null,a,o;if(r)if(Gv(n.validationData))v.assert(n.validationBatches==null||n.validationBatches>0&&Number.isInteger(n.validationBatches),()=>`For fitDataset() with dataset-based validation, config.validationBatches is expected not to be provided, or to be a positive integer, but got ${n.validationBatches}`);else{let g=zU(n.validationData);a=g.xs,o=g.ys}let i=e.makeTrainFunction(),l=e.getDedupedMetricsNames(),u;r?u=l.slice().concat(l.map(g=>"val_"+g)):u=l.slice();let c=R8(n.callbacks,n.yieldEvery),p=n.verbose==null?1:n.verbose,{callbackList:d,history:h}=_8(c,p,n.epochs,null,null,BU(t,n),null,r,u);d.setModel(e),e.history=h,await d.onTrainBegin(),e.stopTraining_=!1;let f=n.initialEpoch==null?0:n.initialEpoch,m=await t.iterator();for(;f<n.epochs;){let g={};await d.onEpochBegin(f);let y=0,x=0;for(s||(m=await t.iterator());!s||y<n.batchesPerEpoch;){let A=await m.next();if(s&&A.done){console.warn(`You provided \`batchesPerEpoch\` as ${n.batchesPerEpoch}, but your dataset iterator ran out of data after ${y} batches; interrupting training. Make sure that your dataset can generate at least \`batchesPerEpoch * epochs\` batches (in this case, ${n.batchesPerEpoch*n.epochs} batches). 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t={};return t.className="linear",t.config={},c3(t)}if(typeof e=="string"){let t={};return t.className=e,t.config={},c3(t)}else return e instanceof As?e:c3(e)}function y5(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 sk=class extends de.Serializable{},Ch=class extends sk{constructor(e){super(),y5(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 J(()=>{let t=Wt([1]);return this.hasL1&&(t=ce(t,ke(L(this.l1,tn(e))))),this.hasL2&&(t=ce(t,ke(L(this.l2,kh(e))))),U(t,[])})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(e,t){return new e({l1:t.l1,l2:t.l2})}};Ch.className="L1L2";de.registerClass(Ch);function rG(e){return y5(e),new Ch({l1:e!=null?e.l1:null,l2:0})}function aG(e){return y5(e),new Ch({l2:e!=null?e.l2:null,l1:0})}var Xv={l1l2:"L1L2"};function St(e){return XA(e)}function 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e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};w5.className="ThresholdedReLU";de.registerClass(w5);var k5=class extends ut{constructor(e){super(e==null?{}:e),this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new g5().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Xe(e);return this.softmax(n,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};k5.className="Softmax";de.registerClass(k5);function Gu(e,t,n){if(typeof e=="number")return Qi(e,t);if(e.length!==t)throw new j(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${e.length} elements.`);for(let s=0;s<t;++s){let r=e[s];if(!bV(r))throw new j(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${JSON.stringify(e)} including a non-integer number ${r}`)}return e}function Er(e,t,n,s,r=1){if(e==null)return e;let a=t+(t-1)*(r-1),o;return n==="same"?o=e:o=e-a+1,Math.floor((o+s-1)/s)}function Vr(e,t,n,s){if(e==null)return null;if(s==="valid")e=e*t+no([n-t,0]);else if(s==="same")e=e*t;else throw new j(`Unsupport padding mode: ${s}.`);return e}function I5(e,t){return J(()=>(Yt(t),t==="channelsFirst"?st(e,[0,2,3,1]):e))}function rk(e,t){return J(()=>(Yt(t),t==="channelsFirst"?st(e,[0,2,3,4,1]):e))}function oG(e,t,n,s=1,r="valid",a,o=1){return J(()=>{if(a==null&&(a=_r()),Yt(a),e.shape.length!==3)throw new j(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new j(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new j(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(a==="channelsFirst"&&(e=st(e,[0,2,1])),r==="causal")throw new He("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let i=g0(e,t,s,r==="same"?"same":"valid","NWC",o);return n!=null&&(i=Pr(i,n)),i})}function Zv(e,t,n,s=[1,1],r="valid",a,o,i=null){return J(()=>{if(a==null&&(a=_r()),Yt(a),e.rank!==3&&e.rank!==4)throw new j(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new j(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=I5(e,a);if(r==="causal")throw new He("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=Qu.conv2d({x:l,filter:t,strides:s,pad:r==="same"?"same":"valid",dilations:o,dataFormat:"NHWC",bias:n,activation:i}),a==="channelsFirst"&&(l=st(l,[0,3,1,2])),l})}function iG(e,t,n,s=[1,1,1],r="valid",a,o){return J(()=>{if(a==null&&(a=_r()),Yt(a),e.rank!==4&&e.rank!==5)throw new j(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new j(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let i=rk(e,a);if(r==="causal")throw new He("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return i=cA(i,t,s,r==="same"?"same":"valid","NDHWC",o),n!=null&&(i=Pr(i,n)),a==="channelsFirst"&&(i=st(i,[0,4,1,2,3])),i})}var S5=class extends ut{constructor(e,t){if(super(t),this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",S5.verifyArgs(t),this.rank=e,vn(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new He(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Gu(t.kernelSize,e,"kernelSize"),this.strides=Gu(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,Qs(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Yt(this.dataFormat),this.activation=ro(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=Ot(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=yn(t.biasConstraint),this.biasRegularizer=Mt(t.biasRegularizer),this.activityRegularizer=Mt(t.activityRegularizer),this.dilationRate=Gu(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new j(`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 j(`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 j(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Wr("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!KA(e.kernelSize,"number",1,3))throw new j(`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:so(this.activation),useBias:this.useBias,biasInitializer:Vt(this.biasInitializer),biasRegularizer:St(this.biasRegularizer),activityRegularizer:St(this.activityRegularizer),biasConstraint:gn(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Th=class extends S5{constructor(e,t){super(e,t),this.kernel=null,Th.verifyArgs(t),this.filters=t.filters,vn(this.filters,"filters"),this.kernelInitializer=Ot(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=yn(t.kernelConstraint),this.kernelRegularizer=Mt(t.kernelRegularizer)}build(e){e=xt(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new j(`The channel dimension of the input should be defined. Found ${e[t]}`);let n=e[t],s=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:{[t]:n}}],this.built=!0}call(e,t){return J(()=>{e=Xe(e);let n,s=this.bias==null?null:this.bias.read(),r=p8(this.activation.getClassName());if(r!=null&&this.rank===2)n=Zv(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate,r);else{if(this.rank===1)n=oG(e,this.kernel.read(),s,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=Zv(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=iG(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new He("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=xt(e);let t=[],n=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let r=0;r<n.length;++r){let a=Er(n[r],this.kernelSize[r],this.padding,this.strides[r],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[r]);t.push(a)}let s=[e[0]];return this.dataFormat==="channelsLast"?(s=s.concat(t),s.push(this.filters)):(s.push(this.filters),s=s.concat(t)),s}getConfig(){let e={filters:this.filters,kernelInitializer:Vt(this.kernelInitializer),kernelRegularizer:St(this.kernelRegularizer),kernelConstraint:gn(this.kernelConstraint)},t=super.getConfig();return Object.assign(e,t),e}static verifyArgs(e){if(!("filters"in e)||typeof e.filters!="number"||e.filters<1)throw new j(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Nh=class extends Th{constructor(e){super(2,e),Nh.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!KA(e.kernelSize,"number",1,2))throw new j(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Nh.className="Conv2D";de.registerClass(Nh);var Eh=class extends Th{constructor(e){super(3,e),Eh.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!(Array.isArray(e.kernelSize)&&(e.kernelSize.length===1||e.kernelSize.length===3)))throw new j(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};Eh.className="Conv3D";de.registerClass(Eh);var C5=class extends Nh{constructor(e){if(super(e),this.inputSpec=[new rn({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new j(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=xt(e),e.length!==4)throw new j("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new j("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],s=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",s,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new rn({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return J(()=>{let n=Xe(e);if(n.shape.length!==4)throw new j(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let s=n.shape,r=s[0],a,o;this.dataFormat==="channelsFirst"?(a=2,o=3):(a=1,o=2);let i=s[a],l=s[o],u=this.kernelSize[0],c=this.kernelSize[1],p=this.strides[0],d=this.strides[1],h=Vr(i,p,u,this.padding),f=Vr(l,d,c,this.padding),m=[r,h,f,this.filters];this.dataFormat!=="channelsLast"&&(n=st(n,[0,2,3,1]));let g=y0(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(g=st(g,[0,3,1,2])),this.bias!=null&&(g=Pr(g,this.bias.read(),this.dataFormat)),this.activation!=null&&(g=this.activation.apply(g)),g})}computeOutputShape(e){e=xt(e);let t=e.slice(),n,s,r;this.dataFormat==="channelsFirst"?(n=1,s=2,r=3):(n=3,s=1,r=2);let a=this.kernelSize[0],o=this.kernelSize[1],i=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[s]=Vr(t[s],i,a,this.padding),t[r]=Vr(t[r],l,o,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};C5.className="Conv2DTranspose";de.registerClass(C5);var T5=class extends Eh{constructor(e){if(super(e),this.inputSpec=[new rn({ndim:5})],this.padding!=="same"&&this.padding!=="valid")throw new j(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=xt(e),e.length!==5)throw new j("Input should have rank 5; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new j("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],s=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",s,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new rn({ndim:5,axes:{[t]:n}})],this.built=!0}call(e,t){return J(()=>{let n=Xe(e);if(n.shape.length!==5)throw new j(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let s=n.shape,r=s[0],a,o,i;this.dataFormat==="channelsFirst"?(i=2,a=3,o=4):(i=1,a=2,o=3);let l=s[i],u=s[a],c=s[o],p=this.kernelSize[0],d=this.kernelSize[1],h=this.kernelSize[2],f=this.strides[0],m=this.strides[1],g=this.strides[2],y=Vr(l,f,p,this.padding),x=Vr(u,m,d,this.padding),A=Vr(c,g,h,this.padding),b=[r,y,x,A,this.filters];this.dataFormat!=="channelsLast"&&(n=st(n,[0,2,3,4,1]));let w=dA(n,this.kernel.read(),b,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(w=st(w,[0,4,1,2,3])),this.bias!==null&&(w=Pr(w,this.bias.read(),this.dataFormat)),this.activation!==null&&(w=this.activation.apply(w)),w})}computeOutputShape(e){e=xt(e);let t=e.slice(),n,s,r,a;this.dataFormat==="channelsFirst"?(n=1,s=2,r=3,a=4):(n=4,s=1,r=2,a=3);let o=this.kernelSize[0],i=this.kernelSize[1],l=this.kernelSize[2],u=this.strides[0],c=this.strides[1],p=this.strides[2];return t[n]=this.filters,t[s]=Vr(t[s],u,o,this.padding),t[r]=Vr(t[r],c,i,this.padding),t[a]=Vr(t[a],p,l,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};T5.className="Conv3DTranspose";de.registerClass(T5);var ak=class extends Th{constructor(e,t){if(super(e,t),this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new j("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new j("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 j(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=Ot(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=Mt(t.depthwiseRegularizer),this.depthwiseConstraint=yn(t.depthwiseConstraint),this.pointwiseInitializer=Ot(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=Mt(t.pointwiseRegularizer),this.pointwiseConstraint=yn(t.pointwiseConstraint)}build(e){if(e=xt(e),e.length<this.rank+2)throw new j(`Inputs to SeparableConv${this.rank}D should have rank ${this.rank+2}, but received input shape: ${JSON.stringify(e)}`);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null||e[t]<0)throw new j(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],s=this.kernelSize.concat([n,this.depthMultiplier]),r=[];for(let o=0;o<this.rank;++o)r.push(1);r.push(n*this.depthMultiplier,this.filters);let a=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",s,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,a,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",r,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,a,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,a,this.biasConstraint):this.bias=null,this.inputSpec=[new rn({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return J(()=>{e=Xe(e);let n;if(this.rank===1)throw new He("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=st(e,[0,2,3,1])),n=D0(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Pr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=st(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=Vt(this.depthwiseInitializer),e.pointwiseInitializer=Vt(this.pointwiseInitializer),e.depthwiseRegularizer=St(this.depthwiseRegularizer),e.pointwiseRegularizer=St(this.pointwiseRegularizer),e.depthwiseConstraint=gn(this.depthwiseConstraint),e.pointwiseConstraint=gn(this.pointwiseConstraint),e}};ak.className="SeparableConv";var N5=class extends ak{constructor(e){super(2,e)}};N5.className="SeparableConv2D";de.registerClass(N5);var c2=class extends Th{constructor(e){super(1,e),c2.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"&&!KA(e.kernelSize,"number",1,1))throw new j(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};c2.className="Conv1D";de.registerClass(c2);var E5=class extends ut{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 J(()=>{if(e=Xe(e),this.dataFormat==="channelsLast"){let n=Vf(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Vf(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Vf(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Vf(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}};E5.className="Cropping2D";de.registerClass(E5);var R5=class extends ut{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,Yt(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,yV(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 J(()=>{let n=Xe(e),s=n.shape;if(this.dataFormat==="channelsFirst"){n=st(n,[0,2,3,1]);let r=this.size[0]*s[2],a=this.size[1]*s[3],o=this.interpolation==="nearest"?Ne.resizeNearestNeighbor(n,[r,a]):Ne.resizeBilinear(n,[r,a]);return st(o,[0,3,1,2])}else{let r=this.size[0]*s[1],a=this.size[1]*s[2];return this.interpolation==="nearest"?Ne.resizeNearestNeighbor(n,[r,a]):Ne.resizeBilinear(n,[r,a])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat,interpolation:this.interpolation},t=super.getConfig();return Object.assign(e,t),e}};R5.className="UpSampling2D";de.registerClass(R5);function lG(e,t,n=[1,1],s="valid",r,a){return J(()=>{r==null&&(r=_r()),Yt(r);let o=I5(e,r);if(e.rank!==4)throw new j(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new j(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return o=Wc(o,t,n,s==="same"?"same":"valid","NHWC",a),r==="channelsFirst"&&(o=st(o,[0,3,1,2])),o})}var _5=class extends S5{constructor(e){super(2,e),this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=Ot(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=yn(e.depthwiseConstraint),this.depthwiseRegularizer=Mt(e.depthwiseRegularizer)}build(e){if(e=xt(e),e.length<4)throw new j(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new j(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],s=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",s,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[n*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return J(()=>{e=Xe(e);let n=lG(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Pr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=xt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],s=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,r=Er(t,this.kernelSize[0],this.padding,this.strides[0]),a=Er(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],s,r,a]:[e[0],r,a,s]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=Vt(this.depthwiseInitializer),e.depthwiseRegularizer=St(this.depthwiseRegularizer),e.depthwiseConstraint=gn(this.depthwiseRegularizer),e}};_5.className="DepthwiseConv2D";de.registerClass(_5);function ok(e,t,n,s){if(Array.isArray(e)){if(t!=null||n!=null)throw new j("When inputs is an array, neither initialState or constants should be provided");s!=null&&(n=e.slice(e.length-s,e.length),e=e.slice(0,e.length-s)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function r(a){return a==null||Array.isArray(a)?a:[a]}return t=r(t),n=r(n),{inputs:e,initialState:t,constants:n}}function ik(e,t,n,s=!1,r,a,o=!1,i=!1){return J(()=>{let l=t.shape.length;if(l<3)throw new j(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(Rr(2,l));if(t=st(t,u),a!=null)throw new He("The rnn() functoin of the deeplearn.js backend does not support constants yet.");o&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),r!=null&&(r=ge(ge(r,"bool"),"float32"),r.rank===l-1&&(r=Kt(r,-1)),r=st(r,u)),s&&(t=Ks(t,0),r!=null&&(r=Ks(r,0)));let c=[],p,d=n,h=t.shape[0],f=es(t),m;r!=null&&(m=es(r));for(let y=0;y<h;++y){let x=f[y],A=J(()=>e(x,d));if(r==null)p=A[0],d=A[1];else{let b=J(()=>{let w=m[y],k=he($s(w),w),S=ce(L(A[0],w),L(d[0],k)),E=d.map((R,P)=>ce(L(A[1][P],w),L(R,k)));return{output:S,newStates:E}});p=b.output,d=b.newStates}i&&c.push(p)}let g;return i&&(g=on(c,1)),[p,g,d]})}var Jr=class extends ut{constructor(e){super(e);let t;if(e.cell==null)throw new j("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new h2({cells:e.cell}):t=e.cell,t.stateSize==null)throw new j("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 rn({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 Rr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){P3(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],s;if(this.returnSequences?s=[e[0],e[1],n]:s=[e[0],n],this.returnState){let r=[];for(let a of t)r.push([e[0],a]);return[s].concat(r)}else return s}computeMask(e,t){return J(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let s=this.states.map(r=>null);return[n].concat(s)}else return n})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;n<e;++n)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){if(this.numConstants!=null)throw new He("Constants support is not implemented in RNN yet.");P3(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,s=e.slice(2);this.inputSpec[0]=new rn({shape:[n,null,...s]});let r=[e[0]].concat(e.slice(2));this.cell.build(r);let a;if(Array.isArray(this.cell.stateSize)?a=this.cell.stateSize:a=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(o=>o.shape[o.shape.length-1]),a))throw new j(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=a.map(o=>new rn({shape:[null,o]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){J(()=>{if(!this.stateful)throw new ia("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new j("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.states_==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(s=>Wt([n,s])):this.states_=[Wt([n,this.cell.stateSize])];else if(e==null)ne(this.states_),this.keptStates!=null&&(ne(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(s=>Wt([n,s])):this.states_[0]=Wt([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new j(`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()):ne(this.states_);for(let s=0;s<this.states_.length;++s){let r=e[s],a=Array.isArray(this.cell.stateSize)?this.cell.stateSize[s]:this.cell.stateSize,o=[n,a];if(!v.arraysEqual(r.shape,o))throw new j(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${r.shape}`);this.states_[s]=r}}this.states_=this.states_.map(s=>bn(s.clone()))})}apply(e,t){let n=t==null?null:t.initialState,s=t==null?null:t.constants;t==null&&(t={});let r=ok(e,n,s,this.numConstants);e=r.inputs,n=r.initialState,s=r.constants;let a=[],o=[];if(n!=null){t.initialState=n,a=a.concat(n),this.stateSpec=[];for(let l of n)this.stateSpec.push(new rn({shape:l.shape}));o=o.concat(this.stateSpec)}if(s!=null&&(t.constants=s,a=a.concat(s),this.numConstants=s.length),a[0]instanceof Cr){let l=[e].concat(a),u=this.inputSpec.concat(o),c=this.inputSpec;this.inputSpec=u;let p=super.apply(l,t);return this.inputSpec=c,p}else return super.apply(e,t)}call(e,t){return J(()=>{let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;e=Xe(e),r==null&&(this.stateful?r=this.states_:r=this.getInitialState(e));let a=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(r.length!==a)throw new j(`RNN Layer has ${a} state(s) but was passed ${r.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let o={training:s},l=ik((h,f)=>{let m=this.cell.call([h].concat(f),o);return[m[0],m.slice(1)]},e,r,this.goBackwards,n,null,this.unroll,this.returnSequences),u=l[0],c=l[1],p=l[2];this.stateful&&this.resetStates(p,s);let d=this.returnSequences?c:u;return this.returnState?[d].concat(p):d})}getInitialState(e){return J(()=>{let t=Wt(e.shape);return t=ke(t,[1,2]),t=wh(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?D3(t,[1,n]):t):this.cell.stateSize>1?[D3(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()===Jr.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let s=t.cell,r=Nr(s,n);return new e(Object.assign(t,{cell:r}))}};Jr.className="RNN";de.registerClass(Jr);var Rh=class extends ut{},d2=class extends Rh{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,vn(this.units,"units"),this.activation=ro(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Ot(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Ot(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Ot(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=Mt(e.kernelRegularizer),this.recurrentRegularizer=Mt(e.recurrentRegularizer),this.biasRegularizer=Mt(e.biasRegularizer),this.kernelConstraint=yn(e.kernelConstraint),this.recurrentConstraint=yn(e.recurrentConstraint),this.biasConstraint=yn(e.biasConstraint),this.dropout=ec([1,no([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=ec([1,no([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=xt(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 J(()=>{if(e=e,e.length!==2)throw new j(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let s=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ao({ones:()=>$s(e),rate:this.dropout,training:s,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ao({ones:()=>$s(n),rate:this.recurrentDropout,training:s,dropoutFunc:this.dropoutFunc}));let r,a=this.dropoutMask,o=this.recurrentDropoutMask;a!=null?r=Hr(L(e,a),this.kernel.read()):r=Hr(e,this.kernel.read()),this.bias!=null&&(r=Pr(r,this.bias.read())),o!=null&&(n=L(n,o));let i=ce(r,Hr(n,this.recurrentKernel.read()));return this.activation!=null&&(i=this.activation.apply(i)),[i,i]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:so(this.activation),useBias:this.useBias,kernelInitializer:Vt(this.kernelInitializer),recurrentInitializer:Vt(this.recurrentInitializer),biasInitializer:Vt(this.biasInitializer),kernelRegularizer:St(this.kernelRegularizer),recurrentRegularizer:St(this.recurrentRegularizer),biasRegularizer:St(this.biasRegularizer),activityRegularizer:St(this.activityRegularizer),kernelConstraint:gn(this.kernelConstraint),recurrentConstraint:gn(this.recurrentConstraint),biasConstraint:gn(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};d2.className="SimpleRNNCell";de.registerClass(d2);var D5=class extends Jr{constructor(e){e.cell=new d2(e),super(e)}call(e,t){return J(()=>{this.cell.dropoutMask!=null&&(ne(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ne(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}static fromConfig(e,t){return new e(t)}};D5.className="SimpleRNN";de.registerClass(D5);var p2=class extends Rh{constructor(e){if(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",e.resetAfter)throw new j("GRUCell does not support reset_after parameter set to true.");this.units=e.units,vn(this.units,"units"),this.activation=ro(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ro(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Ot(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Ot(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Ot(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=Mt(e.kernelRegularizer),this.recurrentRegularizer=Mt(e.recurrentRegularizer),this.biasRegularizer=Mt(e.biasRegularizer),this.kernelConstraint=yn(e.kernelConstraint),this.recurrentConstraint=yn(e.recurrentConstraint),this.biasConstraint=yn(e.biasConstraint),this.dropout=ec([1,no([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=ec([1,no([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=xt(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 J(()=>{if(e=e,e.length!==2)throw new j(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,s=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ao({ones:()=>$s(e),rate:this.dropout,training:n,count:3,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ao({ones:()=>$s(s),rate:this.recurrentDropout,training:n,count:3,dropoutFunc:this.dropoutFunc}));let r=this.dropoutMask,a=this.recurrentDropoutMask,o,i,l;0<this.dropout&&this.dropout<1&&(e=L(e,r[0]));let u=Hr(e,this.kernel.read());this.useBias&&(u=Pr(u,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(s=L(s,a[0]));let c=this.recurrentKernel.read(),[p,d]=Zt(c,[2*this.units,this.units],c.rank-1),h=Hr(s,p),[f,m,g]=Zt(u,3,u.rank-1),[y,x]=Zt(h,2,h.rank-1);o=this.recurrentActivation.apply(ce(f,y)),i=this.recurrentActivation.apply(ce(m,x));let A=Hr(L(i,s),d);l=this.activation.apply(ce(g,A));let b=ce(L(o,s),L(ce(1,Dt(o)),l));return[b,b]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:so(this.activation),recurrentActivation:so(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Vt(this.kernelInitializer),recurrentInitializer:Vt(this.recurrentInitializer),biasInitializer:Vt(this.biasInitializer),kernelRegularizer:St(this.kernelRegularizer),recurrentRegularizer:St(this.recurrentRegularizer),biasRegularizer:St(this.biasRegularizer),activityRegularizer:St(this.activityRegularizer),kernelConstraint:gn(this.kernelConstraint),recurrentConstraint:gn(this.recurrentConstraint),biasConstraint:gn(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};p2.className="GRUCell";de.registerClass(p2);var $5=class extends Jr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new p2(e),super(e)}call(e,t){return J(()=>{this.cell.dropoutMask!=null&&(ne(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ne(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};$5.className="GRU";de.registerClass($5);var _h=class extends Rh{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,vn(this.units,"units"),this.activation=ro(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ro(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Ot(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Ot(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Ot(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=Mt(e.kernelRegularizer),this.recurrentRegularizer=Mt(e.recurrentRegularizer),this.biasRegularizer=Mt(e.biasRegularizer),this.kernelConstraint=yn(e.kernelConstraint),this.recurrentConstraint=yn(e.recurrentConstraint),this.biasConstraint=yn(e.biasConstraint),this.dropout=ec([1,no([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=ec([1,no([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=xt(e);let n=e[e.length-1];this.kernel=this.addWeight("kernel",[n,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let s;if(this.useBias){if(this.unitForgetBias){let r=this.biasInitializer,a=this.units;s=new(t=class extends pr{apply(i,l){let u=r.apply([a]),c=new e2().apply([a]),p=r.apply([a*2]);return $v($v(u,c),p)}},t.className="CustomInit",t)}else s=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,s,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return J(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new j(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let s=e[1],r=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ao({ones:()=>$s(e),rate:this.dropout,training:n,count:4,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ao({ones:()=>$s(s),rate:this.recurrentDropout,training:n,count:4,dropoutFunc:this.dropoutFunc}));let a=this.dropoutMask,o=this.recurrentDropoutMask,i,l,u,c;0<this.dropout&&this.dropout<1&&(e=L(e,a[0]));let p=Hr(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(s=L(s,o[0])),p=ce(p,Hr(s,this.recurrentKernel.read())),this.useBias&&(p=Pr(p,this.bias.read()));let[d,h,f,m]=Zt(p,4,p.rank-1);i=this.recurrentActivation.apply(d),l=this.recurrentActivation.apply(h),u=ce(L(l,r),L(i,this.activation.apply(f))),c=this.recurrentActivation.apply(m);let g=L(c,this.activation.apply(u));return[g,g,u]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:so(this.activation),recurrentActivation:so(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Vt(this.kernelInitializer),recurrentInitializer:Vt(this.recurrentInitializer),biasInitializer:Vt(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:St(this.kernelRegularizer),recurrentRegularizer:St(this.recurrentRegularizer),biasRegularizer:St(this.biasRegularizer),activityRegularizer:St(this.activityRegularizer),kernelConstraint:gn(this.kernelConstraint),recurrentConstraint:gn(this.recurrentConstraint),biasConstraint:gn(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};_h.className="LSTMCell";de.registerClass(_h);var P5=class extends Jr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new _h(e),super(e)}call(e,t){return J(()=>{this.cell.dropoutMask!=null&&(ne(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ne(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};P5.className="LSTM";de.registerClass(P5);var h2=class extends Rh{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 J(()=>{e=e;let n=e.slice(1),s=[];for(let o of this.cells.slice().reverse())Array.isArray(o.stateSize)?s.push(n.splice(0,o.stateSize.length)):s.push(n.splice(0,1));s.reverse();let r=[],a;for(let o=0;o<this.cells.length;++o){let i=this.cells[o];n=s[o],o===0?a=[e[0]].concat(n):a=[a[0]].concat(n),a=i.call(a,t),r.push(a.slice(1))}n=[];for(let o of r.slice().reverse())n.push(...o);return[a[0]].concat(n)})}build(e){P3(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,s)=>{Gi(`RNNCell_${s}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=r=>({className:r.getClassName(),config:r.getConfig()}),s={cells:this.cells.map(t)};return Object.assign({},e,s)}static fromConfig(e,t,n={}){let s=[];for(let r of t.cells)s.push(Nr(r,n));return new e({cells:s})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return F3(e)}setWeights(e){let t=[];for(let n of this.cells){let s=n.weights.length,r=e.splice(s);for(let a=0;a<n.weights.length;++a)t.push([n.weights[a],r[a]])}r5(t)}};h2.className="StackedRNNCells";de.registerClass(h2);function ao(e){let{ones:t,rate:n,training:s=!1,count:r=1,dropoutFunc:a}=e,o=()=>a!=null?a(t(),n):x8(t(),n),i=()=>Ih(o,t,s);return!r||r<=1?bn(i().clone()):Array(r).fill(void 0).map(i).map(u=>bn(u.clone()))}var uG=function(e,t){var n={};for(var s in e)Object.prototype.hasOwnProperty.call(e,s)&&t.indexOf(s)<0&&(n[s]=e[s]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var r=0,s=Object.getOwnPropertySymbols(e);r<s.length;r++)t.indexOf(s[r])<0&&Object.prototype.propertyIsEnumerable.call(e,s[r])&&(n[s[r]]=e[s[r]]);return n},lk=class extends Jr{constructor(e){if(e.unroll)throw new He("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new He("It is not possible at the moment to stack convolutional cells.");super(e),this.inputSpec=[new rn({ndim:5})]}call(e,t){return J(()=>{if(this.cell.dropoutMask!=null&&(ne(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ne(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new j("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return J(()=>{let{stateSize:t}=this.cell,n=e.shape,s=this.computeSingleOutputShape(n),r=[s[0],...s.slice(2)],a=Wt(r);return Array.isArray(t)?Array(t.length).fill(a):[a]})}resetStates(e,t=!1){J(()=>{if(!this.stateful)throw new ia("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,s=this.computeSingleOutputShape(n),r=[s[0],...s.slice(2)];if(n[0]==null)throw new j("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(()=>Wt(r)):this.states_=[Wt(r)];else if(e==null)ne(this.states_),this.keptStates!=null&&(ne(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Wt(r)):this.states_[0]=Wt(r);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new j(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t?this.keptStates.push(this.states_.slice()):ne(this.states_);for(let o=0;o<this.states_.length;++o){let i=e[o],l=r;if(!v.arraysEqual(i.shape,l))throw new j(`State ${o} is incompatible with layer ${this.name}: expected shape=${l}, received shape=${i.shape}`);this.states_[o]=i}}this.states_=this.states_.map(o=>bn(o.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:s,padding:r,strides:a,dilationRate:o}=this.cell,i=t==="channelsFirst",l=e[i?3:2],u=e[i?4:3],c=Er(l,s[0],r,a[0],o[0]),p=Er(u,s[1],r,a[1],o[1]);return[...e.slice(0,2),...i?[n,c,p]:[c,p,n]]}};lk.className="ConvRNN2D";var f2=class extends _h{constructor(e){let{filters:t,kernelSize:n,strides:s,padding:r,dataFormat:a,dilationRate:o}=e;super(Object.assign({},e,{units:t})),this.filters=t,vn(this.filters,"filters"),this.kernelSize=Gu(n,2,"kernelSize"),this.kernelSize.forEach(i=>vn(i,"kernelSize")),this.strides=Gu(s||1,2,"strides"),this.strides.forEach(i=>vn(i,"strides")),this.padding=r||"valid",Qs(this.padding),this.dataFormat=a||"channelsLast",Yt(this.dataFormat),this.dilationRate=Gu(o||1,2,"dilationRate"),this.dilationRate.forEach(i=>vn(i,"dilationRate"))}build(e){var t;e=xt(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new j(`The channel dimension of the input should be defined. Found ${e[n]}`);let s=e[n],r=4,a=this.kernelSize.concat([s,this.filters*r]);this.kernel=this.addWeight("kernel",a,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let o=this.kernelSize.concat([this.filters,this.filters*r]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",o,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let i;if(this.unitForgetBias){let l=this.biasInitializer,u=this.filters;i=new(t=class extends pr{apply(p,d){let h=l.apply([u]),f=Ns([u]),m=l.apply([u*2]);return ZA([h,f,m])}},t.className="CustomInit",t)}else i=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*r],null,i,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return J(()=>{if(e.length!==3)throw new j(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,s=e[0],r=e[1],a=e[2],o=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ao({ones:()=>$s(s),rate:this.dropout,training:n,count:o,dropoutFunc:this.dropoutFunc}));let i=this.dropoutMask,l=(B,ee,Q)=>!ee||!ee[Q]?B:L(ee[Q],B),u=l(s,i,0),c=l(s,i,1),p=l(s,i,2),d=l(s,i,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ao({ones:()=>$s(r),rate:this.recurrentDropout,training:n,count:o,dropoutFunc:this.dropoutFunc}));let h=this.recurrentDropoutMask,f=l(r,h,0),m=l(r,h,1),g=l(r,h,2),y=l(r,h,3),x=3,[A,b,w,k]=Zt(this.kernel.read(),o,x),[S,E,R,P]=this.useBias?Zt(this.bias.read(),o):[null,null,null,null];u=this.inputConv(u,A,S,this.padding),c=this.inputConv(c,b,E,this.padding),p=this.inputConv(p,w,R,this.padding),d=this.inputConv(d,k,P,this.padding);let[_,$,T,F]=Zt(this.recurrentKernel.read(),o,x);f=this.recurrentConv(f,_),m=this.recurrentConv(m,$),g=this.recurrentConv(g,T),y=this.recurrentConv(y,F);let G=this.recurrentActivation.apply(ce(u,f)),q=this.recurrentActivation.apply(ce(c,m)),z=ce(L(q,a),L(G,this.activation.apply(ce(p,g)))),Z=L(this.recurrentActivation.apply(ce(d,y)),this.activation.apply(z));return[Z,Z,z]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=uG(e,["units"]),s={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,s)}inputConv(e,t,n,s){let r=fa(e,t,this.strides,s||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Pr(r,n,this.dataFormat):r}recurrentConv(e,t){return fa(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};f2.className="ConvLSTM2DCell";de.registerClass(f2);var F5=class extends lk{constructor(e){let t=new f2(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};F5.className="ConvLSTM2D";de.registerClass(F5);var m2=class extends ut{constructor(e){super(e),this.rate=Math.max(Math.min(e.rate,1),0),this.noiseShape=e.noiseShape,this.seed=e.seed,this.supportsMasking=!0}getNoiseShape(e){if(this.noiseShape==null)return this.noiseShape;let t=e.shape,n=[];for(let s=0;s<this.noiseShape.length;++s)n.push(this.noiseShape[s]==null?t[s]:this.noiseShape[s]);return n}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e);if(0<this.rate&&this.rate<1){let s=t.training==null?!1:t.training,r=this.getNoiseShape(n);return Ih(()=>x8(n,this.rate,r,this.seed),()=>n,s)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};m2.className="Dropout";de.registerClass(m2);var O5=class extends m2{constructor(e){super(e),this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};O5.className="SpatialDropout1D";de.registerClass(O5);var M5=class extends ut{constructor(e){if(super(e),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,vn(this.units,"units"),this.activation=ro(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=Ot(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=Ot(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=yn(e.kernelConstraint),this.biasConstraint=yn(e.biasConstraint),this.kernelRegularizer=Mt(e.kernelRegularizer),this.biasRegularizer=Mt(e.biasRegularizer),this.activityRegularizer=Mt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=xt(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=xt(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e),s=p8(this.activation.getClassName()),r;return s!=null?r=Hr(n,this.kernel.read(),s,this.bias?this.bias.read():null):(r=Hr(n,this.kernel.read()),this.bias!=null&&(r=Pr(r,this.bias.read())),this.activation!=null&&(r=this.activation.apply(r))),r})}getConfig(){let e={units:this.units,activation:so(this.activation),useBias:this.useBias,kernelInitializer:Vt(this.kernelInitializer),biasInitializer:Vt(this.biasInitializer),kernelRegularizer:St(this.kernelRegularizer),biasRegularizer:St(this.biasRegularizer),activityRegularizer:St(this.activityRegularizer),kernelConstraint:gn(this.kernelConstraint),biasConstraint:gn(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};M5.className="Dense";de.registerClass(M5);var z5=class extends ut{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=xt(e);for(let t of e.slice(1))if(t==null)throw new j(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],Xa(e,1)]}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let s=[0];for(let r=2;r<n.rank;++r)s.push(r);s.push(1),n=st(n,s)}return kV(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};z5.className="Flatten";de.registerClass(z5);var L5=class extends ut{constructor(e){super(e),this.supportsMasking=!0,this.activation=ro(e.activation)}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e);return this.activation.apply(n)})}getConfig(){let e={activation:so(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};L5.className="Activation";de.registerClass(L5);var B5=class extends ut{constructor(e){super(e),this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return J(()=>(e=Xe(e),vV(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};B5.className="RepeatVector";de.registerClass(B5);var W5=class extends ut{constructor(e){super(e),this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let n="Total size of new array must be unchanged.",s=t.slice(),r=1,a=null;for(let i=0;i<s.length;++i){let l=s[i];if(this.isUnknown(l))if(a===null)a=i;else throw new j("Can only specifiy one unknown dimension.");else r*=l}let o=Xa(e);if(a!==null){if(r===0||o%r!==0)throw new j(n);s[a]=o/r}else if(o!==r)throw new j(n);return s}computeOutputShape(e){let t=!1;for(let n=0;n<e.length;++n)if(this.isUnknown(e[n])){t=!0;break}return t?e.slice(0,1).concat(this.targetShape):e.slice(0,1).concat(this.fixUnknownDimension(e.slice(1),this.targetShape))}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e),s=n.shape,r=s.slice(0,1).concat(this.fixUnknownDimension(s.slice(1),this.targetShape));return U(n,r)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};W5.className="Reshape";de.registerClass(W5);var V5=class extends ut{constructor(e){if(super(e),e.dims==null)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(e.dims))throw new Error(`Permute constructor requires \`dims\` to be an Array, but received ${e.dims} instead.`);let t=Rr(1,e.dims.length+1);if(!v.arraysEqual(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new rn({ndim:this.dims.length+1})]}computeOutputShape(e){e=xt(e);let t=e.slice();return this.dims.forEach((n,s)=>{t[s+1]=e[n]}),t}call(e,t){return st(Xe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};V5.className="Permute";de.registerClass(V5);var U5=class extends ut{constructor(e){super(e==null?{}:e),this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=Xe(e),s=-1;return Sp(Ji(n,this.maskValue),s)}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e),s=-1,r=!0,a=Sp(Ji(n,this.maskValue),s,r);return L(n,ge(a,n.dtype))})}};U5.className="Masking";de.registerClass(U5);var G5=class extends ut{constructor(e){if(super(e),this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(_t(e.inputLength))}this.inputDim=e.inputDim,vn(this.inputDim,"inputDim"),this.outputDim=e.outputDim,vn(this.outputDim,"outputDim"),this.embeddingsInitializer=Ot(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=Mt(e.embeddingsRegularizer),this.activityRegularizer=Mt(e.activityRegularizer),this.embeddingsConstraint=yn(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return J(()=>this.maskZero?(e=Xe(e),Ji(e,it(e))):null)}computeOutputShape(e){if(e=xt(e),this.inputLength==null)return[...e,this.outputDim];let t=_t(this.inputLength);if(t.length!==e.length-1)throw new j(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let s=0;s<t.length;++s){let r=t[s],a=e[s+1];if(r!=null&&a!=null&&r!==a)throw new j(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);r==null&&(t[n]=a),n++}}return[e[0],...t,this.outputDim]}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e);n.dtype!=="int32"&&(n=J0(n,"int32"));let s=A8(this.embeddings.read(),U(n,[n.size]));return U(s,xt(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:Vt(this.embeddingsInitializer),embeddingsRegularizer:St(this.embeddingsRegularizer),activityRegularizer:St(this.activityRegularizer),embeddingsConstraint:gn(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};G5.className="Embedding";de.registerClass(G5);var tu=class extends ut{constructor(e){super(e||{}),this.supportsMasking=!0}mergeFunction(e){throw new He}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let n=e.slice(0,e.length-t.length);for(let s=0;s<t.length;++s){let r=e[e.length-t.length+s],a=t[s];if(r==null||a==null||r<0||a<0)n.push(null);else if(r===1)n.push(a);else if(a===1)n.push(r);else{if(r!==a)throw new j("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(r)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[xt(e)]),e=e,e.length<2)throw new j(`A merge layer should be called on an Array of at least 2 inputs. Got ${e.length} input(s).`);let t=[];for(let r of e)r!=null&&r[0]!==null&&t.push(r[0]);if(t=qa(t),t.length>1)throw new j(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let n=e[0]==null?null:e[0].slice(1);for(let r=1;r<e.length;++r){let a=e[r]==null?null:e[r].slice(1);n=this.computeElementwiseOpOutputShape(n,a)}let s=e.map(r=>r.length);e.indexOf(null)===-1&&qa(s).length===1?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return J(()=>{if(e=e,this.reshapeRequired){let n=[],s=e.map(r=>r.rank);if(s.indexOf(null)===-1){let r=no(s);for(let a of e){let o=a.rank;for(let i=0;i<r-o;++i)a=wh(a,1);n.push(a)}return this.mergeFunction(n)}else{let r=!1;for(let i of e){let l=i.rank;if(l==null){let u=i.shape,c=u[0],p=u.slice(1).concat([c]),d=U(i,[c].concat(Xa(u.slice(1))));d=st(d,[1,0]),d=U(d,p),n.push(d),r=!0}else if(l>1){let u=Rr(1,l).concat([0]);n.push(st(i,u)),r=!0}else n.push(i)}let a=this.mergeFunction(n),o=a.rank;if(r){if(o==null){let i=a.shape,l=i.length,u=i[l-1],c=[u].concat(i.slice(0,i.length-1));a=U(st(U(a,[-1,u]),[1,0]),c)}else if(o>1){let i=[o-1].concat(Rr(0,o-1));a=st(a,i)}}return a}}else return this.mergeFunction(e)})}computeOutputShape(e){e=e;let t;e[0]==null?t=null:t=e[0].slice(1);for(let s=1;s<e.length;++s){let r=e[s]==null?null:e[s].slice(1);t=this.computeElementwiseOpOutputShape(t,r)}let n=[];for(let s of e)s!=null&&s[0]!==null&&n.push(s[0]);return n=qa(n),n.length===1?t=n.concat(t):t=[null].concat(t),t}computeMask(e,t){return J(()=>{if(t==null)return null;if(!Array.isArray(t))throw new j("`mask` should be an Array");if(!Array.isArray(e))throw new j("`inputs` should be an Array");if(t.length!==e.length)throw new j(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${e.length} vs ${t.length})`);if(t.every(s=>s==null))return null;t=t.map(s=>s==null?s:Kt(s,0));let n=t[0];for(let s=1;s<t.length-1;++s)n=lr(n,t[s]);return n})}},H5=class extends tu{constructor(e){super(e)}mergeFunction(e){return J(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ce(t,e[n]);return t})}};H5.className="Add";de.registerClass(H5);var j5=class extends tu{constructor(e){super(e)}mergeFunction(e){return J(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=L(t,e[n]);return t})}};j5.className="Multiply";de.registerClass(j5);var q5=class extends tu{constructor(e){super(e)}mergeFunction(e){return J(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ce(t,e[n]);return L(1/e.length,t)})}};q5.className="Average";de.registerClass(q5);var X5=class extends tu{constructor(e){super(e)}mergeFunction(e){return J(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=Yr(t,e[n]);return t})}};X5.className="Maximum";de.registerClass(X5);var K5=class extends tu{constructor(e){super(e)}mergeFunction(e){return J(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=qc(t,e[n]);return t})}};K5.className="Minimum";de.registerClass(K5);var Z5=class extends tu{constructor(e){super(e),this.DEFAULT_AXIS=-1,e==null&&(e={}),this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){if(!(Array.isArray(e)&&Array.isArray(e[0]))||e.length===1)throw new j("A `Concatenate` layer should be called on a list of at least 2 inputs");e=e;let t=!0;for(let s of e)if(s!=null){t=!1;break}if(t)return;let n=[];for(let s=0;s<e.length;++s){let r=e[s].slice();r.splice(this.axis,1);let a=!1;for(let o of n)if(v.arraysEqual(o,r)){a=!0;break}a||n.push(r)}if(n.length>1)throw new j("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return J(()=>ZA(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new j("A `Concatenate` layer should be called on a list of inputs.");let t=e,n=t[0].slice(),s=this.axis<0?n.length+this.axis:this.axis;for(let r of t.slice(1)){if(n[s]==null||r[s]==null){n[s]=null;break}n[s]+=r[s]}return n}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new j("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new j("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new j(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return J(()=>{let n=!0;if(t.forEach(a=>{if(a!=null){n=!1;return}}),n)return null;let s=[];for(let a=0;a<e.length;++a)t[a]==null?s.push(ge($s(e[a]),"bool")):t[a].rank<e[a].rank?s.push(Kt(t[a],-1)):s.push(t[a]);let r=Ct(s,this.axis);return m0(r,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};Z5.className="Concatenate";de.registerClass(Z5);function Qd(e,t){for(;e<0;)e+=t;return e}function cG(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new He("batchDot is not implemented for tensors of 4D or higher rank yet");if(v.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),v.assert(e.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof n=="number"&&(n=[n,n]),e.dtype==="complex64"||t.dtype==="complex64")throw new He("batchDot is not implemented for complex64-type Tensors yet.");let s=e.shape.length,r=t.shape.length;n==null&&(n=[s-1,r-2]);let a=n;return J(()=>{let o;if(s>r){o=s-r;let l=[];for(let u=0;u<o;++u)l.push(1);t=U(t,t.shape.concat(l))}else if(r>s){o=r-s;let l=[];for(let u=0;u<o;++u)l.push(1);e=U(e,e.shape.concat(l))}else o=0;let i;if(e.shape.length===2&&t.shape.length===2)a[0]===a[1]?i=ke(L(e,t),a[0]):i=ke(L(st(e,[1,0]),t),a[1]);else{let l=a[0]!==e.shape.length-1,u=a[1]===t.shape.length-1;i=Qe(e,t,l,u)}if(o>0){let l;s>r?l=s+r-3:l=s-1;let u=[];for(let c=l;c<l+o;++c)u.push(c);i=rt(i,u)}return i.shape.length===1&&(i=Kt(i,1)),i})}var Y5=class extends tu{constructor(e){super(e),this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],n=e[1];if(t.length>3||n.length>3)throw new He("Dot layer does not support tensors of 4D or higher rank yet.");let s=this.interpretAxes(t,n);if(t[s[0]]!==n[s[1]])throw new j(`Dimension incompatibility: ${t[s[0]]} !== ${n[s[1]]}`)}mergeFunction(e){if(e.length!==2)throw new j(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],n=e[1],s;return Array.isArray(this.axes)?s=this.axes.map((r,a)=>Qd(r,e[a].shape.length)):s=[Qd(this.axes,t.shape.length),Qd(this.axes,n.shape.length)],this.normalize&&(t=wm(t,s[0]),n=wm(n,s[1])),cG(t,n,s)}interpretAxes(e,t){let n;return Array.isArray(this.axes)?n=this.axes:n=[Qd(this.axes,e.length),Qd(this.axes,t.length)],n}computeOutputShape(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0].slice(),n=e[1].slice();if(t.length>3||n.length>3)throw new He("Dot layer does not support tensors of 4D or higher rank yet.");let s=this.interpretAxes(t,n);t.splice(s[0],1),n.splice(s[1],1),n.splice(0,1);let r=t.concat(n);return r.length===1&&r.push(1),r}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};Y5.className="Dot";de.registerClass(Y5);var J5=class extends ut{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 J(()=>{this.invokeCallHook(e,t);let n=Xe(e);return Ih(()=>ce(Q0(n.shape,0,this.stddev),n),()=>n,t.training||!1)})}};J5.className="GaussianNoise";de.registerClass(J5);var Q5=class extends ut{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 J(()=>{this.invokeCallHook(e,t);let n=Xe(e);return this.rate>0&&this.rate<1?Ih(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return L(n,Q0(n.shape,1,r))},()=>n,t.training||!1):n})}};Q5.className="GaussianDropout";de.registerClass(Q5);var ex=class extends ut{constructor(e){super(e),this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Xe(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return J(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return Ih(()=>{let r=Xe(e),a=1.6732632423543772,o=1.0507009873554805,i=-a*o,l=ii(Xc(n),this.rate);l=J0(l,"float32");let u=((1-this.rate)*(1+this.rate*i**2))**-.5,c=-u*i*this.rate,p=ce(L(r,l),L(ce(l,-1),i));return ce(L(p,u),c)},()=>Xe(e),t.training||!1)}return e})}};ex.className="AlphaDropout";de.registerClass(ex);function Ep(e,t,n,s,r,a=.001){let o;if(e.rank===2)o=tA(e,t,n,s,r,a);else if(e.rank===3)o=nA(e,t,n,s,r,a);else if(e.rank===4)o=sA(e,t,n,s,r,a);else throw new He(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return o}function dG(e,t,n,s,r=.001){return J(()=>{let a=fh(e,s),o=a.mean,i=a.variance;return[Ep(e,o,i,n,t,r),o,i]})}function pG(e,t,n,s,r=.001){return J(()=>{let a=fh(e,s),o=a.mean,i=a.variance,l=[];for(let f of Rr(0,e.rank))s.indexOf(f)!==-1?l.push(1):l.push(e.shape[f]);let u=U(o,l),c=U(i,l),p=t==null?null:U(t,l),d=n==null?null:U(n,l);return[Ep(e,u,c,d,p,r),o,i]})}function hG(e,t,n,s,r=.001){return v.arraysEqual(s.slice().sort(),Rr(0,e.rank-1))?dG(e,t,n,s,r):pG(e,t,n,s,r)}var tx=class extends ut{constructor(e){e==null&&(e={}),super(e),this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=Ot(e.betaInitializer||"zeros"),this.gammaInitializer=Ot(e.gammaInitializer||"ones"),this.movingMeanInitializer=Ot(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=Ot(e.movingVarianceInitializer||"ones"),this.betaConstraint=yn(e.betaConstraint),this.gammaConstraint=yn(e.gammaConstraint),this.betaRegularizer=Mt(e.betaRegularizer),this.gammaRegularizer=Mt(e.gammaRegularizer)}build(e){e=xt(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new j(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new rn({ndim:e.length,axes:{[t]:n}})];let s=[n];this.scale&&(this.gamma=this.addWeight("gamma",s,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",s,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",s,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",s,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return J(()=>{let n=t.training==null?!1:t.training,s=Xe(e),r=s.shape,a=r.length,o=Rr(0,a),i=this.axis>=0?this.axis:this.axis+a;o.splice(i,1);let l=Qi(1,a);l[i]=r[i];let u=o.slice();u.sort();let c=!v.arraysEqual(u,Rr(0,a).slice(0,a-1)),p=()=>{if(c){let y=U(this.movingMean.read(),l),x=U(this.movingVariance.read(),l),A=this.center?U(this.beta.read(),l):null,b=this.scale?U(this.gamma.read(),l):null;return Ep(s,y,x,A,b,this.epsilon)}else return Ep(s,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!n)return p();let[d,h,f]=hG(s,this.gamma.read(),this.beta.read(),o,this.epsilon),m=(y,x,A)=>{J(()=>{let b=1-A,w=y.read(),k=L(he(w,x),b);y.write(he(w,k))})};return(()=>{m(this.movingMean,h,this.momentum),m(this.movingVariance,f,this.momentum)})(),d})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Vt(this.betaInitializer),gammaInitializer:Vt(this.gammaInitializer),movingMeanInitializer:Vt(this.movingMeanInitializer),movingVarianceInitializer:Vt(this.movingVarianceInitializer),betaRegularizer:St(this.betaRegularizer),gammaRegularizer:St(this.gammaRegularizer),betaConstraint:gn(this.betaConstraint),gammaConstraint:gn(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};tx.className="BatchNormalization";de.registerClass(tx);var nx=class extends ut{constructor(e){if(e==null&&(e={}),super(e),this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=Ot(e.betaInitializer||"zeros"),this.gammaInitializer=Ot(e.gammaInitializer||"ones"),this.betaRegularizer=Mt(e.betaRegularizer),this.gammaRegularizer=Mt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=xt(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let r=0;r<this.axis.length;++r)this.axis[r]<0&&(this.axis[r]+=t);for(let r of this.axis)if(r<0||r>=t)throw new Error(`Invalid axis: ${r}`);if(this.axis.length!==qa(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(r=>e[r]),s=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,s):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,s):this.beta=null,this.built=!0}call(e,t){let n=Xe(e),s=n.shape,r=s.length;return J(()=>{let{mean:o,variance:i}=fh(n,this.axis,!0),l=Qi(1,r);for(let f of this.axis)l[f]=s[f];let u=f=>f!=null&&f.shape.length!==r?U(f,l):f,c=this.scale?u(this.gamma.read()):null,p=this.center?u(this.beta.read()):null,d=[],h=[];for(let f=0;f<r;++f)this.axis.indexOf(f)!==-1?(d.push(s[f]),h.push(1)):(d.push(1),h.push(s[f]));return o=js(o,d),i=js(i,d),c!=null&&(c=js(c,h)),p!=null&&(p=js(p,h)),Ep(n,o,i,p,c,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Vt(this.betaInitializer),gammaInitializer:Vt(this.gammaInitializer),betaRegularizer:St(this.betaRegularizer),gammaRegularizer:St(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};nx.className="LayerNormalization";de.registerClass(nx);function fG(e,t,n){return J(()=>{if(e.rank!==4)throw new j(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new j("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=_r()),n!=="channelsLast"&&n!=="channelsFirst")throw new j(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let s;return n==="channelsFirst"?s=[[0,0],[0,0],t[0],t[1]]:s=[[0,0],t[0],t[1],[0,0]],Js(e,s)})}var sx=class extends ut{constructor(e){if(e==null&&(e={}),super(e),this.dataFormat=e.dataFormat==null?_r():e.dataFormat,e.padding==null)this.padding=[[1,1],[1,1]];else if(typeof e.padding=="number")this.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,e.padding.length!==2)throw new j(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${e.padding.length} array.`);let t,n;if(typeof e.padding[0]=="number")t=[e.padding[0],e.padding[0]],n=[e.padding[1],e.padding[1]];else{if(e.padding=e.padding,e.padding[0].length!==2)throw new j(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${e.padding[0].length} array.`);if(t=e.padding[0],e.padding[1].length!==2)throw new j(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new rn({ndim:4})]}computeOutputShape(e){e=xt(e);let t,n;return this.dataFormat==="channelsFirst"?(e[2]!=null&&e[2]>=0?t=e[2]+this.padding[0][0]+this.padding[0][1]:t=null,e[3]!=null&&e[3]>=0?n=e[3]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],e[1],t,n]):(e[1]!=null&&e[1]>=0?t=e[1]+this.padding[0][0]+this.padding[0][1]:t=null,e[2]!=null&&e[2]>=0?n=e[2]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],t,n,e[3]])}call(e,t){return J(()=>fG(Xe(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};sx.className="ZeroPadding2D";de.registerClass(sx);function g2(e,t,n,s,r,a){return J(()=>{Yt(r),f8(a),Qs(s),n==null&&(n=[1,1]),s==null&&(s="valid"),r==null&&(r=_r()),a==null&&(a="max"),e=I5(e,r);let o,i=s==="same"?"same":"valid";return a==="max"?o=hh(e,t,n,i):o=ih(e,t,n,i),r==="channelsFirst"&&(o=st(o,[0,3,1,2])),o})}function uk(e,t,n,s,r,a){return J(()=>{Yt(r),f8(a),Qs(s),n==null&&(n=[1,1,1]),s==null&&(s="valid"),r==null&&(r=_r()),a==null&&(a="max"),e=rk(e,r);let o,i=s==="same"?"same":"valid";return a==="max"?o=TA(e,t,n,i):o=eA(e,t,n,i),r==="channelsFirst"&&(o=st(o,[0,4,1,2,3])),o})}var ck=class extends ut{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 j(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(vn(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 j(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);vn(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,Qs(this.padding),this.inputSpec=[new rn({ndim:3})]}computeOutputShape(e){e=xt(e);let t=Er(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return J(()=>{this.invokeCallHook(e,t),e=wh(Xe(e),2);let n=this.poolingFunction(Xe(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return rt(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},rx=class extends ck{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),g2(e,t,n,s,r,"max")}};rx.className="MaxPooling1D";de.registerClass(rx);var ax=class extends ck{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),g2(e,t,n,s,r,"avg")}};ax.className="AveragePooling1D";de.registerClass(ax);var dk=class extends ut{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new j(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];vn(this.poolSize,"poolSize"),vn(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Yt(this.dataFormat),Qs(this.padding),this.inputSpec=[new rn({ndim:4})]}computeOutputShape(e){e=xt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Er(t,this.poolSize[0],this.padding,this.strides[0]),n=Er(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 J(()=>(this.invokeCallHook(e,t),this.poolingFunction(Xe(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}},ox=class extends dk{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),g2(e,t,n,s,r,"max")}};ox.className="MaxPooling2D";de.registerClass(ox);var ix=class extends dk{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),g2(e,t,n,s,r,"avg")}};ix.className="AveragePooling2D";de.registerClass(ix);var pk=class extends ut{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 j(`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];vn(this.poolSize,"poolSize"),vn(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Yt(this.dataFormat),Qs(this.padding),this.inputSpec=[new rn({ndim:5})]}computeOutputShape(e){e=xt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],s=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Er(t,this.poolSize[0],this.padding,this.strides[0]),n=Er(n,this.poolSize[1],this.padding,this.strides[1]),s=Er(s,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,s]:[e[0],t,n,s,e[4]]}call(e,t){return J(()=>(this.invokeCallHook(e,t),this.poolingFunction(Xe(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}},lx=class extends pk{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),uk(e,t,n,s,r,"max")}};lx.className="MaxPooling3D";de.registerClass(lx);var ux=class extends pk{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),uk(e,t,n,s,r,"avg")}};ux.className="AveragePooling3D";de.registerClass(ux);var hk=class extends ut{constructor(e){super(e),this.inputSpec=[new rn({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new He}},cx=class extends hk{constructor(e){super(e||{})}call(e,t){return J(()=>{let n=Xe(e);return Bt(n,1)})}};cx.className="GlobalAveragePooling1D";de.registerClass(cx);var dx=class extends hk{constructor(e){super(e||{})}call(e,t){return J(()=>{let n=Xe(e);return mn(n,1)})}};dx.className="GlobalMaxPooling1D";de.registerClass(dx);var fk=class extends ut{constructor(e){super(e),this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Yt(this.dataFormat),this.inputSpec=[new rn({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new He}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},px=class extends fk{call(e,t){return J(()=>{let n=Xe(e);return this.dataFormat==="channelsLast"?Bt(n,[1,2]):Bt(n,[2,3])})}};px.className="GlobalAveragePooling2D";de.registerClass(px);var hx=class extends fk{call(e,t){return J(()=>{let n=Xe(e);return this.dataFormat==="channelsLast"?mn(n,[1,2]):mn(n,[2,3])})}};hx.className="GlobalMaxPooling2D";de.registerClass(hx);var mk=class extends ut{constructor(e){super(e),this.layer=e.layer}build(e){this.built=!0}get trainable(){return this.layer!=null?this.layer.trainable:!1}set trainable(e){this.layer!=null&&(this.layer.trainable=e)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(e){this.layer.setWeights(e)}getConfig(){let e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=super.getConfig();return Object.assign(e,t),e}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.layer!=null&&this.layer.setFastWeightInitDuringBuild(e)}static fromConfig(e,t,n={}){let s=t.layer,r=Nr(s,n);delete t.layer;let a={layer:r};return Object.assign(a,t),new e(a)}},fx=class extends mk{constructor(e){super(e),this.supportsMasking=!0}build(e){if(e=xt(e),e.length<3)throw new j(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=xt(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),s=e[1];return[n[0],s].concat(n.slice(1))}call(e,t){return J(()=>(e=Xe(e),ik((a,o)=>[Xe(this.layer.call(a,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};fx.className="TimeDistributed";de.registerClass(fx);function mG(e){Ql(gV,"BidirectionalMergeMode",e)}var gG="concat",mx=class extends mk{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Nr(n),t.goBackwards=t.goBackwards!==!0;let s={};if(s.className=e.layer.getClassName(),s.config=t,this.backwardLayer=Nr(s),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?gG:e.mergeMode,mG(this.mergeMode),e.weights)throw new He("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,s,r;return this.returnState&&(r=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,s=[n]):this.mergeMode==null?s=[n,n.slice()]:s=[n],this.returnState?this.mergeMode==null?s.concat(r).concat(r.slice()):[n].concat(r).concat(r.slice()):ps(s)}apply(e,t){let n=t==null?null:t.initialState,s=t==null?null:t.constants;t==null&&(t={});let r=ok(e,n,s,this.numConstants);if(e=r.inputs,n=r.initialState,s=r.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&s==null)return super.apply(e,t);let a=[],o=[];if(n!=null){let l=n.length;if(l%2>0)throw new j("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,a.push(...n);let u=n.map(c=>new rn({shape:c.shape}));this.forwardLayer.stateSpec=u.slice(0,l/2),this.backwardLayer.stateSpec=u.slice(l/2),o.push(...u)}if(s!=null)throw new He("Support for constants in Bidirectional layers is not implemented yet.");let i=a[0]instanceof Cr;for(let l of a)if(l instanceof Cr!==i)throw new j("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(i){let l=[e].concat(a),u=this.inputSpec.concat(o),c=this.inputSpec;this.inputSpec=u;let p=super.apply(l,t);return this.inputSpec=c,p}else return super.apply(e,t)}call(e,t){return J(()=>{let n=t.initialState,s,r;if(n==null)s=this.forwardLayer.call(e,t),r=this.backwardLayer.call(e,t);else{let i=n.slice(0,n.length/2),l=n.slice(n.length/2);s=this.forwardLayer.call(e,Object.assign(t,{initialState:i})),r=this.backwardLayer.call(e,Object.assign(t,{initialState:l}))}let a;this.returnState&&(Array.isArray(s)&&(a=s.slice(1).concat(r.slice(1))),s=s[0],r=r[0]),this.returnSequences&&(r=Ks(r,1));let 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i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.max(I("x",e,t,n),i,l)]}case"Mean":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.mean(I("x",e,t,n),i,l)]}case"Min":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.min(I("x",e,t,n),i,l)]}case"Sum":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.sum(I("x",e,t,n),i,l)]}case"All":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.all(I("x",e,t,n),i,l)]}case"Any":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.any(I("x",e,t,n),i,l)]}case"ArgMax":{let i=I("axis",e,t,n);return[s.argMax(I("x",e,t,n),i)]}case"ArgMin":{let i=I("axis",e,t,n);return[s.argMin(I("x",e,t,n),i)]}case"Prod":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.prod(I("x",e,t,n),i,l)]}case"Cumprod":{let i=I("axis",e,t,n),l=I("exclusive",e,t,n),u=I("reverse",e,t,n);return[s.cumprod(I("x",e,t,n),i,l,u)]}case"Cumsum":{let i=I("axis",e,t,n),l=I("exclusive",e,t,n),u=I("reverse",e,t,n);return[s.cumsum(I("x",e,t,n),i,l,u)]}case"Bincount":let r=I("x",e,t,n),a=I("weights",e,t,n),o=I("size",e,t,n);return[s.bincount(r,a,o)];case"DenseBincount":{let i=I("x",e,t,n),l=I("weights",e,t,n),u=I("size",e,t,n),c=I("binaryOutput",e,t,n);return[s.denseBincount(i,l,u,c)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},zj=(e,t,n,s=En)=>{switch(e.op){case"ConcatV2":case"Concat":{let r=I("n",e,t,n),a=I("axis",e,t,n),o=I("tensors",e,t,n);return o=o.slice(0,r),[s.concat(o,a)]}case"Gather":{let r=I("x",e,t,n),a=I("indices",e,t,n);return[s.gather(r,s.cast(a,"int32"),0)]}case"GatherV2":{let r=I("axis",e,t,n),a=I("batchDims",e,t,n),o=I("x",e,t,n),i=I("indices",e,t,n);return[s.gather(o,s.cast(i,"int32"),r,a)]}case"Reverse":{let r=I("dims",e,t,n),a=[];for(let i=0;i<r.length;i++)r[i]&&a.push(i);let o=I("x",e,t,n);return[s.reverse(o,a)]}case"ReverseV2":{let r=I("axis",e,t,n),a=I("x",e,t,n);return[s.reverse(a,r)]}case"Slice":{let r=I("begin",e,t,n),a=I("size",e,t,n);return[s.slice(I("x",e,t,n),r,a)]}case"StridedSlice":{let r=I("begin",e,t,n),a=I("end",e,t,n),o=I("strides",e,t,n),i=I("beginMask",e,t,n),l=I("endMask",e,t,n),u=I("ellipsisMask",e,t,n),c=I("newAxisMask",e,t,n),p=I("shrinkAxisMask",e,t,n),d=I("x",e,t,n);return[s.stridedSlice(d,r,a,o,i,l,u,c,p)]}case"Pack":return J(()=>{let r=I("axis",e,t,n),a=I("tensors",e,t,n),o=a[0].shape,i=s.squeeze(a[0]).shape,l=a.map(u=>{let c=v.arraysEqual(u.shape,o);if(!c&&!v.arraysEqual(s.squeeze(u).shape,i))throw new Error("the input tensors shape does not match");return c?u:s.reshape(u,o)});return[s.stack(l,r)]});case"Unpack":{let r=I("axis",e,t,n),a=I("tensor",e,t,n);return s.unstack(a,r)}case"Tile":{let r=I("reps",e,t,n);return[s.tile(I("x",e,t,n),r)]}case"Split":case"SplitV":{let r=I("axis",e,t,n),a=I("numOrSizeSplits",e,t,n),o=I("x",e,t,n);return s.split(o,a,r)}case"ScatterNd":{let r=I("indices",e,t,n),a=I("values",e,t,n),o=I("shape",e,t,n);return[s.scatterND(r,a,o)]}case"GatherNd":{let 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TypeError(`Node type ${e.op} is not implemented`)}},Bj=(e,t,n,s=En)=>{switch(e.op){case"FFT":return[s.fft(I("x",e,t,n))];case"IFFT":return[s.ifft(I("x",e,t,n))];case"RFFT":return[s.rfft(I("x",e,t,n))];case"IRFFT":return[s.irfft(I("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Wj=(e,t,n,s=En)=>{switch(e.op){case"StringNGrams":{let{nGrams:r,nGramsSplits:a}=s.string.stringNGrams(I("data",e,t,n),I("dataSplits",e,t,n),I("separator",e,t,n),I("nGramWidths",e,t,n),I("leftPad",e,t,n),I("rightPad",e,t,n),I("padWidth",e,t,n),I("preserveShortSequences",e,t,n));return[r,a]}case"StringSplit":{let{indices:r,values:a,shape:o}=s.string.stringSplit(I("input",e,t,n),I("delimiter",e,t,n),I("skipEmpty",e,t,n));return[r,a,o]}case"StringToHashBucketFast":return[s.string.stringToHashBucketFast(I("input",e,t,n),I("numBuckets",e,t,n))];default:throw TypeError(`Node type ${e.op} is not 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r=I("blockSize",e,t,n),a=I("dataFormat",e,t,n).toUpperCase();return[s.depthToSpace(I("x",e,t,n),r,a)]}case"BroadcastTo":return[s.broadcastTo(I("x",e,t,n),I("shape",e,t,n))];case"BroadcastArgs":return[s.broadcastArgs(I("s0",e,t,n),I("s1",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function s7(e,t,n,s,r=J){let a=((o,i,l)=>{switch(o.category){case"arithmetic":return r(()=>Aj(o,i,l));case"basic_math":return r(()=>xj(o,i,l));case"control":return Sj(o,i,l);case"convolution":return r(()=>Cj(o,i,l));case"creation":return r(()=>Tj(o,i,l));case"dynamic":return Nj(o,i,l);case"evaluation":return r(()=>Ej(o,i,l));case"image":return r(()=>$j(o,i,l));case"graph":return r(()=>Rj(o,i,l));case"logical":return r(()=>Pj(o,i,l));case"matrices":return r(()=>Fj(o,i,l));case"normalization":return r(()=>Oj(o,i,l));case"reduction":return r(()=>Mj(o,i,l));case"slice_join":return r(()=>zj(o,i,l));case"sparse":return r(()=>Lj(o,i,l));case"spectral":return r(()=>Bj(o,i,l));case"string":return r(()=>Wj(o,i,l));case"transformation":return r(()=>Vj(o,i,l));case"hash_table":return Dj(o,i,l,s);case"custom":let u=Sk(o.op);if(u&&u.customExecutor)return u.customExecutor(new yj(o,i,l));throw TypeError(`Custom op ${o.op} is not registered.`);default:throw TypeError(`Unknown op '${o.op}'. 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e?e.map(t=>t.id===0&&t.iterationId===0?"":`${t.frameName}-${t.iterationId}`).join("/"):""}enterFrame(e){this.contexts&&(this.lastId++,this.contexts=this.contexts.slice(),this.contexts.push(this.newFrame(this.lastId,e)),this._currentContextIds.unshift(this.contextIdforContexts(this.contexts)))}exitFrame(){if(this.contexts&&this.contexts.length>1)this.contexts=this.contexts.slice(),this.contexts.splice(-1),this.currentContextIds.shift();else throw new Error("Cannot exit frame, the context is empty")}nextIteration(){if(this.contexts&&this.contexts.length>0){this.contexts=this.contexts.slice(),this.lastId++;let e=Object.assign({},this.contexts[this.contexts.length-1]);e.iterationId+=1,e.id=this.lastId,this.contexts.splice(-1,1,e),this._currentContextIds.splice(0,1,this.contextIdforContexts(this.contexts))}else throw new Error("Cannot increase frame iteration, the context is empty")}getWeight(e){return this.weightMap[e]}addTensorArray(e){this.tensorArrayMap[e.id]=e}getTensorArray(e){return this.tensorArrayMap[e]}addTensorList(e){this.tensorListMap[e.id]=e}getTensorList(e){return this.tensorListMap[e]}dispose(e){for(let t in this.tensorArrayMap)this.tensorArrayMap[t].clearAndClose(e);for(let t in this.tensorListMap)this.tensorListMap[t].clearAndClose(e)}};function a7(e,t,n,s){let r=new Set,a=[],o=null,i=null,l=new Set,u=Object.keys(e).map(d=>Ss(d)[0]),c=[];s!=null&&(c=s.map(d=>Ss(d.name)[0]));let p=[...t];for(;p.length>0;){let d=p.pop();if((qk(d)||qj(d)||Xj(d))&&o==null&&(o=d,i=o.children.map(h=>h.name).filter(h=>r.has(h))),r.add(d.name),n[d.name]==null&&u.indexOf(d.name)===-1&&c.indexOf(d.name)===-1){if(d.inputs.length===0){a.push(d.name);continue}d.inputs.forEach(h=>{l.has(h.name)||(l.add(h.name),p.push(h))})}}return{inputs:e,outputs:t,usedNodes:r,missingInputs:a,dynamicNode:o,syncInputs:i}}function Uj(e,t,n){let{usedNodes:s,inputs:r}=n,a=[],o=Object.keys(r).map(c=>Ss(c)[0]).map(c=>e.nodes[c]),i=e.initNodes;o.forEach(c=>{s.has(c.name)&&a.push(c)}),e.weights.forEach(c=>{s.has(c.name)&&a.push(c)}),i!=null&&i.forEach(c=>{s.has(c.name)&&a.push(c)});let l=new Set,u=[];for(;a.length>0;){let c=a.pop();l.add(c.name),t[c.name]||u.push(c),c.children.forEach(p=>{!l.has(p.name)&&s.has(p.name)&&p.inputs.every(d=>l.has(d.name))&&a.push(p)})}return u}var Gj=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],Hj=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],jj=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function qk(e){return Gj.indexOf(e.op)>=0}function qj(e){return Hj.indexOf(e.op)>=0}function Xj(e){return jj.indexOf(e.op)>=0}var J3=class{constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},this.intermediateTensors={},this.keepTensorForDebug=!1,this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,e.functions!=null&&Object.keys(e.functions).forEach(n=>{this._functionExecutorMap[n]=new J3(e.functions[n],this)})}get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){let t=Object.keys(e).map(n=>e[n].map(s=>s.id));this._weightIds=[].concat(...t),this._weightMap=e}set resourceManager(e){this._resourceManager=e}get inputs(){return this._inputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(e=>e.signatureKey||e.name)}get outputNodes(){return this._outputs.map(e=>{let t=e.signatureKey||e.name;return e.defaultOutput?`${t}:${e.defaultOutput}`:t})}get functions(){return Object.keys(this._functions).reduce((e,t)=>(e[t]=this._functions[t].signature,e),{})}getCompilationKey(e,t){let n=e.map(r=>r.name).sort(),s=t.map(r=>r.name).sort();return n.join(this.SEPERATOR)+"--"+s.join(this.SEPERATOR)}compile(e,t){let n=a7(e,t,this.weightMap,this._initNodes),{missingInputs:s,dynamicNode:r,syncInputs:a}=n;if(r!=null)throw new Error(`This execution contains the node '${r.name}', which has the dynamic op '${r.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${a}]`);if(s.length>0){let o=t.map(l=>l.name),i=Object.keys(e);throw new Error(`Cannot compute the outputs [${o}] from the provided inputs [${i}]. Missing the following inputs: [${s}]`)}return Uj(this.graph,this.weightMap,n)}execute(e,t){e=this.mapInputs(e);let n=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let s=n.map(c=>this.graph.nodes[Ss(c)[0]]),r=t.map(c=>Ss(c)[0]),a=r.map(c=>this.graph.nodes[c]);this.resetIntermediateTensors(),a.length===0&&(a=this._outputs);let o=this.getCompilationKey(s,a),i=this.compiledMap.get(o);i==null&&(i=this.compile(e,a),this.compiledMap.set(o,i));let l={},u={};return J(()=>{let c=new r7(this.weightMap,l,u,this.functionExecutorMap),p=Object.assign({},this.weightMap);Object.keys(e).forEach(f=>{let[m,g]=Ss(f),y=[];y[g]=e[f],p[m]=y});let d=this.getFrozenTensorIds(p),h={};for(let f=0;f<i.length;f++){let m=i[f];if(!p[m.name]){let g=s7(m,p,c,this._resourceManager);if(v.isPromise(g))throw new Error(`The execution of the op '${m.op}' returned a promise. 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You can use model.execute() instead.");let y=i.filter(x=>!qk(x)&&!Jn(x.name,h,t)).map(x=>x.name);if(y.length>0){let x="";throw c!=null&&(x=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${p}]`),new Error(`Cannot compute the outputs [${y}] from the provided inputs [${r}]. 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u}processChildNodes(e,t,n,s,r,a){e.children.forEach(o=>{let[i]=Ur(o.name,n);r[i]||!a.has(o.name)||(o.op==="Merge"?o.inputNames.some(l=>!!Jn(l,s,n))&&(r[i]=!0,t.push({contexts:n.currentContext,node:o})):o.inputNames.every(l=>!!Jn(l,s,n))&&(r[i]=!0,t.push({contexts:n.currentContext,node:o})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let n=e[t],[s]=Ss(t),r=this.graph.nodes[s];if(r.attrParams.shape&&r.attrParams.shape.value){let a=r.attrParams.shape.value,o=a.length===n.shape.length&&n.shape.every((i,l)=>a[l]===-1||a[l]===i);v.assert(o,()=>`The shape of dict['${r.name}'] provided in model.execute(dict) must be [${a}], but was [${n.shape}]`)}r.attrParams.dtype&&r.attrParams.dtype.value&&v.assert(n.dtype===r.attrParams.dtype.value,()=>`The dtype of dict['${r.name}'] provided in model.execute(dict) must be ${r.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(e){let t={};for(let n 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if(this.loadOptions.requestInit!=null)this.handler=this.io.browserHTTPRequest(e,this.loadOptions);else{let t=this.io.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(this.io.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=this.handler.load();return v.isPromise(e)?e.then(t=>this.loadSync(t)):this.loadSync(e)}loadSync(e){this.artifacts=e;let t=this.artifacts.modelTopology,n=this.artifacts.signature;if(this.artifacts.userDefinedMetadata!=null){let r=this.artifacts.userDefinedMetadata;r.signature!=null&&(n=r.signature),r.structuredOutputKeys!=null&&(this.structuredOutputKeys=r.structuredOutputKeys)}this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;let s=this.io.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new J3(Qv.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(s),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let r=Qv.Instance.transformGraph(e.modelInitializer);this.initializer=new J3(r),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=this.io.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${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){let 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this.upstream.next()}},gq=class extends wn{constructor(e,t){super(),this.upstream=e,this.maxCount=t,this.count=0}summary(){return`${this.upstream.summary()} -> Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},yq=class extends wn{constructor(e,t,n=!0){super(),this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=n,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length<this.batchSize;){let t=await this.upstream.next();if(t.done)return this.enableSmallLastBatch&&e.length>0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},Aq=class extends wn{constructor(e,t){super(),this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;ne(e.value)}}},xq=class extends wn{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=Tr.getTensorsInContainer(e.value),n=this.transform(e.value),s=Tr.getTensorsInContainer(n);for(let r of t)Tr.isTensorInList(r,s)||r.dispose();return{value:n,done:!1}}},bq=class extends wn{constructor(e,t){super(),this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}},o7=class extends wn{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=Tr.getTensorsInContainer(e.value),n=await this.transform(e.value),s=Tr.getTensorsInContainer(n);for(let r of t)Tr.isTensorInList(r,s)||r.dispose();return{value:n,done:!1}}},kx=class extends wn{constructor(){super(),this.outputQueue=new vx,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}}},vq=class extends kx{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=Tr.getTensorsInContainer(e.value),n=this.transform(e.value),s=Tr.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let r of t)Tr.isTensorInList(r,s)||r.dispose();return!0}},eI=class extends wn{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}},Ha;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(Ha||(Ha={}));var wq=class extends wn{constructor(e,t=Ha.FAIL){super(),this.iterators=e,this.mismatchMode=t,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(e){await e;let t=0,n=0;function s(a){return a instanceof wn?{value:a.next().then(i=>(t++,i.done&&n++,i.value)),recurse:!1}:{value:null,recurse:!0}}let r=await Yk(this.iterators,s);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case Ha.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case Ha.SHORTEST:return{value:null,done:!0};case Ha.LONGEST:default:}return this.count++,{value:r,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},tI=class extends wn{constructor(e,t){super(),this.upstream=e,this.bufferSize=t,this.buffer=new Jk(t)}summary(){return`${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()}},kq=class extends tI{constructor(e,t,n){super(e,t),this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=sq.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}}},Jc=class{constructor(){this.size=null}batch(e,t=!0){let n=this;v.assert(e>0,()=>`batchSize needs to be positive, but it is
      ${e}`);let s;return this.size===1/0||this.size==null?s=this.size:t?s=Math.ceil(this.size/e):s=Math.floor(this.size/e),Is(async()=>(await n.iterator()).columnMajorBatch(e,t,Cq),s)}concatenate(e){let t=this,n;return this.size===1/0||e.size===1/0?n=1/0:this.size!=null&&e.size!=null?n=this.size+e.size:n=null,Is(async()=>(await t.iterator()).concatenate(await e.iterator()),n)}filter(e){let t=this,n;return this.size===1/0?n=1/0:n=null,Is(async()=>(await t.iterator()).filter(s=>J(()=>e(s))),n)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return Is(async()=>(await t.iterator()).map(n=>J(()=>e(n))),this.size)}mapAsync(e){let t=this;return Is(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return Is(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,n;return this.size!=null&&e>0?n=this.size*e:e===0?n=0:this.size!=null&&(e===void 0||e<0)?n=1/0:n=null,Is(async()=>{let s=wx(async()=>({value:await t.iterator(),done:!1}));return cq(s.take(e))},n)}skip(e){let t=this,n;return this.size!=null&&e>=0&&this.size>=e?n=this.size-e:this.size!=null&&(this.size<e||e===void 0||e<0)?n=0:n=null,Is(async()=>(await t.iterator()).skip(e),n)}shuffle(e,t,n=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified.  If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let s=this,r=nq.alea(t||v.now().toString());return Is(async()=>{let a=r.int32();return n&&(a+=r.int32()),(await s.iterator()).shuffle(e,a.toString())},this.size)}take(e){let t=this,n;return this.size!=null&&this.size>e?n=e:this.size!=null&&this.size<=e?n=this.size:n=null,Is(async()=>(await t.iterator()).take(e),n)}async toArray(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};Jc.MAX_BUFFER_SIZE=1e4;function Is(e,t=null){return new class extends Jc{constructor(){super(...arguments),this.size=t}async iterator(){return e()}}}function Iq(e){return Is(async()=>Qk(e),e.length)}function Sq(e){if(!rc(e))throw new Error("The argument to zip() must be an object or array.");let t;if(Array.isArray(e))for(let n=0;n<e.length;n++)t=t==null?e[n].size:Math.min(t,e[n].size);else if(e instanceof Object)for(let n in e)t=t==null?e[n].size:Math.min(t,e[n].size);return Is(async()=>{let n=await Yk(e,s=>{if(s instanceof Jc)return{value:s.iterator(),recurse:!1};if(rc(s))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return dq(n,Ha.SHORTEST)},t)}function Cq(e){if(e===null)return null;let t=e[0];return oq(t)?{value:Tq(e),recurse:!1}:{value:null,recurse:!0}}function Tq(e){if(e.length===0)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof tt?on(e):ft(e)}var nI=class extends Jc{constructor(e){super(),this.input=e}async iterator(){return(await this.input.iterator()).decodeUTF8().split(`
`).map(s=>(s.endsWith("\r")&&(s=s.slice(0,-1)),s))}},Hf='"',tp=Symbol("out"),i7=Symbol("field"),jf=Symbol("quote"),p3=Symbol("quoteafterquote"),l7=Symbol("quoteinquote"),sI=class extends Jc{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 nI(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((s,r)=>(s[r]=s[r]+1||1,s),{}),n=Object.keys(t).filter(s=>t[s]>1);if(v.assert(n.length===0,()=>"Duplicate column names found: "+n.toString()),this.columnConfigs){for(let s of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(s)===-1)throw new Error('The key "'+s+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let t=await(await this.base.iterator()).next();if(t.done)throw new Error("No data was found for CSV parsing.");let n=t.value;return this.parseRow(n,!1)}else return null}async iterator(){this.columnNamesValidated||await this.setColumnNames();let e=await this.base.iterator();return this.hasHeader&&(e=e.skip(1)),e.map(t=>this.makeDataElement(t))}makeDataElement(e){let t=this.parseRow(e),n={},s={};for(let r=0;r<this.fullColumnNames.length;r++){let a=this.fullColumnNames[r],o=this.columnConfigs?this.columnConfigs[a]:null;if(!(this.configuredColumnsOnly&&!o)){let i=t[r],l=null;if(i==="")if(o&&o.default!==void 0)l=o.default;else{if(o&&(o.required||o.isLabel))throw new Error(`Required column ${a} is empty in this line: ${e}`);l=void 0}else{let u=Number(i);if(isNaN(u))o&&o.dtype==="bool"?l=this.getBoolean(i):l=i;else if(!o||!o.dtype)l=u;else switch(o.dtype){case"float32":l=u;break;case"int32":l=Math.floor(u);break;case"bool":l=this.getBoolean(i);break;default:l=u}}o&&o.isLabel?s[a]=l:n[a]=l}}return Object.keys(s).length===0?n:{xs:n,ys:s}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let n=[],s=0,r=e.length,a=tp;for(let o=0;o<r;o++)switch(a){case tp:switch(e.charAt(o)){case Hf:s=o+1,a=jf;break;case this.delimiter:if(s=o+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),a=tp;break;default:a=i7,s=o;break}break;case i7:switch(e.charAt(o)){case this.delimiter:n.push(e.substring(s,o)),a=tp,s=o+1;break;default:}break;case jf:switch(e.charAt(o)){case Hf:a=p3;break;default:}break;case p3:switch(e.charAt(o)){case this.delimiter:n.push(e.substring(s,o-1)),a=tp,s=o+1;break;case Hf:a=jf;break;default:a=l7;break}break;case l7:switch(e.charAt(o)){case Hf:a=jf;break;default:}break;default:}if(a===p3?n.push(e.substring(s,r-1)):n.push(e.substring(s)),t&&n.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},rI=class extends wn{constructor(e){super(),this.microphoneConfig=e,this.isClosed=!1,this.fftSize=e.fftSize||1024;let t=Math.log2(this.fftSize);if(this.fftSize<0||t<4||t>14||!Number.isInteger(t))throw new Error(`Invalid fftSize: it must be a power of 2 between 2 to 4 and 2 to 14, but got ${this.fftSize}`);if(this.numFrames=e.numFramesPerSpectrogram||43,this.sampleRateHz=e.sampleRateHz,this.columnTruncateLength=e.columnTruncateLength||this.fftSize,this.audioTrackConstraints=e.audioTrackConstraints,this.smoothingTimeConstant=e.smoothingTimeConstant||0,this.includeSpectrogram=e.includeSpectrogram!==!1,this.includeWaveform=e.includeWaveform===!0,!this.includeSpectrogram&&!this.includeWaveform)throw new Error("Both includeSpectrogram and includeWaveform are false. At least one type of data should be returned.")}summary(){return"microphone"}static async create(e={}){if(!X().get("IS_BROWSER"))throw new Error("microphone API is only supported in browser environment.");let t=new rI(e);return await t.start(),t}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(n){throw new Error(`Error thrown while initializing video stream: ${n.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let e=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new e,!this.sampleRateHz)this.sampleRateHz=this.audioContext.sampleRate;else if(this.audioContext.sampleRate!==this.sampleRateHz)throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);let t=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,t.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let e,t,n=await this.getAudioData();if(this.includeSpectrogram){let s=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(s,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let s=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(s,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:e,waveform:t},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let e=[],t=[],n=0;return new Promise(s=>{let r=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-1/0&&s({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(r),s({freqDataQueue:e,timeDataQueue:t}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(e){let t=e[0].length,n=new Float32Array(e.length*t);return e.forEach((s,r)=>n.set(s,r*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(v.sizeFromShape(t));return n.set(e,n.length-e.length),ft(n,t)}},aI=class extends wn{constructor(e,t){if(super(),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=Ft([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,s=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,r=(1-n)/2,a=(1-s)/2,o=r+n,i=s+a;this.cropBox=or([a,r,i,o],[1,4])}else this.cropBox=or([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(!X().get("IS_BROWSER"))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 aI(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=Ys.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: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return J(()=>{let t=Kt(ge(e,"float32"),0),n;n=Ne.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let s=n.shape;return U(n,s.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(t=>t.stop());try{this.webcamVideoElement.srcObject=null}catch(t){console.log(t),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},oI=class{},iI=class extends wn{split(e){return new Nq(this,e)}},Nq=class extends iI{constructor(e,t){super(),this.upstream=e,this.impl=new Eq(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Eq=class extends kx{constructor(e,t){super(),this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let n of t.slice(0,-1))this.outputQueue.push(n);return this.carryover=t[t.length-1],!0}},Rq=class extends wn{decodeUTF8(){return new _q(this)}},_q=class extends iI{constructor(e){super(),this.upstream=e,this.impl=new Dq(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Dq=class extends kx{constructor(e){if(super(),this.upstream=e,X().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=Y7();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let n;return X().get("IS_BROWSER")?n=this.decoder.decode(t,{stream:!0}):n=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(n),!0}},lI=class extends Rq{constructor(e,t={}){super(),this.file=e,this.options=t,v.assert(e instanceof Uint8Array||(X().get("IS_BROWSER")?e instanceof File||e instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=t.offset||0,this.chunkSize=t.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((t,n)=>{let s=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)t(new Uint8Array(this.file.slice(this.offset,s)));else{let r=new FileReader;r.onload=o=>{let i=r.result;if(i instanceof 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a=v.sizeFromShape(s),o=t[0],i=r.length,l=[],u=1,c=-1;for(let g=0;g<i;++g){let y=r[g];if(y===-1){if(c!==-1)throw new Error(C.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(c,g));c=g,l.push(1)}else{if(y<0)throw new Error(C.getSparseReshapeNegativeOutputDimErrorMessage(g,y));u*=y,l.push(y)}}if(c!==-1){if(u<=0)throw new Error(C.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage());let g=Math.trunc(a/u);if(u*g!==a)throw new Error(C.getSparseReshapeInputOutputMultipleErrorMessage(s,l));l[c]=g}if(v.sizeFromShape(l)!==a)throw new Error(C.getSparseReshapeInputOutputMismatchErrorMessage(s,l));let d=s.length,h=[];if(d>0){h[d-1]=1;for(let g=d-2;g>=0;--g)h[g]=h[g+1]*s[g+1]}let f=[];if(i>0){f[i-1]=1;for(let g=i-2;g>=0;--g)f[g]=f[g+1]*l[g+1]}let m=v.getArrayFromDType(n,o*i);for(let g=0;g<o;++g){let y=0;for(let x=0;x<d;++x)y+=e[g*d+x]*h[x];for(let x=0;x<i;++x)m[g*i+x]=Math.trunc(y/f[x]),y%=f[x]}return[m,[o,i],l]}function Dx(e,t,n,s,r,a=!1,o=0){let i=s.length,l=[t[0],e.length/t[0]],u=l[1],p=i>0?r[i-1]+1:0;if(p<0)throw new Error(C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let d=t.slice();d[0]=p;let h=d.reduce((A,b)=>A*b,1),f=v.getArrayFromDType(n,h);if(i===0)return p>0&&f.fill(o),[f,d];if(p<=0)throw new Error(C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let m=0,g=1,y=0,x=r[m];for(;;){let A=0;if(g<i){if(A=r[g],x===A){++g;continue}if(x>=A)throw new Error(C.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage())}if(x<0||x>=p)throw new Error(C.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(x,p));x>y&&f.fill(o,y*u,x*u);for(let b=m;b<g;++b){let w=s[b];if(w<0||w>=l[0])throw new Error(C.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(b,s[b],l[0]));for(let k=0;k<u;k++)f[x*u+k]+=e[w*u+k]}if(a)for(let b=0;b<u;b++)f[x*u+b]/=g-m;if(m=g,++g,y=x+1,x=A,g>i)break}return y<p&&f.fill(o,y*u,p*u),[f,d]}var DX=ci(e=>Math.sqrt(e)),$X=bt(Jo,e=>Math.sqrt(e)),PX={kernelName:Jo,backendName:"cpu",kernelFunc:$X},BI=un((e,t)=>{let n=e-t;return n*n}),FX=kn(ti,BI),OX={kernelName:ti,backendName:"cpu",kernelFunc:FX};function WI(e,t,n,s){let r=Le(e,t.dtype);for(let a=0;a<r.size;a++){let o=r.indexToLoc(a),i=new Array(o.length);for(let l=0;l<i.length;l++)i[l]=o[l]*n[l]+s[l];r.set(t.get(...i),...o)}return r}var MX=class{constructor(e,t,n,s,r,a){this.separator=v.encodeString(e),this.nGramWidths=t,this.leftPad=v.encodeString(n),this.rightPad=v.encodeString(s),this.padWidth=r,this.preserveShort=a}getPadWidth(e){return Math.min(this.padWidth<0?e-1:this.padWidth,e-1)}getNumNGrams(e,t){let n=this.getPadWidth(t);return Math.max(0,e+2*n-t+1)}createNGrams(e,t,n,s,r,a){for(let o=0;o<r;++o){let i=this.getPadWidth(a),l=Math.max(0,i-o),u=Math.max(0,i-(r-(o+1))),c=a-(l+u),p=t+(l>0?0:o-i),d=0;d+=l*this.leftPad.length;for(let 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i=e.locToIndex(o);s.values[r]=e.values[i]}return s}var op=(e,t)=>{let n=t.value-e.value;return n===0?e.index-t.index:n};function GI(e,t,n=0,s=e.length-1){for(;s>n;){if(s-n>600){let i=s-n+1,l=t-n+1,u=Math.log(i),c=.5*Math.exp(2*u/3),p=.5*Math.sqrt(u*c*(i-c)/i)*Math.sign(l-i/2),d=Math.max(n,Math.floor(t-l*c/i+p)),h=Math.min(s,Math.floor(t+(i-l)*c/i+p));GI(e,t,d,h)}let r=e[t],a=n,o=s;for(v.swap(e,n,t),op(e[s],r)>0&&v.swap(e,n,s);a<o;){for(v.swap(e,a,o),a++,o--;op(e[a],r)<0;)a=a+1;for(;op(e[o],r)>0;)o=o-1}op(e[n],r)===0?v.swap(e,n,o):(o=o+1,v.swap(e,o,s)),o<=t&&(n=o+1),t<=o&&(s=o-1)}}function HI(e,t,n,s,r){let a=t[t.length-1],[o,i]=[e.length/a,a],l=v.getTypedArrayFromDType(n,o*s),u=v.getTypedArrayFromDType("int32",o*s);for(let p=0;p<o;p++){let d=p*i,h=e.subarray(d,d+i),f=new Array(h.length);h.forEach((x,A)=>f[A]={value:x,index:A}),s<f.length&&(GI(f,s),f=f.slice(0,s)),r&&f.sort(op);let m=p*s,g=l.subarray(m,m+s),y=u.subarray(m,m+s);for(let x=0;x<s;x++)g[x]=f[x].value,y[x]=f[x].index}let c=t.slice();return c[c.length-1]=s,[Le(c,n,l),Le(c,"int32",u)]}function jI(e,t,n,s){let r=v.parseAxisParam(t,n)[0],a=[1,n[0],1];for(let f=0;f<r;f++)a[0]*=n[f];a[1]=n[r];for(let f=r+1;f<n.length;f++)a[2]*=n[f];let o={},i=new Int32Array(n[r]),l=new fn(a,s,e),u=[],c=a[0]===1&&a[2]===1;for(let f=0;f<n[r];f++){let m;if(c)m=e[f].toString();else{let g=[];for(let y=0;y<a[0];y++)for(let x=0;x<a[2];x++)g.push(l.get(y,f,x));m=g.join(",")}if(o[m]!==void 0)i[f]=o[m];else{let g=Object.keys(o).length;o[m]=g,i[f]=g,u.push(f)}}let p=a.slice();p[1]=Object.keys(o).length;let d=new fn(p,s);u.forEach((f,m)=>{for(let g=0;g<a[0];g++)for(let y=0;y<a[2];y++)d.set(l.get(g,f,y),g,m,y)});let h=n.slice();return h[r]=p[1],{outputValues:d.values,outputShape:h,indices:i}}jl("cpu",()=>new Ix,1);var qI=bt(Io,e=>e>=0?e:Math.exp(e)-1),WX={kernelName:Io,backendName:"cpu",kernelFunc:qI};function XI(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{alpha:a}=s;Ce([r],"leakyRelu");let o=v.sizeFromShape(r.shape),i=n.data.get(r.dataId).values,l=v.getTypedArrayFromDType("float32",o);for(let u=0;u<i.length;u++)l[u]=i[u]<0?a*i[u]:i[u];return n.makeTensorInfo(r.shape,"float32",l)}var VX={kernelName:_o,backendName:"cpu",kernelFunc:XI},UX=un((e,t)=>e<0?t*e:e);function KI(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t;Ce([s,r],"prelu");let a=n.data.get(s.dataId).values,o=n.data.get(r.dataId).values,[i,l]=UX(s.shape,r.shape,a,o,"float32");return n.makeTensorInfo(l,"float32",i)}var GX={kernelName:Uo,backendName:"cpu",kernelFunc:KI},ZI=bt(Ho,e=>Math.max(0,e)),HX={kernelName:Ho,backendName:"cpu",kernelFunc:ZI},YI=bt(Xo,e=>Math.min(Math.max(0,e),6)),jX={kernelName:Xo,backendName:"cpu",kernelFunc:YI};function _m(e,t,n,s,r){if(n==="linear")return Kr({inputs:{x:t},backend:e});if(n==="relu")return ZI({inputs:{x:t},backend:e});if(n==="elu")return qI({inputs:{x:t},backend:e});if(n==="relu6")return YI({inputs:{x:t},backend:e});if(n==="prelu")return KI({inputs:{x:t,alpha:s},backend:e});if(n==="leakyrelu")return XI({inputs:{x:t},backend:e,attrs:{alpha:r}});if(n==="sigmoid")return MI({inputs:{x:t},backend:e});throw new Error(`Activation ${n} has not been implemented for the CPU backend.`)}function Rt(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{shape:a}=s,o=v.sizeFromShape(r.shape),i=v.inferFromImplicitShape(a,o),l=v.sizeFromShape(i);v.assert(o===l,()=>`The new shape (${i}) has ${l} elements and the old shape (${r.shape}) has ${o} elements. 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b=o?[g,c,d]:[g,d,c],w=i?[y,h,p]:[y,p,h],k=Rt({inputs:{x:r},backend:n,attrs:{shape:b}}),S=Rt({inputs:{x:a},backend:n,attrs:{shape:w}}),E=o?k.shape[1]:k.shape[2],R=o?k.shape[2]:k.shape[1],P=i?S.shape[1]:S.shape[2],_=Math.max(g,y),$=n.data.get(k.dataId).values,T=n.data.get(S.dataId).values,F=v.computeStrides(k.shape),G=v.computeStrides(S.shape),[q,z,Z]=o?[F[0],1,F[1]]:[F[0],F[1],1],[B,ee,Q]=i?[1,G[1],G[0]]:[G[1],1,G[0]],oe=R*P,Y=Le([_,R,P],k.dtype),ae=Y.values,le=n.blockSize;for(let ye=0;ye<_;ye++)for(let we=0;we<R;we+=le)for(let Re=0;Re<P;Re+=le)for(let _e=0;_e<E;_e+=le){let Be=Math.min(we+le,R),Ge=Math.min(Re+le,P),ot=Math.min(_e+le,E);for(let dt=we;dt<Be;dt++)for(let pt=Re;pt<Ge;pt++){let At=0;for(let $e=_e;$e<ot;$e++){let Tt=Math.min(ye,g-1)*q,It=Math.min(ye,y-1)*Q,Un=$[Tt+dt*z+$e*Z],Qt=T[$e*B+pt*ee+It];At+=Un*Qt}ae[ye*oe+(dt*P+pt)]+=At}}return n.disposeIntermediateTensorInfo(k),n.disposeIntermediateTensorInfo(S),n.makeTensorInfo(A,Y.dtype,Y.values)}var XX={kernelName:fo,backendName:"cpu",kernelFunc:JI};function KX(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=s,d,h,f,m=[];d=JI({inputs:{a:r,b:a},attrs:{transposeA:l,transposeB:u},backend:n}),o&&(h=ac({inputs:{a:d,b:o},backend:n}),m.push(d),d=h),c&&(f=_m(n,d,c,i,p),m.push(d),d=f);for(let y of m)n.disposeIntermediateTensorInfo(y);return d}var ZX={kernelName:Ya,backendName:"cpu",kernelFunc:KX},YX=bt(dc,e=>Math.acos(e)),JX={kernelName:dc,backendName:"cpu",kernelFunc:YX},QX=bt(pc,e=>Math.acosh(e)),eK={kernelName:pc,backendName:"cpu",kernelFunc:QX};function tK(e){let{inputs:t,backend:n}=e,s=t;Ce(t,"addN");let r=s.map(i=>n.data.get(i.dataId).values),a=Le(s[0].shape,s[0].dtype),o=a.values;for(let i=0;i<s.length;i++){let l=r[i];for(let u=0;u<o.length;u++)o[u]+=l[u]}return n.makeTensorInfo(a.shape,a.dtype,a.values)}var nK={kernelName:co,backendName:"cpu",kernelFunc:tK};function sK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;Ce(r,"all");let i=v.parseAxisParam(a,r.shape),l=i,u=C.getAxesPermutation(l,r.shape.length),c=r;u!=null&&(c=gs({inputs:{x:r},backend:n,attrs:{perm:u}}),l=C.getInnerMostAxes(l.length,r.shape.length)),C.assertAxesAreInnerMostDims("all",l,c.shape.length);let[p,d]=C.computeOutAndReduceShapes(c.shape,l),h=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(p),c.dtype),m=n.data.get(c.dataId).values;for(let y=0;y<f.length;++y){let x=y*h,A=m[x];for(let b=0;b<h;++b){let w=m[x+b];A=A&&w}f[y]=A}u!=null&&n.disposeIntermediateTensorInfo(c);let g=n.makeTensorInfo(p,c.dtype,f);if(o){let y=C.expandShapeToKeepDim(p,i),x=Rt({inputs:{x:g},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(g),x}return g}var rK={kernelName:hc,backendName:"cpu",kernelFunc:sK};function aK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;Ce(r,"any");let i=v.parseAxisParam(a,r.shape),l=i,u=C.getAxesPermutation(l,r.shape.length),c=r;u!=null&&(c=gs({inputs:{x:r},backend:n,attrs:{perm:u}}),l=C.getInnerMostAxes(l.length,r.shape.length)),C.assertAxesAreInnerMostDims("any",l,c.shape.length);let[p,d]=C.computeOutAndReduceShapes(c.shape,l),h=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(p),c.dtype),m=n.data.get(c.dataId).values;for(let y=0;y<f.length;++y){let x=y*h,A=m[x];for(let b=0;b<h;++b){let w=m[x+b];A=A||w}f[y]=A}u!=null&&n.disposeIntermediateTensorInfo(c);let g=n.makeTensorInfo(p,c.dtype,f);if(o){let y=C.expandShapeToKeepDim(p,i),x=Rt({inputs:{x:g},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(g),x}return g}var oK={kernelName:fc,backendName:"cpu",kernelFunc:aK};function iK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s;Ce(r,"argMax");let o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=gs({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),o=[o[0]],C.assertAxesAreInnerMostDims("argMax",o,l.shape.length);let[c,p]=C.computeOutAndReduceShapes(l.shape,o),d=v.sizeFromShape(c),h=v.makeZerosTypedArray(d,"int32"),f=v.sizeFromShape(p),m=n.data.get(l.dataId).values;for(let g=0;g<h.length;++g){let y=g*f,x=m[y],A=0;for(let b=0;b<f;++b){let w=m[y+b];w>x&&(x=w,A=b)}h[g]=A}return u.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.makeTensorInfo(c,"int32",h)}var lK={kernelName:po,backendName:"cpu",kernelFunc:iK};function uK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s;Ce(r,"argMin");let o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=gs({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),o=[o[0]],C.assertAxesAreInnerMostDims("argMin",o,l.shape.length);let[c,p]=C.computeOutAndReduceShapes(l.shape,o),d=v.sizeFromShape(c),h=v.makeZerosTypedArray(d,"int32"),f=v.sizeFromShape(p),m=n.data.get(l.dataId).values;for(let g=0;g<h.length;++g){let y=g*f,x=m[y],A=0;for(let b=0;b<f;++b){let w=m[y+b];w<x&&(x=w,A=b)}h[g]=A}return u.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.makeTensorInfo(c,"int32",h)}var cK={kernelName:mc,backendName:"cpu",kernelFunc:uK},dK=bt(gc,e=>Math.asin(e)),pK={kernelName:gc,backendName:"cpu",kernelFunc:dK},hK=bt(yc,e=>Math.asinh(e)),fK={kernelName:yc,backendName:"cpu",kernelFunc:hK},mK=bt(Ac,e=>Math.atan(e)),gK={kernelName:Ac,backendName:"cpu",kernelFunc:mK},yK=un((e,t)=>Math.atan2(e,t)),AK=kn(bc,yK),xK={kernelName:bc,backendName:"cpu",kernelFunc:AK},bK=bt(xc,e=>Math.atanh(e)),vK={kernelName:xc,backendName:"cpu",kernelFunc:bK};function Mx(e,t,n,s,r,a){let o=r.strideHeight,i=r.strideWidth,l=r.dilationHeight,u=r.dilationWidth,c=r.effectiveFilterHeight,p=r.effectiveFilterWidth,d=r.padInfo.top,h=r.padInfo.left,f=a==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=Le(r.outShape,n),g=m.values,y=r.outShape[1]*r.outShape[2]*r.outShape[3],x=r.outShape[2]*r.outShape[3],A=r.outShape[3];for(let b=0;b<r.batchSize;++b){let w=b*y,k=b*s[0];for(let S=0;S<r.inChannels;++S)for(let E=0;E<r.outHeight;++E){let R=E*o-d,P=Math.max(0,R),_=Math.min(r.inHeight,c+R),$=w+E*x;for(let T=0;T<r.outWidth;++T){let F=T*i-h,G=Math.max(0,F),q=Math.min(r.inWidth,p+F),z=f,Z=0,B=0;for(let Q=P;Q<_;Q+=l){let oe=k+Q*s[1];for(let Y=G;Y<q;Y+=u){let ae=oe+Y*s[2],le=e[ae+S];a==="max"&&le>z?z=le:a==="avg"&&(Z+=le,B++)}if(isNaN(z))break}let ee=$+T*A+S;g[ee]=a==="avg"?Z/B:z}}}return m}function QI(e,t,n,s,r=!1,a=!1){let o=Le(s.outShape,"int32"),i=s.strideHeight,l=s.strideWidth,u=s.dilationHeight,c=s.dilationWidth,p=s.effectiveFilterHeight,d=s.effectiveFilterWidth,h=s.padInfo.top,f=s.padInfo.left,m=Le(t,n,e);for(let g=0;g<s.batchSize;++g)for(let y=0;y<s.inChannels;++y)for(let x=0;x<s.outHeight;++x){let A=x*i-h,b=A;for(;b<0;)b+=u;let w=Math.min(s.inHeight,p+A);for(let k=0;k<s.outWidth;++k){let S=k*l-f,E=S;for(;E<0;)E+=c;let R=Math.min(s.inWidth,d+S),P=Number.NEGATIVE_INFINITY,_=-1;for(let $=b;$<w;$+=u){let T=$-A;for(let F=E;F<R;F+=c){let G=F-S,q=m.get(g,$,F,y);q>P&&(P=q,r?_=a?((g*s.inHeight+$)*s.inWidth+F)*s.inChannels+y:($*s.inWidth+F)*s.inChannels+y:_=T*d+G)}}o.set(_,g,x,k,y)}}return o}function eS(e,t,n,s,r,a){let o=r.strideDepth,i=r.strideHeight,l=r.strideWidth,u=r.dilationDepth,c=r.dilationHeight,p=r.dilationWidth,d=r.effectiveFilterDepth,h=r.effectiveFilterHeight,f=r.effectiveFilterWidth,m=r.padInfo.front,g=r.padInfo.top,y=r.padInfo.left,x=a==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,A=Le(r.outShape,n),b=A.values,w=r.outShape[1]*r.outShape[2]*r.outShape[3]*r.outShape[4],k=r.outShape[2]*r.outShape[3]*r.outShape[4],S=r.outShape[3]*r.outShape[4],E=r.outShape[4];for(let R=0;R<r.batchSize;++R){let P=R*w,_=R*s[0];for(let $=0;$<r.inChannels;++$)for(let T=0;T<r.outDepth;++T){let F=T*o-m,G=F;for(;G<0;)G+=u;let q=Math.min(r.inDepth,d+F),z=P+T*k;for(let Z=0;Z<r.outHeight;++Z){let B=Z*i-g,ee=B;for(;ee<0;)ee+=c;let Q=Math.min(r.inHeight,h+B),oe=z+Z*S;for(let Y=0;Y<r.outWidth;++Y){let ae=Y*l-y,le=ae;for(;le<0;)le+=p;let ye=Math.min(r.inWidth,f+ae),we=oe+Y*E,Re=x,_e=0,Be=0;for(let ot=G;ot<q;ot+=u){let dt=_+ot*s[1];for(let pt=ee;pt<Q;pt+=c){let At=dt+pt*s[2];for(let $e=le;$e<ye;$e+=p){let Tt=At+$e*s[3],It=e[Tt+$];if(a==="max"&&It>Re?Re=It:a==="avg"&&(_e+=It,Be++),isNaN(Re))break}if(isNaN(Re))break}if(isNaN(Re))break}let Ge=we+$;b[Ge]=a==="avg"?_e/Be:Re}}}}return A}function wK(e,t){let n=Le(t.outShape,"int32"),s=t.strideDepth,r=t.strideHeight,a=t.strideWidth,o=t.dilationDepth,i=t.dilationHeight,l=t.dilationWidth,u=t.effectiveFilterDepth,c=t.effectiveFilterHeight,p=t.effectiveFilterWidth,d=t.padInfo.front,h=t.padInfo.top,f=t.padInfo.left;for(let m=0;m<t.batchSize;++m)for(let g=0;g<t.inChannels;++g)for(let y=0;y<t.outDepth;++y){let x=y*s-d,A=x;for(;A<0;)A+=o;let b=Math.min(t.inDepth,u+x);for(let w=0;w<t.outHeight;++w){let k=w*r-h,S=k;for(;S<0;)S+=i;let E=Math.min(t.inHeight,c+k);for(let R=0;R<t.outWidth;++R){let P=R*a-f,_=P;for(;_<0;)_+=l;let $=Math.min(t.inWidth,p+P),T=Number.NEGATIVE_INFINITY,F=-1;for(let G=A;G<b;G+=o){let q=G-x;for(let z=S;z<E;z+=i){let Z=z-k;for(let B=_;B<$;B+=l){let ee=B-P,Q=e.get(m,G,z,B,g);Q>=T&&(T=Q,F=q*c*p+Z*c+ee)}}}n.set(F,m,y,w,R,g)}}}return n}function kK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;Ce(r,"avgPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;v.assert(C.eitherStridesOrDilationsAreOne(o,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=C.computePool2DInfo(r.shape,a,o,u,i,l),p;if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))p=Kr({inputs:{x:r},backend:n});else{let d=n.data.get(r.dataId).values,h=v.computeStrides(r.shape),f=Mx(d,r.shape,r.dtype,h,c,"avg");p=n.makeTensorInfo(c.outShape,r.dtype,f.values)}return p}var IK={kernelName:ho,backendName:"cpu",kernelFunc:kK};function SK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l,dataFormat:u}=s;Ce(r,"avgPool3d");let c=C.computePool3DInfo(r.shape,a,o,1,i,l,u),p=n.data.get(r.dataId).values,d=eS(p,r.shape,r.dtype,v.computeStrides(r.shape),c,"avg");return n.makeTensorInfo(d.shape,"float32",d.values)}var CK={kernelName:Mp,backendName:"cpu",kernelFunc:SK};function TK(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=s;Ce([r,a],"avgPool3DGrad");let c=C.computePool3DInfo(a.shape,o,i,1,l,u),p=c.strideDepth,d=c.strideHeight,h=c.strideWidth,f=c.filterDepth,m=c.filterHeight,g=c.filterWidth,y=c.dilationDepth,x=c.dilationHeight,A=c.dilationWidth,b=c.effectiveFilterDepth,w=c.effectiveFilterHeight,k=c.effectiveFilterWidth,S=b-1-c.padInfo.front,E=k-1-c.padInfo.left,R=w-1-c.padInfo.top,P=Le(a.shape,"float32"),_=1/(f*m*g),$=n.bufferSync(r);for(let T=0;T<c.batchSize;++T)for(let F=0;F<c.inChannels;++F)for(let G=0;G<c.inDepth;++G)for(let q=0;q<c.inHeight;++q)for(let z=0;z<c.inWidth;++z){let Z=G-S,B=q-R,ee=z-E,Q=0;for(let oe=0;oe<b;oe+=y){let Y=(Z+oe)/p;if(!(Y<0||Y>=c.outDepth||Math.floor(Y)!==Y))for(let ae=0;ae<w;ae+=x){let le=(B+ae)/d;if(!(le<0||le>=c.outHeight||Math.floor(le)!==le))for(let ye=0;ye<k;ye+=A){let we=(ee+ye)/h;if(we<0||we>=c.outWidth||Math.floor(we)!==we)continue;Q+=$.get(T,Y,le,we,F)}}}P.set(Q*_,T,G,q,z,F)}return n.makeTensorInfo(P.shape,P.dtype,P.values)}var NK={kernelName:Gm,backendName:"cpu",kernelFunc:TK};function EK(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a;Ce([r,a],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=s,c=C.computePool2DInfo(o.shape,i,l,1,u),p=c.strideHeight,d=c.strideWidth,h=c.filterHeight,f=c.filterWidth,m=c.dilationHeight,g=c.dilationWidth,y=c.effectiveFilterHeight,x=c.effectiveFilterWidth,A=x-1-c.padInfo.left,b=y-1-c.padInfo.top,w=Le(o.shape,"float32"),k=1/(h*f),S=n.data.get(r.dataId).values,E=Le(r.shape,"float32",S);for(let R=0;R<c.batchSize;++R)for(let P=0;P<c.inChannels;++P)for(let _=0;_<c.inHeight;++_)for(let $=0;$<c.inWidth;++$){let T=_-b,F=$-A,G=0;for(let q=0;q<y;q+=m){let z=(T+q)/p;if(!(z<0||z>=c.outHeight||Math.floor(z)!==z))for(let Z=0;Z<x;Z+=g){let B=(F+Z)/d;if(B<0||B>=c.outWidth||Math.floor(B)!==B)continue;G+=E.get(R,z,B,P)}}w.set(G*k,R,_,$,P)}return n.makeTensorInfo(w.shape,w.dtype,w.values)}var RK={kernelName:Um,backendName:"cpu",kernelFunc:EK};function _K(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,scale:a,offset:o,mean:i,variance:l}=t;v.assert(i.shape.length===l.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(o==null||i.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(a==null||i.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks."),Ce([r,i,l,a,o],"batchNorm");let{varianceEpsilon:u}=s;u==null&&(u=.001);let c=n.data.get(r.dataId).values,p=n.data.get(i.dataId).values,d=n.data.get(l.dataId).values,h=a?n.data.get(a.dataId).values:new Float32Array([1]),f=o?n.data.get(o.dataId).values:new Float32Array([0]),m=new Float32Array(c.length),g=f.length,y=h.length,x=d.length,A=p.length,b=0,w=0,k=0,S=0;for(let E=0;E<c.length;++E)m[E]=f[b++]+(c[E]-p[w++])*h[k++]/Math.sqrt(d[S++]+u),b>=g&&(b=0),w>=A&&(w=0),k>=y&&(k=0),S>=x&&(S=0);return n.makeTensorInfo(r.shape,r.dtype,m)}var DK={kernelName:No,backendName:"cpu",kernelFunc:_K};function $K(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s;Ce([r],"batchToSpaceND");let i=a.reduce((y,x)=>y*x),l=C.getReshaped(r.shape,a,i),u=C.getPermuted(l.length,a.length),c=C.getReshapedPermuted(r.shape,a,i),p=C.getSliceBeginCoords(o,a.length),d=C.getSliceSize(c,o,a.length),h=Rt({inputs:{x:r},backend:n,attrs:{shape:l}}),f=gs({inputs:{x:h},backend:n,attrs:{perm:u}}),m=Rt({inputs:{x:f},backend:n,attrs:{shape:c}}),g=tl({inputs:{x:m},backend:n,attrs:{begin:p,size:d}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),g}var PK={kernelName:il,backendName:"cpu",kernelFunc:$K};function FK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o}=s,i=n.data.get(r.dataId).values,l=n.data.get(a.dataId).values,u=Tx(i,l,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,u)}var OK={kernelName:Hm,backendName:"cpu",kernelFunc:FK};function MK(e){let{inputs:t,backend:n}=e,{s0:s,s1:r}=t,a=n.data.get(s.dataId).values,o=n.data.get(r.dataId).values,i=C.assertAndGetBroadcastShape(Array.from(a),Array.from(o));return n.makeTensorInfo([i.length],"int32",Int32Array.from(i))}var zK={kernelName:jm,backendName:"cpu",kernelFunc:MK},LK=bt(xa,(e,t)=>{let n=t;return e>n.clipValueMax?n.clipValueMax:e<n.clipValueMin?n.clipValueMin:e}),BK={kernelName:xa,backendName:"cpu",kernelFunc:LK},WK=e=>{let{x:t}=e.inputs,n=e.backend,s=new Float32Array(v.sizeFromShape(t.shape)),r=n.data.get(t.dataId),a=r.complexTensorInfos.real,o=r.complexTensorInfos.imag,i=n.data.get(a.dataId).values,l=n.data.get(o.dataId).values;for(let u=0;u<i.length;u++){let c=i[u],p=l[u];s[u]=Math.hypot(c,p)}return n.makeOutput(s,t.shape,"float32")},VK={kernelName:Lp,backendName:"cpu",kernelFunc:WK};function oc(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.data.get(s.dataId).complexTensorInfos.imag,a=n.data.get(r.dataId).values;return n.makeTensorInfo(r.shape,r.dtype,a)}var UK={kernelName:Up,backendName:"cpu",kernelFunc:oc};function ic(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s,a=v.parseAxisParam(r,t[0].shape)[0],o=C.computeOutShape(t.map(m=>m.shape),a);if(v.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let i=t.filter(m=>v.sizeFromShape(m.shape)>0);if(i.length===1)return Kr({inputs:{x:i[0]},backend:n});let l=i.map(m=>m.shape);if(C.assertParamsConsistent(l,a),i[0].dtype==="complex64"){let m=i.map(b=>el({inputs:{input:b},backend:n})),g=i.map(b=>oc({inputs:{input:b},backend:n})),y=ic({inputs:m,backend:n,attrs:{axis:a}}),x=ic({inputs:g,backend:n,attrs:{axis:a}}),A=Cs({inputs:{real:y,imag:x},backend:n});return m.forEach(b=>n.disposeIntermediateTensorInfo(b)),g.forEach(b=>n.disposeIntermediateTensorInfo(b)),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(x),A}let u=i.map(m=>{let g=v.sizeFromShape(m.shape.slice(a));return Rt({inputs:{x:m},backend:n,attrs:{shape:[-1,g]}})}),c=u.map(m=>({vals:n.data.get(m.dataId).values,shape:m.shape}));o=C.computeOutShape(u.map(m=>m.shape),1);let p=u[0].shape[0]===1,d=Nx(c,o,t[0].dtype,p),h=C.computeOutShape(i.map(m=>m.shape),a),f=n.makeTensorInfo(h,t[0].dtype,d);return u.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var GK={kernelName:ll,backendName:"cpu",kernelFunc:ic};function tS(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=s;Ce([r,a],"conv2d");let p=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,a.shape,o,u,i,c,!1,p),h=d.filterHeight,f=d.filterWidth,m=d.dilationHeight,g=d.dilationWidth,y=d.padInfo.left,x=d.padInfo.top,A=d.dataFormat==="channelsLast",b=new fn(d.outShape,r.dtype),w=v.computeStrides(r.shape),k=v.computeStrides(a.shape),S=w[0],E=A?w[1]:w[2],R=A?w[2]:1,P=A?1:w[1],_=b.strides[0],$=A?b.strides[1]:b.strides[2],T=A?b.strides[2]:1,F=A?1:b.strides[1],G=n.data.get(r.dataId).values,q=n.data.get(a.dataId).values,z=b.values;for(let Z=0;Z<d.batchSize;++Z){let B=Z*S,ee=Z*_;for(let Q=0;Q<d.outHeight;++Q){let oe=ee+Q*$,Y=Q*d.strideHeight-x;for(let ae=0;ae<h;++ae){let le=Y+ae*m;if(le<0||le>=d.inHeight)continue;let ye=ae*k[0],we=B+le*E;for(let Re=0;Re<d.outWidth;++Re){let _e=oe+Re*T,Be=Re*d.strideWidth-y;for(let Ge=0;Ge<f;++Ge){let ot=Be+Ge*g;if(ot<0||ot>=d.inWidth)continue;let dt=ye+Ge*k[1],pt=we+ot*R,At=dt;for(let $e=0;$e<d.inChannels;++$e){let Tt=G[pt+$e*P];for(let It=0;It<d.outChannels;++It)z[_e+It*F]+=Tt*q[At+It];At+=d.outChannels}}}}}}return n.makeTensorInfo(b.shape,b.dtype,z)}var HK={kernelName:yo,backendName:"cpu",kernelFunc:tS};function jK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,filterShape:c}=s;Ce([r,a],"conv2dBackpropFilter");let p=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,c,o,1,i,u,!1,p),{strideHeight:h,strideWidth:f,filterHeight:m,filterWidth:g}=d,y=d.dataFormat==="channelsLast",x=new fn(d.filterShape,"float32"),A=d.padInfo.left,b=d.padInfo.top,w=n.data.get(r.dataId).values,k=n.data.get(a.dataId).values,S=new fn(r.shape,r.dtype,w),E=new fn(a.shape,a.dtype,k);for(let R=0;R<m;++R){let P=Math.max(0,Math.ceil((b-R)/h)),_=Math.min(d.outHeight,(d.inHeight+b-R)/h);for(let $=0;$<g;++$){let T=Math.max(0,Math.ceil((A-$)/f)),F=Math.min(d.outWidth,(d.inWidth+A-$)/f);for(let G=0;G<d.inChannels;++G)for(let q=0;q<d.outChannels;++q){let z=0;for(let Z=0;Z<d.batchSize;++Z)for(let B=P;B<_;++B){let ee=R+B*h-b;for(let Q=T;Q<F;++Q){let oe=$+Q*f-A;y?z+=S.get(Z,ee,oe,G)*E.get(Z,B,Q,q):z+=S.get(Z,G,ee,oe)*E.get(Z,q,B,Q)}}x.set(z,R,$,G,q)}}}return n.makeTensorInfo(x.shape,x.dtype,x.values)}var qK={kernelName:qm,backendName:"cpu",kernelFunc:jK};function XK(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{inputShape:o,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=s;Ce([r,a],"conv2dBackpropInput");let p=v.computeStrides(a.shape),d=v.computeStrides(r.shape),h=C.convertConv2DDataFormat(u),f=C.computeConv2DInfo(o,a.shape,i,1,l,c,!1,h),m=new fn(f.inShape,"float32"),g=m.values,y=n.data.get(r.dataId).values,x=n.data.get(a.dataId).values,[A,b,w]=p,{batchSize:k,filterHeight:S,filterWidth:E,inChannels:R,inHeight:P,inWidth:_,outChannels:$,outHeight:T,outWidth:F,strideHeight:G,strideWidth:q}=f;h=f.dataFormat;let z=S-1-f.padInfo.top,Z=E-1-f.padInfo.left,B=h==="channelsLast",ee=m.strides[0],Q=B?m.strides[1]:m.strides[2],oe=B?m.strides[2]:1,Y=B?1:m.strides[1],ae=d[0],le=B?d[1]:d[2],ye=B?d[2]:1,we=B?1:d[1];for(let Re=0;Re<k;++Re)for(let _e=0;_e<R;++_e)for(let Be=0;Be<P;++Be){let Ge=Be-z,ot=Math.max(0,Math.ceil(Ge/G)),dt=Math.min(T,(S+Ge)/G);for(let pt=0;pt<_;++pt){let At=pt-Z,$e=Math.max(0,Math.ceil(At/q)),Tt=Math.min(F,(E+At)/q),It=0;for(let Qt=ot;Qt<dt;++Qt){let bs=Qt*G-Ge;for(let pn=$e;pn<Tt;++pn){let Gn=pn*q-At,vs=ae*Re+le*Qt+ye*pn,ws=A*(S-1-bs)+b*(E-1-Gn)+w*_e;for(let $n=0;$n<$;++$n){let Vs=y[vs+we*$n],Hn=x[ws+$n];It+=Vs*Hn}}}let Un=ee*Re+Q*Be+oe*pt+Y*_e;g[Un]=It}}return n.makeTensorInfo(m.shape,m.dtype,m.values)}var KK={kernelName:Ao,backendName:"cpu",kernelFunc:XK};function ZK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l}=s;Ce([r,a],"conv3d");let u=C.computeConv3DInfo(r.shape,a.shape,o,l,i),{filterDepth:c,filterHeight:p,filterWidth:d,dilationDepth:h,dilationHeight:f,dilationWidth:m,padInfo:g}=u,y=g.front,x=g.left,A=g.top,b=new fn(u.outShape,r.dtype),w=n.data.get(r.dataId).values,k=n.data.get(a.dataId).values,S=b.values,E=v.computeStrides(r.shape),R=v.computeStrides(a.shape);for(let P=0;P<u.batchSize;++P){let 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u=v.computeStrides(r.shape),c=v.computeStrides(a.shape),p=C.computeConv3DInfo(r.shape,l,o,1,i),d=p.strideDepth,h=p.strideHeight,f=p.strideWidth,m=p.filterDepth,g=p.filterHeight,y=p.filterWidth,x=new fn(p.filterShape,"float32"),A=x.values,[b,w,k,S]=x.strides,E=n.data.get(a.dataId).values,[R,P,_,$]=c,T=n.data.get(r.dataId).values,[F,G,q,z]=u,Z=p.padInfo.front,B=p.padInfo.left,ee=p.padInfo.top;for(let Q=0;Q<m;++Q){let oe=Math.max(0,Math.ceil((Z-Q)/d)),Y=Math.min(p.outDepth,(p.inDepth+Z-Q)/d),ae=Q*b;for(let le=0;le<g;++le){let ye=Math.max(0,Math.ceil((ee-le)/h)),we=Math.min(p.outHeight,(p.inHeight+ee-le)/h),Re=le*w+ae;for(let _e=0;_e<y;++_e){let Be=Math.max(0,Math.ceil((B-_e)/f)),Ge=Math.min(p.outWidth,(p.inWidth+B-_e)/f),ot=_e*k+Re;for(let dt=0;dt<p.inChannels;++dt){let pt=dt*S+ot;for(let At=0;At<p.outChannels;++At){let $e=0;for(let Tt=0;Tt<p.batchSize;++Tt){let It=Tt*F,Un=Tt*R;for(let Qt=oe;Qt<Y;++Qt){let pn=(Q+Qt*d-Z)*G+It,Gn=Qt*P+Un;for(let vs=ye;vs<we;++vs){let 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dt=ot-we,pt=Math.max(0,Math.ceil(dt/ae)),At=Math.min(Q,(T+dt)/ae);for(let $e=0;$e<Z;++$e){let Tt=$e-Re,It=Math.max(0,Math.ceil(Tt/le)),Un=Math.min(oe,(F+Tt)/le);for(let Qt=0;Qt<B;++Qt){let bs=Qt-_e,pn=Math.max(0,Math.ceil(bs/ye)),Gn=Math.min(Y,(G+bs)/ye),vs=0;for(let ws=pt;ws<At;++ws){let $n=ws*ae-dt;for(let Vs=It;Vs<Un;++Vs){let Hn=Vs*le-Tt;for(let sa=pn;sa<Gn;++sa){let ra=sa*ye-bs,Au=A*Be+b*ws+w*Vs+k*sa,Fa=E*(T-1-$n)+R*(F-1-Hn)+P*(G-1-ra)+_*Ge;for(let aa=0;aa<ee;++aa){let Od=x[Au+aa],xu=S[Fa+aa];vs+=Od*xu}}}}h[f*Be+m*ot+g*$e+y*Qt+Ge]=vs}}}return n.makeTensorInfo(d.shape,d.dtype,d.values)}var tZ={kernelName:Km,backendName:"cpu",kernelFunc:eZ},nZ=bt(xo,e=>Math.cos(e)),sZ={kernelName:xo,backendName:"cpu",kernelFunc:nZ},rZ=bt(bo,e=>Math.cosh(e)),aZ={kernelName:bo,backendName:"cpu",kernelFunc:rZ};function oZ(e){let{inputs:t,backend:n,attrs:s}=e,{image:r,boxes:a,boxInd:o}=t,{cropSize:i,method:l,extrapolationValue:u}=s,[c,p,d,h]=r.shape,f=a.shape[0],[m,g]=i,y=Le([f,m,g,h],"float32"),x=n.data.get(a.dataId).values,A=n.data.get(o.dataId).values,b=n.data.get(r.dataId).values,w=v.computeStrides(r.shape),k=v.computeStrides(y.shape);for(let S=0;S<f;S++){let E=S*4,R=x[E],P=x[E+1],_=x[E+2],$=x[E+3],T=A[S];if(T>=c)continue;let F=m>1?(_-R)*(p-1)/(m-1):0,G=g>1?($-P)*(d-1)/(g-1):0;for(let q=0;q<m;q++){let z=m>1?R*(p-1)+q*F:.5*(R+_)*(p-1);if(z<0||z>p-1){for(let Z=0;Z<g;Z++)for(let B=0;B<h;B++){let ee=B+Z*k[2]+q*k[1]+S*k[0];y.values[ee]=u}continue}if(l==="bilinear"){let Z=Math.floor(z),B=Math.ceil(z),ee=z-Z;for(let Q=0;Q<g;Q++){let oe=g>1?P*(d-1)+Q*G:.5*(P+$)*(d-1);if(oe<0||oe>d-1){for(let ye=0;ye<h;ye++){let we=ye+Q*k[2]+q*k[1]+S*k[0];y.values[we]=u}continue}let Y=Math.floor(oe),ae=Math.ceil(oe),le=oe-Y;for(let ye=0;ye<h;ye++){let we=ye+Y*w[2]+Z*w[1]+T*w[0],Re=b[we];we=ye+ae*w[2]+Z*w[1]+T*w[0];let 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p=On(u.dtype,"int32"),d=v.makeOnesTypedArray(v.sizeFromShape(u.shape),p),h=n.data.get(u.dataId).values,f=u.shape[u.shape.length-1],m=i?(y,x)=>y+f-x-1:(y,x)=>y+x;for(let y=0;y<h.length;y+=f)for(let x=0;x<f;x++){let A=m(y,x);if(x===0)d[A]=o?1:h[A];else{let b=m(y,x-1);d[A]=o?h[b]*d[b]:h[A]*d[b]}}let g=n.makeTensorInfo(u.shape,p,d);if(l!=null){let y=C.getUndoAxesPermutation(l),x=gs({inputs:{x:g},backend:n,attrs:{perm:y}});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(u),x}return g}var uZ={kernelName:ul,backendName:"cpu",kernelFunc:lZ};function cZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;Ce(r,"cumsum");let l=C.getAxesPermutation([a],r.shape.length),u=r;l!=null&&(u=gs({inputs:{x:r},backend:n,attrs:{perm:l}}));let c=C.getInnerMostAxes(1,r.shape.length)[0];if(c!==u.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${c}`);let p=On(u.dtype,"int32"),d=v.makeZerosTypedArray(v.sizeFromShape(u.shape),p),h=n.data.get(u.dataId).values,f=u.shape[u.shape.length-1],m=i?(y,x)=>y+f-x-1:(y,x)=>y+x;for(let y=0;y<h.length;y+=f)for(let x=0;x<f;x++){let A=m(y,x);if(x===0)d[A]=o?0:h[A];else{let b=m(y,x-1);d[A]=o?h[b]+d[b]:h[A]+d[b]}}let g=n.makeTensorInfo(u.shape,p,d);if(l!=null){let y=C.getUndoAxesPermutation(l),x=gs({inputs:{x:g},backend:n,attrs:{perm:y}});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(u),x}return g}var dZ={kernelName:vo,backendName:"cpu",kernelFunc:cZ};function pZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o,binaryOutput:i}=s;if(r.shape.length===1){let l=n.data.get(r.dataId).values,u=n.data.get(a.dataId).values,c=Tx(l,u,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,c)}else if(r.shape.length===2){let l=n.bufferSync(r),u=n.bufferSync(a),c=fI(l,u,o,i);return n.makeTensorInfo(c.shape,a.dtype,c.values)}throw new Error(`Error in denseBincount: input must be 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AZ={kernelName:Ym,backendName:"cpu",kernelFunc:yZ};function xZ(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=s;Ce([r,a],"depthwiseConv2DNativeBackpropInput");let p=v.computeStrides(r.shape),d=v.computeStrides(a.shape),h=C.computeConv2DInfo(c,a.shape,o,i,l,u,!0),f=new fn(h.inShape,"float32"),m=f.values,[g,y,x]=f.strides,A=n.data.get(r.dataId).values,[b,w,k]=p,S=n.data.get(a.dataId).values,[E,R,P]=d,{batchSize:_,filterHeight:$,filterWidth:T,inChannels:F,inHeight:G,inWidth:q,outChannels:z,outHeight:Z,outWidth:B,strideHeight:ee,strideWidth:Q}=h,oe=$-1-h.padInfo.top,Y=T-1-h.padInfo.left,ae=z/F;for(let le=0;le<_;++le)for(let ye=0;ye<F;++ye)for(let we=0;we<G;++we){let Re=we-oe,_e=Math.max(0,Math.ceil(Re/ee)),Be=Math.min(Z,($+Re)/ee);for(let Ge=0;Ge<q;++Ge){let ot=Ge-Y,dt=Math.max(0,Math.ceil(ot/Q)),pt=Math.min(B,(T+ot)/Q),At=0;for(let $e=_e;$e<Be;++$e){let Tt=$e*ee-Re;for(let It=dt;It<pt;++It){let 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P=v.toNestedArray(R,u.data.get(a.dataId).values),_=v.makeZerosNestedTypedArray(s.shape,s.dtype);for(let T=0;T<d;++T)for(let F=0;F<g;++F){let G=F*A-x.top;for(let q=0;q<y;++q){let z=q*b-x.left;for(let Z=0;Z<m;++Z){let B=Number.MIN_SAFE_INTEGER,ee=G<0?0:G,Q=z<0?0:z;for(let oe=0;oe<w;++oe){let Y=G+oe*S;if(Y>=0&&Y<h)for(let ae=0;ae<k;++ae){let le=z+ae*E;if(le>=0&&le<f){let ye=c[T][Y][le][Z]+p[oe][ae][Z];ye>B&&(B=ye,ee=Y,Q=le)}}}_[T][ee][Q][Z]+=P[T][F][q][Z]}}}return{dataId:u.write(v.toTypedArray(_,s.dtype),s.shape,s.dtype),shape:s.shape,dtype:s.dtype}}};function $h(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;Ce(r,"sum");let i;r.dtype==="bool"?i=oo({inputs:{x:r},backend:n,attrs:{dtype:"int32"}}):i=Kr({inputs:{x:r},backend:n});let 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TZ(e){let{inputs:t,backend:n,attrs:s}=e,{equation:r}=s,a=t,{allDims:o,summedDims:i,idDims:l}=C.decodeEinsumEquation(r,a.length);C.checkEinsumDimSizes(o.length,l,a);let{path:u,steps:c}=C.getEinsumComputePath(i,l),p=c.length,d=null,h=o.length,f=[];for(let m=0;m<p;++m){for(let g of c[m]){let{permutationIndices:y,expandDims:x}=C.getEinsumPermutation(h,l[g]),A;C.isIdentityPermutation(y)?A=a[g]:(A=gs({inputs:{x:a[g]},backend:n,attrs:{perm:y}}),f.push(A));let b=A.shape.slice();for(let w=0;w<x.length;++w)b.splice(x[w],0,1);v.arraysEqual(A.shape,b)||(A=Rt({inputs:{x:A},backend:n,attrs:{shape:b}}),f.push(A)),d===null?d=A:(d=y2({inputs:{a:A,b:d},backend:n}),f.push(d))}m<p-1&&(u[m]>=0&&(d=$h({inputs:{x:d},backend:n,attrs:{axis:u[m]-(o.length-h),keepDims:!1}}),f.push(d)),h--)}for(let m of f)m!==d&&n.disposeIntermediateTensorInfo(m);return d}var NZ={kernelName:Vp,backendName:"cpu",kernelFunc:TZ};function EZ(e){let{inputs:t,backend:n}=e,{dy:s,y:r}=t;Ce([s,r],"eluGrad");let a=new 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s=e.shape,r=s[0],a=s[1],o=n.data.get(e.dataId),i=o.complexTensorInfos.real,l=o.complexTensorInfos.imag,u=[r,a],c=v.sizeFromShape(u),p=v.getTypedArrayFromDType("float32",c),d=v.getTypedArrayFromDType("float32",c);for(let g=0;g<r;g++){let y=tl({inputs:{x:i},backend:n,attrs:{begin:[g,0],size:[1,a]}}),x=tl({inputs:{x:l},backend:n,attrs:{begin:[g,0],size:[1,a]}}),A=Cs({inputs:{real:y,imag:x},backend:n}),{real:b,imag:w}=WZ(A,t,n),k=C.mergeRealAndImagArrays(b,w);for(let S=0;S<a;S++){let E=C.getComplexWithIndex(k,S);p[g*a+S]=E.real,d[g*a+S]=E.imag}n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(x),n.disposeIntermediateTensorInfo(A)}let h=n.makeTensorInfo(u,"float32",p),f=n.makeTensorInfo(u,"float32",d),m=Cs({inputs:{real:h,imag:f},backend:n});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),m}function WZ(e,t,n){let 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e.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:return"FRAMEBUFFER_INCOMPLETE_DIMENSIONS";case e.FRAMEBUFFER_UNSUPPORTED:return"FRAMEBUFFER_UNSUPPORTED";default:return`unknown error ${t}`}}function ka(e,t,n){let s=Ie(e,()=>t());if(s==null)throw new Error(n);return s}function CS(e,t){let n=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,s=t+e.TEXTURE0;if(s<e.TEXTURE0||s>n){let r=`[gl.TEXTURE0, gl.TEXTURE${n}]`;throw new Error(`textureUnit must be in ${r}.`)}}function nl(e,t=2){return v.sizeFromShape(e.slice(0,e.length-t))}function sl(e){if(e.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[e.length>1?e[e.length-2]:1,e[e.length-1]]}function sm(e){let t=[1,1,1];return e.length===0||e.length===1&&e[0]===1||(t=[nl(e),...sl(e)]),t}function TS(e,t=!1){let n=X().getNumber("WEBGL_MAX_TEXTURE_SIZE");t&&(n=n*2,e=e.map((r,a)=>a>=e.length-2?v.nearestLargerEven(e[a]):e[a]),e.length===1&&(e=[2,e[0]])),e.length!==2&&(e=v.squeezeShape(e).newShape);let s=v.sizeFromShape(e);if(e.length<=1&&s<=n)return[1,s];if(e.length===2&&e[0]<=n&&e[1]<=n)return e;if(e.length===3&&e[0]*e[1]<=n&&e[2]<=n)return[e[0]*e[1],e[2]];if(e.length===3&&e[0]<=n&&e[1]*e[2]<=n)return[e[0],e[1]*e[2]];if(e.length===4&&e[0]*e[1]*e[2]<=n&&e[3]<=n)return[e[0]*e[1]*e[2],e[3]];if(e.length===4&&e[0]<=n&&e[1]*e[2]*e[3]<=n)return[e[0],e[1]*e[2]*e[3]];if(t){let r=nl(e),a=2,o=2;return e.length&&([a,o]=sl(e)),s=r*(a/2)*(o/2),v.sizeToSquarishShape(s).map(i=>i*2)}return v.sizeToSquarishShape(s)}function Xf(e){return e%2===0}function _p(e,t){if(e=e.slice(-2),t=t.slice(-2),v.arraysEqual(e,t)||!e.length||!t.length||e[0]===0||e[1]===0||t[0]===0||t[1]===0)return!0;if(e.length!==t.length){let n=e.slice(-1)[0],s=t.slice(-1)[0];if(n===s||Xf(n)&&Xf(s)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&Xf(e[0])&&Xf(t[0])}var rm,am;function NS(e){if(rm==null){let t=Dr(e);rm=t.getParameter(t.MAX_TEXTURE_SIZE)}return rm}function lee(){rm=null}function uee(){am=null}function ES(e){if(am==null){let t=Dr(e);am=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,am)}function RS(e){if(e===0)return 0;let t,n=Dr(e);return Xs(n,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:Xs(n,"EXT_disjoint_timer_query")?t=1:t=0,t}function Xs(e,t){return e.getExtension(t)!=null}function sy(e){try{if(Dr(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function _S(e){if(e===0)return!1;let t=Dr(e);if(e===1){if(!Xs(t,"OES_texture_float"))return!1}else if(!Xs(t,"EXT_color_buffer_float"))return!1;return ry(t)}function DS(e){if(e===0)return!1;let t=Dr(e);if(e===1){if(!Xs(t,"OES_texture_float")||!Xs(t,"WEBGL_color_buffer_float"))return!1}else{if(Xs(t,"EXT_color_buffer_float"))return ry(t);let s="EXT_color_buffer_half_float";if(Xs(t,s)){let r=t.getExtension(s);return cee(t,r)}return!1}return ry(t)}function ry(e){let t=Bx(e),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n);let s=1,r=1;e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,s,r,0,t.textureFormatFloat,t.textureTypeFloat,null);let a=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,a),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let o=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(a),o}function cee(e,t){let n=Bx(e,t),s=e.createTexture();e.bindTexture(e.TEXTURE_2D,s);let r=1,a=1;e.texImage2D(e.TEXTURE_2D,0,n.internalFormatHalfFloat,r,a,0,n.textureFormatFloat,n.textureTypeHalfFloat,null);let o=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,o),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,s,0);let i=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(s),e.deleteFramebuffer(o),i}function $S(e){return e!==2?!1:Dr(e).fenceSync!=null}function td(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&v.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGL backend.`)})}var Pe=X();Pe.registerFlag("HAS_WEBGL",()=>Pe.getNumber("WEBGL_VERSION")>0);Pe.registerFlag("WEBGL_VERSION",()=>sy(2)?2:sy(1)?1:0);Pe.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);Pe.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>Pe.get("WEBGL_VERSION")===2);Pe.registerFlag("WEBGL_CPU_FORWARD",()=>!0);Pe.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);Pe.registerFlag("WEBGL_PACK",()=>Pe.getBool("HAS_WEBGL"));Pe.registerFlag("WEBGL_PACK_NORMALIZATION",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_CLIP",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_REDUCE",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_LAZILY_UNPACK",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_CONV_IM2COL",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>NS(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>ES(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let 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Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${e}.`)});Pe.registerFlag("CPU_HANDOFF_SIZE_THRESHOLD",()=>128);Pe.registerFlag("WEBGL_USE_SHAPES_UNIFORMS",()=>!1);Pe.registerFlag("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e5);Pe.registerFlag("TOPK_K_CPU_HANDOFF_THRESHOLD",()=>128);function as(){let e,t,n,s,r,a,o,i,l,u;return X().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",n="out",s="in",r="texture",a="outputColor",o="out vec4 outputColor;",i=`
      bool isnan_custom(float val) {
        uint floatToUint = floatBitsToUint(val);
        return (floatToUint & 0x7fffffffu) > 0x7f800000u;
      }

      bvec4 isnan_custom(vec4 val) {
        return bvec4(isnan_custom(val.x),
          isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));
      }

      #define isnan(value) isnan_custom(value)
    `,l="",u=`
      #define round(value) newRound(value)
      int newRound(float value) {
        return int(floor(value + 0.5));
      }

      ivec4 newRound(vec4 value) {
        return ivec4(floor(value + vec4(0.5)));
      }
    `):(e="",t="attribute",n="varying",s="varying",r="texture2D",a="gl_FragColor",o="",i=`
      #define isnan(value) isnan_custom(value)
      bool isnan_custom(float val) {
        return (val > 0. || val < 1. || val == 0.) ? false : true;
      }
      bvec4 isnan_custom(vec4 val) {
        return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));
      }
    `,l=`
      uniform float INFINITY;

      bool isinf(float val) {
        return abs(val) == INFINITY;
      }
      bvec4 isinf(vec4 val) {
        return equal(abs(val), vec4(INFINITY));
      }
    `,u=`
      int round(float value) {
        return int(floor(value + 0.5));
      }

      ivec4 round(vec4 value) {
        return ivec4(floor(value + vec4(0.5)));
      }
    `),{version:e,attribute:t,varyingVs:n,varyingFs:s,texture2D:r,output:a,defineOutput:o,defineSpecialNaN:i,defineSpecialInf:l,defineRound:u}}function nu(e,t,n="index"){let s=v.computeStrides(t);return s.map((r,a)=>{let o=`int ${e[a]} = ${n} / ${r}`,i=a===s.length-1?`int ${e[a+1]} = ${n} - ${e[a]} * ${r}`:`index -= ${e[a]} * ${r}`;return`${o}; ${i};`}).join("")}function x2(e,t,n="index"){let s=v.computeStrides(t);return s.map((r,a)=>{let o=`int ${e[a]} = ${n} / outShapeStrides[${a}]`,i=a===s.length-1?`int ${e[a+1]} = ${n} - ${e[a]} * outShapeStrides[${a}]`:`index -= ${e[a]} * outShapeStrides[${a}]`;return`${o}; ${i};`}).join("")}function dee(e,t){let n=e.length,s=e.map(a=>`${t}[${a}]`),r=new Array(n-1);r[n-2]=s[n-1];for(let a=n-3;a>=0;--a)r[a]=`(${r[a+1]} * ${s[a+1]})`;return r}function pee(e,t,n="index"){let s=e.map((a,o)=>o),r=dee(s,t);return r.map((a,o)=>{let i=`int ${e[o]} = ${n} / ${r[o]}`,l=o===r.length-1?`int ${e[o+1]} = ${n} - ${e[o]} * ${r[o]}`:`index -= ${e[o]} * ${r[o]}`;return`${i}; ${l};`}).join("")}function Vx(e){let t=v.computeStrides(e).map(n=>n.toString());return`
  int getFlatIndex(ivec3 coords) {
    return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
  }
`}function Ux(){return`
  int getFlatIndex(ivec3 coords) {
    return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
  }
`}var PS=`
  const float FLOAT_MAX = 1.70141184e38;
  const float FLOAT_MIN = 1.17549435e-38;

  lowp vec4 encode_float(highp float v) {
    if (isnan(v)) {
      return vec4(255, 255, 255, 255);
    }

    highp float av = abs(v);

    if(av < FLOAT_MIN) {
      return vec4(0.0, 0.0, 0.0, 0.0);
    } else if(v > FLOAT_MAX) {
      return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;
    } else if(v < -FLOAT_MAX) {
      return vec4(0.0, 0.0,  128.0, 255.0) / 255.0;
    }

    highp vec4 c = vec4(0,0,0,0);

    highp float e = floor(log2(av));
    highp float m = exp2(fract(log2(av))) - 1.0;

    c[2] = floor(128.0 * m);
    m -= c[2] / 128.0;
    c[1] = floor(32768.0 * m);
    m -= c[1] / 32768.0;
    c[0] = floor(8388608.0 * m);

    highp float ebias = e + 127.0;
    c[3] = floor(ebias / 2.0);
    ebias -= c[3] * 2.0;
    c[2] += floor(ebias) * 128.0;

    c[3] += 128.0 * step(0.0, -v);

    return c / 255.0;
  }
`,{getBroadcastDims:FS}=C;function hee(e,t,n){let s=[];if(e.forEach(h=>{let f=v.sizeFromShape(h.shapeInfo.logicalShape);if(h.shapeInfo.isUniform?s.push(`uniform float ${h.name}${f>1?`[${f}]`:""};`):(s.push(`uniform sampler2D ${h.name};`),s.push(`uniform int offset${h.name};`)),n.enableShapeUniforms){let{uniformShape:m}=Gx(n.packedInputs,h.shapeInfo.logicalShape,h.shapeInfo.texShape);switch(m.length){case 1:s.push(`uniform int ${h.name}Shape;`);break;case 2:s.push(`uniform ivec2 ${h.name}Shape;`);break;case 3:s.push(`uniform ivec3 ${h.name}Shape;`);break;case 4:s.push(`uniform ivec4 ${h.name}Shape;`);break;default:break}s.push(`uniform ivec2 ${h.name}TexShape;`)}}),n.enableShapeUniforms){switch(t.logicalShape.length){case 1:s.push("uniform int outShape;");break;case 2:s.push("uniform ivec2 outShape;"),s.push("uniform int outShapeStrides;");break;case 3:s.push("uniform ivec3 outShape;"),s.push("uniform ivec2 outShapeStrides;");break;case 4:s.push("uniform ivec4 outShape;"),s.push("uniform ivec3 outShapeStrides;");break;default:break}s.push("uniform ivec2 outTexShape;")}n.customUniforms&&n.customUniforms.forEach(h=>{s.push(`uniform ${h.type} ${h.name}${h.arrayIndex?`[${h.arrayIndex}]`:""};`)});let r=s.join(`
`),a=e.map(h=>fee(h,t,n.packedInputs,n.enableShapeUniforms)).join(`
`),o=t.texShape,i=as(),l=yee(i),u,c,p=bee(i);return t.isPacked?(u=mee(t.logicalShape,o,n.enableShapeUniforms),c=xee(i)):(u=gee(t.logicalShape,o,n.enableShapeUniforms),c=Aee(i)),n.packedInputs&&(p+=Iee),[p,l,c,r,u,a,n.userCode].join(`
`)}function nd(e,t=!1){let n=e.shapeInfo.logicalShape;switch(n.length){case 0:return Oee(e,t);case 1:return zee(e,t);case 2:return Bee(e,t);case 3:return Vee(e,t);case 4:return Gee(e,t);case 5:return Hee(e);case 6:return jee(e);default:throw new Error(`${n.length}-D input sampling is not yet supported`)}}function OS(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return Fee(e);case 1:return Mee(e,t);case 2:return Lee(e,t);case 3:return Wee(e,t);default:return Uee(e,t)}}function fee(e,t,n=!1,s){let r="";n?r+=OS(e,s):r+=nd(e,s);let a=e.shapeInfo.logicalShape,o=t.logicalShape;return a.length<=o.length&&(n?r+=qee(e,t):r+=Xee(e,t)),r}function mee(e,t,n){switch(e.length){case 0:return MS();case 1:return See(e,t,n);case 2:return $ee(e,t,n);case 3:return Tee(e,t,n);default:return Eee(e,t,n)}}function gee(e,t,n){switch(e.length){case 0:return MS();case 1:return Cee(e,t,n);case 2:return Pee(e,t,n);case 3:return Nee(e,t,n);case 4:return Ree(e,t,n);case 5:return _ee(e,t);case 6:return Dee(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function yee(e){return`
    float sampleTexture(sampler2D textureSampler, vec2 uv) {
      return ${e.texture2D}(textureSampler, uv).r;
    }
  `}function Aee(e){return`
    void setOutput(float val) {
      ${e.output} = vec4(val, 0, 0, 0);
    }
  `}function xee(e){return`
    void setOutput(vec4 val) {
      ${e.output} = val;
    }
  `}function bee(e){return`${e.version}
    precision highp float;
    precision highp int;
    precision highp sampler2D;
    ${e.varyingFs} vec2 resultUV;
    ${e.defineOutput}
    const vec2 halfCR = vec2(0.5, 0.5);

    struct ivec5
    {
      int x;
      int y;
      int z;
      int w;
      int u;
    };

    struct ivec6
    {
      int x;
      int y;
      int z;
      int w;
      int u;
      int v;
    };

    uniform float NAN;
    ${e.defineSpecialNaN}
    ${e.defineSpecialInf}
    ${e.defineRound}

    int imod(int x, int y) {
      return x - y * (x / y);
    }

    int idiv(int a, int b, float sign) {
      int res = a / b;
      int mod = imod(a, b);
      if (sign < 0. && mod != 0) {
        res -= 1;
      }
      return res;
    }

    //Based on the work of Dave Hoskins
    //https://www.shadertoy.com/view/4djSRW
    #define HASHSCALE1 443.8975
    float random(float seed){
      vec2 p = resultUV * seed;
      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);
      p3 += dot(p3, p3.yzx + 19.19);
      return fract((p3.x + p3.y) * p3.z);
    }

    ${vee}
    ${wee}
    ${kee}
  `}var vee=`
vec2 uvFromFlat(int texNumR, int texNumC, int index) {
  int texR = index / texNumC;
  int texC = index - texR * texNumC;
  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
}
vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
  int texelIndex = index / 2;
  int texR = texelIndex / texNumC;
  int texC = texelIndex - texR * texNumC;
  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
}
`,wee=`
vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
  int texNumC, int row, int col) {
  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
  int texR = texelIndex / texNumC;
  int texC = texelIndex - texR * texNumC;
  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
}
`,kee=`
vec2 packedUVfrom3D(int texNumR, int texNumC,
    int texelsInBatch, int texelsInLogicalRow, int b,
    int row, int col) {
  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);
  int texR = index / texNumC;
  int texC = index - texR * texNumC;
  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
}
`,Iee=`
  float getChannel(vec4 frag, vec2 innerDims) {
    vec2 modCoord = mod(innerDims, 2.);
    return modCoord.x == 0. ?
      (modCoord.y == 0. ? frag.r : frag.g) :
      (modCoord.y == 0. ? frag.b : frag.a);
  }
  float getChannel(vec4 frag, int dim) {
    float modCoord = mod(float(dim), 2.);
    return modCoord == 0. ? frag.r : frag.g;
  }
`;function MS(){return`
    int getOutputCoords() {
      return 0;
    }
  `}function See(e,t,n){let s=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return s[0]===1?n?`
      int getOutputCoords() {
        return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));
      }
    `:`
      int getOutputCoords() {
        return 2 * int(resultUV.x * ${s[1]}.0);
      }
    `:s[1]===1?n?`
      int getOutputCoords() {
        return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));
      }
    `:`
      int getOutputCoords() {
        return 2 * int(resultUV.y * ${s[0]}.0);
      }
    `:n?`
    int getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));
      return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);
    }
  `:`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${s[0]}, ${s[1]}));
      return 2 * (resTexRC.x * ${s[1]} + resTexRC.y);
    }
  `}function Cee(e,t,n){return t[0]===1?n?`
      int getOutputCoords() {
        return int(resultUV.x * float(outTexShape[1]));
      }
    `:`
      int getOutputCoords() {
        return int(resultUV.x * ${t[1]}.0);
      }
    `:t[1]===1?n?`
      int getOutputCoords() {
        return int(resultUV.y * float(outTexShape[0]));
      }
    `:`
      int getOutputCoords() {
        return int(resultUV.y * ${t[0]}.0);
      }
    `:n?`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(outTexShape[0], outTexShape[1]));
      return resTexRC.x * outTexShape[1] + resTexRC.y;
    }
  `:`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      return resTexRC.x * ${t[1]} + resTexRC.y;
    }
  `}function Tee(e,t,n){if(n)return`
    ivec3 getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));
      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));
      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;

      int b = index / texelsInBatch;
      index -= b * texelsInBatch;

      int r = 2 * (index / texelsInLogicalRow);
      int c = imod(index, texelsInLogicalRow) * 2;

      return ivec3(b, r, c);
    }
  `;let s=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),a=r*Math.ceil(e[1]/2);return`
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${s[0]}, ${s[1]}));
      int index = resTexRC.x * ${s[1]} + resTexRC.y;

      int b = index / ${a};
      index -= b * ${a};

      int r = 2 * (index / ${r});
      int c = imod(index, ${r}) * 2;

      return ivec3(b, r, c);
    }
  `}function Nee(e,t,n){if(n)return`
  ivec3 getOutputCoords() {
    ivec2 resTexRC = ivec2(resultUV.yx *
                           vec2(outTexShape[0], outTexShape[1]));
    int index = resTexRC.x * outTexShape[1] + resTexRC.y;
    ${x2(["r","c","d"],e)}
    return ivec3(r, c, d);
  }
`;let s=nu(["r","c","d"],e);return`
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      ${s}
      return ivec3(r, c, d);
    }
  `}function Eee(e,t,n){if(n)return`
    ivec4 getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));
      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;

      int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));
      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));
      int texelsInBatchN = texelsInBatch * outShape[1];

      int b2 = index / texelsInBatchN;
      index -= b2 * texelsInBatchN;

      int b = index / texelsInBatch;
      index -= b * texelsInBatch;

      int r = 2 * (index / texelsInLogicalRow);
      int c = imod(index, texelsInLogicalRow) * 2;

      return ivec4(b2, b, r, c);
    }
  `;let s=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),a=r*Math.ceil(e[e.length-2]/2),o=a,i="",l="b, r, c";for(let u=2;u<e.length-1;u++)o*=e[e.length-u-1],i=`
      int b${u} = index / ${o};
      index -= b${u} * ${o};
    `+i,l=`b${u}, `+l;return`
    ivec${e.length} getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${s[0]}, ${s[1]}));
      int index = resTexRC.x * ${s[1]} + resTexRC.y;

      ${i}

      int b = index / ${a};
      index -= b * ${a};

      int r = 2 * (index / ${r});
      int c = imod(index, ${r}) * 2;

      return ivec${e.length}(${l});
    }
  `}function Ree(e,t,n){if(n)return`
    ivec4 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(outTexShape[0], outTexShape[1]));
      int index = resTexRC.x * outTexShape[1] + resTexRC.y;
      ${x2(["r","c","d","d2"],e)}
      return ivec4(r, c, d, d2);
    }
  `;let s=nu(["r","c","d","d2"],e);return`
    ivec4 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      ${s}
      return ivec4(r, c, d, d2);
    }
  `}function _ee(e,t){let n=nu(["r","c","d","d2","d3"],e);return`
    ivec5 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
                             ${t[1]}));

      int index = resTexRC.x * ${t[1]} + resTexRC.y;

      ${n}

      ivec5 outShape = ivec5(r, c, d, d2, d3);
      return outShape;
    }
  `}function Dee(e,t){let n=nu(["r","c","d","d2","d3","d4"],e);return`
    ivec6 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;

      ${n}

      ivec6 result = ivec6(r, c, d, d2, d3, d4);
      return result;
    }
  `}function $ee(e,t,n){let s=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return n?`
      ivec2 getOutputCoords() {
        ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
        return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));
      }
    `:`
      ivec2 getOutputCoords() {
        return 2 * ivec2(resultUV.yx * vec2(${s[0]}, ${s[1]}));
      }
    `;let r=Math.ceil(e[1]/2);return n?`
    ivec2 getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));

      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
      int r = 2 * (index / texelsInLogicalRow);
      int c = imod(index, texelsInLogicalRow) * 2;

      return ivec2(r, c);
    }
  `:`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${s[0]}, ${s[1]}));

      int index = resTexRC.x * ${s[1]} + resTexRC.y;
      int r = 2 * (index / ${r});
      int c = imod(index, ${r}) * 2;

      return ivec2(r, c);
    }
  `}function Pee(e,t,n){return v.arraysEqual(e,t)?n?`
      ivec2 getOutputCoords() {
        return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
      }
    `:`
      ivec2 getOutputCoords() {
        return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
      }
    `:e[1]===1?n?`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(outTexShape[0], outTexShape[1]));
        int index = resTexRC.x * outTexShape[1] + resTexRC.y;
        return ivec2(index, 0);
      }
    `:`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(${t[0]}, ${t[1]}));
        int index = resTexRC.x * ${t[1]} + resTexRC.y;
        return ivec2(index, 0);
      }
    `:e[0]===1?n?`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(outTexShape[0], outTexShape[1]));
        int index = resTexRC.x * outTexShape[1] + resTexRC.y;
        return ivec2(0, index);
      }
    `:`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(${t[0]}, ${t[1]}));
        int index = resTexRC.x * ${t[1]} + resTexRC.y;
        return ivec2(0, index);
      }
    `:n?`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(outTexShape[0], outTexShape[1]));
      int index = resTexRC.x * outTexShape[1] + resTexRC.y;
      int r = index / outShape[1];
      int c = index - r * outShape[1];
      return ivec2(r, c);
    }
  `:`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      int r = index / ${e[1]};
      int c = index - r * ${e[1]};
      return ivec2(r, c);
    }
  `}function su(e){return`offset${e}`}function Fee(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),s=as();return`
    vec4 ${n}() {
      return ${s.texture2D}(${t}, halfCR);
    }
  `}function Oee(e,t){let n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return`float ${s}() {return ${n};}`;let[r,a]=e.shapeInfo.texShape;if(r===1&&a===1)return`
      float ${s}() {
        return sampleTexture(${n}, halfCR);
      }
    `;let o=su(n);if(t)return`
    float ${s}() {
      vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], ${o});
      return sampleTexture(${n}, uv);
    }
  `;let[i,l]=e.shapeInfo.texShape;return`
    float ${s}() {
      vec2 uv = uvFromFlat(${i}, ${l}, ${o});
      return sampleTexture(${n}, uv);
    }
  `}function Mee(e,t){let n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),r=e.shapeInfo.texShape,a=as();if(t)return`
    vec4 ${s}(int index) {
      ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
      vec2 uv = packedUVfrom1D(
        packedTexShape[0], packedTexShape[1], index);
      return ${a.texture2D}(${n}, uv);
    }
  `;let o=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)];return`
    vec4 ${s}(int index) {
      vec2 uv = packedUVfrom1D(
        ${o[0]}, ${o[1]}, index);
      return ${a.texture2D}(${n}, uv);
    }
  `}function zee(e,t){let n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return`
      float ${s}(int index) {
        ${sd(e)}
      }
    `;let r=e.shapeInfo.texShape,a=r[0],o=r[1];if(o===1&&a===1)return`
      float ${s}(int index) {
        return sampleTexture(${n}, halfCR);
      }
    `;let i=su(n);return o===1?t?`
      float ${s}(int index) {
        vec2 uv = vec2(0.5, (float(index + ${i}) + 0.5) / float(${n}TexShape[0]));
        return sampleTexture(${n}, uv);
      }
    `:`
      float ${s}(int index) {
        vec2 uv = vec2(0.5, (float(index + ${i}) + 0.5) / ${a}.0);
        return sampleTexture(${n}, uv);
      }
    `:a===1?t?`
      float ${s}(int index) {
        vec2 uv = vec2((float(index + ${i}) + 0.5) / float(${n}TexShape[1]), 0.5);
        return sampleTexture(${n}, uv);
      }
    `:`
      float ${s}(int index) {
        vec2 uv = vec2((float(index + ${i}) + 0.5) / ${o}.0, 0.5);
        return sampleTexture(${n}, uv);
      }
    `:t?`
    float ${s}(int index) {
      vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index + ${i});
      return sampleTexture(${n}, uv);
    }
  `:`
    float ${s}(int index) {
      vec2 uv = uvFromFlat(${a}, ${o}, index + ${i});
      return sampleTexture(${n}, uv);
    }
  `}function Lee(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=e.shapeInfo.texShape,o=a[0],i=a[1],l=as();if(a!=null&&v.arraysEqual(n,a))return t?`
      vec4 ${r}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${s}TexShape[1], ${s}TexShape[0]);

        return ${l.texture2D}(${s}, uv);
      }
    `:`
      vec4 ${r}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${i}.0, ${o}.0);

        return ${l.texture2D}(${s}, uv);
      }
    `;if(t)return`
    vec4 ${r}(int row, int col) {
      ivec2 packedTexShape = ivec2(ceil(float(${s}TexShape[0]) / 2.0), ceil(float(${s}TexShape[1]) / 2.0));
      int valuesPerRow = int(ceil(float(${s}Shape[1]) / 2.0));
      vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);
      return ${l.texture2D}(${s}, uv);
    }
  `;let u=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],c=Math.ceil(n[1]/2);return`
    vec4 ${r}(int row, int col) {
      vec2 uv = packedUVfrom2D(${c}, ${u[0]}, ${u[1]}, row, col);
      return ${l.texture2D}(${s}, uv);
    }
  `}function Bee(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=e.shapeInfo.texShape;if(a!=null&&v.arraysEqual(n,a)){if(t)return`
      float ${r}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${s}TexShape[1], ${s}TexShape[0]);
        return sampleTexture(${s}, uv);
      }
    `;let d=a[0],h=a[1];return`
    float ${r}(int row, int col) {
      vec2 uv = (vec2(col, row) + halfCR) / vec2(${h}.0, ${d}.0);
      return sampleTexture(${s}, uv);
    }
  `}let{newShape:o,keptDims:i}=v.squeezeShape(n),l=o;if(l.length<n.length){let d=rd(e,l),h=["row","col"];return`
      ${nd(d,t)}
      float ${r}(int row, int col) {
        return ${r}(${ad(h,i)});
      }
    `}if(e.shapeInfo.isUniform)return`
      float ${r}(int row, int col) {
        int index = round(dot(vec2(row, col), vec2(${n[1]}, 1)));
        ${sd(e)}
      }
    `;let u=a[0],c=a[1],p=su(s);return c===1?t?`
      float ${r}(int row, int col) {
        float index = dot(vec3(row, col, ${p}), vec3(${s}Shape[1], 1, 1));
        vec2 uv = vec2(0.5, (index + 0.5) / float(${s}TexShape[0]));
        return sampleTexture(${s}, uv);
      }
    `:`
    float ${r}(int row, int col) {
      float index = dot(vec3(row, col, ${p}), vec3(${n[1]}, 1, 1));
      vec2 uv = vec2(0.5, (index + 0.5) / ${u}.0);
      return sampleTexture(${s}, uv);
    }
  `:u===1?t?`
      float ${r}(int row, int col) {
        float index = dot(vec3(row, col, ${p}), vec3(${s}Shape[1], 1, 1));
        vec2 uv = vec2((index + 0.5) / float(${s}TexShape[1]), 0.5);
        return sampleTexture(${s}, uv);
      }
    `:`
    float ${r}(int row, int col) {
      float index = dot(vec3(row, col, ${p}), vec3(${n[1]}, 1, 1));
      vec2 uv = vec2((index + 0.5) / ${c}.0, 0.5);
      return sampleTexture(${s}, uv);
    }
  `:t?`
      float ${r}(int row, int col) {
        // Explicitly use integer operations as dot() only works on floats.
        int index = row * ${s}Shape[1] + col + ${p};
        vec2 uv = uvFromFlat(${s}TexShape[0], ${s}TexShape[1], index);
        return sampleTexture(${s}, uv);
      }
    `:`
  float ${r}(int row, int col) {
    // Explicitly use integer operations as dot() only works on floats.
    int index = row * ${n[1]} + col + ${p};
    vec2 uv = uvFromFlat(${u}, ${c}, index);
    return sampleTexture(${s}, uv);
  }
`}function Wee(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=e.shapeInfo.texShape,o=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(n[0]===1){let d=n.slice(1),h=[1,2],f=rd(e,d),m=["b","row","col"];return`
        ${OS(f,t)}
        vec4 ${r}(int b, int row, int col) {
          return ${r}(${ad(m,h)});
        }
      `}let i=as();if(t)return`
    vec4 ${r}(int b, int row, int col) {
      ivec2 packedTexShape = ivec2(ceil(float(${s}TexShape[0]) / 2.0), ceil(float(${s}TexShape[1]) / 2.0));
      int valuesPerRow = int(ceil(float(${s}Shape[2]) / 2.0));
      int texelsInBatch = valuesPerRow * int(ceil(float(${s}Shape[1]) / 2.0));
      vec2 uv = packedUVfrom3D(
        packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);
      return ${i.texture2D}(${s}, uv);
    }
  `;let l=o[0],u=o[1],c=Math.ceil(n[2]/2),p=c*Math.ceil(n[1]/2);return`
    vec4 ${r}(int b, int row, int col) {
      vec2 uv = packedUVfrom3D(
        ${l}, ${u}, ${p}, ${c}, b, row, col);
      return ${i.texture2D}(${s}, uv);
    }
  `}function Vee(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=n[1]*n[2],o=n[2],{newShape:i,keptDims:l}=v.squeezeShape(n),u=i;if(u.length<n.length){let m=rd(e,u),g=["row","col","depth"];return`
        ${nd(m,t)}
        float ${r}(int row, int col, int depth) {
          return ${r}(${ad(g,l)});
        }
      `}if(e.shapeInfo.isUniform)return`
      float ${r}(int row, int col, int depth) {
        int index = round(dot(vec3(row, col, depth),
                          vec3(${a}, ${o}, 1)));
        ${sd(e)}
      }
    `;let c=e.shapeInfo.texShape,p=c[0],d=c[1],h=e.shapeInfo.flatOffset;if(d===a&&h==null)return t?`
      float ${r}(int row, int col, int depth) {
        int stride1 = ${s}Shape[2];
        float texR = float(row);
        float texC = dot(vec2(col, depth), vec2(stride1, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${s}TexShape[1], ${s}TexShape[0]);
        return sampleTexture(${s}, uv);
      }
    `:`
        float ${r}(int row, int col, int depth) {
          float texR = float(row);
          float texC = dot(vec2(col, depth), vec2(${o}, 1));
          vec2 uv = (vec2(texC, texR) + halfCR) /
                     vec2(${d}.0, ${p}.0);
          return sampleTexture(${s}, uv);
        }
      `;if(d===o&&h==null)return t?`
      float ${r}(int row, int col, int depth) {
        float texR = dot(vec2(row, col), vec2(${s}Shape[1], 1));
        float texC = float(depth);
        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${s}TexShape[1], ${s}TexShape[0]);
        return sampleTexture(${s}, uv);
      }
    `:`
    float ${r}(int row, int col, int depth) {
      float texR = dot(vec2(row, col), vec2(${n[1]}, 1));
      float texC = float(depth);
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${d}.0, ${p}.0);
      return sampleTexture(${s}, uv);
    }
  `;let f=su(s);return t?`
    float ${r}(int row, int col, int depth) {
      // Explicitly use integer operations as dot() only works on floats.
      int stride0 = ${s}Shape[1] * ${s}Shape[2];
      int stride1 = ${s}Shape[2];
      int index = row * ${a} + col * ${o} + depth + ${f};
      vec2 uv = uvFromFlat(${s}TexShape[0], ${s}TexShape[1], index);
      return sampleTexture(${s}, uv);
    }
    `:`
      float ${r}(int row, int col, int depth) {
        // Explicitly use integer operations as dot() only works on floats.
        int index = row * ${a} + col * ${o} + depth + ${f};
        vec2 uv = uvFromFlat(${p}, ${d}, index);
        return sampleTexture(${s}, uv);
      }
  `}function Uee(e,t){let n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),r=as();if(t)return`
    vec4 ${s}(int b2, int b, int row, int col) {
      int valuesPerRow = int(ceil(float(${n}Shape[3]) / 2.0));
      int texelsInBatch = valuesPerRow * int(ceil(float(${n}Shape[2]) / 2.0));
      int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);
      texelsInBatch *= ${n}Shape[1];
      index = b2 * texelsInBatch + index;
      ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
      int texR = index / packedTexShape[1];
      int texC = index - texR * packedTexShape[1];
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(packedTexShape[1], packedTexShape[0]); return ${r.texture2D}(${n}, uv);
    }
  `;let a=e.shapeInfo.logicalShape,o=a.length,i=e.shapeInfo.texShape,l=[Math.ceil(i[0]/2),Math.ceil(i[1]/2)],u=l[0],c=l[1],p=Math.ceil(a[o-1]/2),d=p*Math.ceil(a[o-2]/2),h="int b, int row, int col",f=`b * ${d} + (row / 2) * ${p} + (col / 2)`;for(let m=2;m<o-1;m++)h=`int b${m}, `+h,d*=a[o-m-1],f=`b${m} * ${d} + `+f;return`
    vec4 ${s}(${h}) {
      int index = ${f};
      int texR = index / ${c};
      int texC = index - texR * ${c};
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${c}, ${u});
      return ${r.texture2D}(${n}, uv);
    }
  `}function Gee(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=n[3],o=n[2]*a,i=n[1]*o,{newShape:l,keptDims:u}=v.squeezeShape(n);if(l.length<n.length){let x=rd(e,l),A=["row","col","depth","depth2"];return`
      ${nd(x,t)}
      float ${r}(int row, int col, int depth, int depth2) {
        return ${r}(${ad(A,u)});
      }
    `}if(e.shapeInfo.isUniform)return`
      float ${r}(int row, int col, int depth, int depth2) {
        int index = round(dot(vec4(row, col, depth, depth2),
                          vec4(${i}, ${o}, ${a}, 1)));
        ${sd(e)}
      }
    `;let c=e.shapeInfo.flatOffset,p=e.shapeInfo.texShape,d=p[0],h=p[1],f=`int stride2 = ${s}Shape[3];`,m=`int stride1 = ${s}Shape[2] * stride2;`,g=`int stride0 = ${s}Shape[1] * stride1;`;if(h===i&&c==null)return t?`
      float ${r}(int row, int col, int depth, int depth2) {
        ${f}
        ${m}
        float texR = float(row);
        float texC =
            dot(vec3(col, depth, depth2),
                vec3(stride1, stride2, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${s}TexShape[1], ${s}TexShape[0]);
        return sampleTexture(${s}, uv);
      }
    `:`
      float ${r}(int row, int col, int depth, int depth2) {
        float texR = float(row);
        float texC =
            dot(vec3(col, depth, depth2),
                vec3(${o}, ${a}, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${h}.0, ${d}.0);
        return sampleTexture(${s}, uv);
      }
    `;if(h===a&&c==null)return t?`
      float ${r}(int row, int col, int depth, int depth2) {
        float texR = dot(vec3(row, col, depth),
                         vec3(${s}Shape[1] * ${s}Shape[2], ${s}Shape[2], 1));
        float texC = float(depth2);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${s}TexShape[1], ${s}TexShape[0]);
        return sampleTexture(${s}, uv);
      }
    `:`
      float ${r}(int row, int col, int depth, int depth2) {
        float texR = dot(vec3(row, col, depth),
                         vec3(${n[1]*n[2]}, ${n[2]}, 1));
        float texC = float(depth2);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${h}.0, ${d}.0);
        return sampleTexture(${s}, uv);
      }
    `;let y=su(s);return t?`
    float ${r}(int row, int col, int depth, int depth2) {
      // Explicitly use integer operations as dot() only works on floats.
      ${f}
      ${m}
      ${g}
      int index = row * stride0 + col * stride1 +
          depth * stride2 + depth2;
      vec2 uv = uvFromFlat(${s}TexShape[0], ${s}TexShape[1], index + ${y});
      return sampleTexture(${s}, uv);
    }
  `:`
    float ${r}(int row, int col, int depth, int depth2) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${i} + col * ${o} +
          depth * ${a} + depth2;
      vec2 uv = uvFromFlat(${d}, ${h}, index + ${y});
      return sampleTexture(${s}, uv);
    }
  `}function Hee(e){let t=e.shapeInfo.logicalShape,n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),r=t[4],a=t[3]*r,o=t[2]*a,i=t[1]*o,{newShape:l,keptDims:u}=v.squeezeShape(t);if(l.length<t.length){let m=rd(e,l),g=["row","col","depth","depth2","depth3"];return`
      ${nd(m)}
      float ${s}(int row, int col, int depth, int depth2, int depth3) {
        return ${s}(${ad(g,u)});
      }
    `}if(e.shapeInfo.isUniform)return`
      float ${s}(int row, int col, int depth, int depth2, int depth3) {
        float index = dot(
          vec4(row, col, depth, depth2),
          vec4(${i}, ${o}, ${a}, ${r})) +
          depth3;
        ${sd(e)}
      }
    `;let c=e.shapeInfo.flatOffset,p=e.shapeInfo.texShape,d=p[0],h=p[1];if(h===i&&c==null)return`
      float ${s}(int row, int col, int depth, int depth2, int depth3) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
                         vec4(${o}, ${a}, ${r}, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${h}.0, ${d}.0);
        return sampleTexture(${n}, uv);
      }
    `;if(h===r&&c==null)return`
      float ${s}(int row, int col, int depth, int depth2, int depth3) {
        float texR = dot(
          vec4(row, col, depth, depth2),
          vec4(${t[1]*t[2]*t[3]},
               ${t[2]*t[3]}, ${t[3]}, 1));
        int texC = depth3;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${h}.0, ${d}.0);
        return sampleTexture(${n}, uv);
      }
    `;let f=su(n);return`
    float ${s}(int row, int col, int depth, int depth2, int depth3) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${i} + col * ${o} + depth * ${a} +
          depth2 * ${r} + depth3 + ${f};
      vec2 uv = uvFromFlat(${d}, ${h}, index);
      return sampleTexture(${n}, uv);
    }
  `}function jee(e){let t=e.shapeInfo.logicalShape,n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:r,keptDims:a}=v.squeezeShape(t);if(r.length<t.length){let g=rd(e,r),y=["row","col","depth","depth2","depth3","depth4"];return`
      ${nd(g)}
      float ${s}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        return ${s}(${ad(y,a)});
      }
    `}let o=t[5],i=t[4]*o,l=t[3]*i,u=t[2]*l,c=t[1]*u;if(e.shapeInfo.isUniform)return`
      float ${s}(int row, int col, int depth,
                  int depth2, int depth3, int depth4) {
        int index = round(dot(
          vec4(row, col, depth, depth2),
          vec4(${c}, ${u}, ${l}, ${i})) +
          dot(
            vec2(depth3, depth4),
            vec2(${o}, 1)));
        ${sd(e)}
      }
    `;let p=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,h=d[0],f=d[1];if(f===c&&p==null)return`
      float ${s}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
          vec4(${u}, ${l}, ${i}, ${o})) +
               float(depth4);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${f}.0, ${h}.0);
        return sampleTexture(${n}, uv);
      }
    `;if(f===o&&p==null)return`
      float ${s}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        float texR = dot(vec4(row, col, depth, depth2),
          vec4(${t[1]*t[2]*t[3]*t[4]},
               ${t[2]*t[3]*t[4]},
               ${t[3]*t[4]},
               ${t[4]})) + float(depth3);
        int texC = depth4;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${f}.0, ${h}.0);
        return sampleTexture(${n}, uv);
      }
    `;let m=su(n);return`
    float ${s}(int row, int col, int depth,
                  int depth2, int depth3, int depth4) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${c} + col * ${u} + depth * ${l} +
          depth2 * ${i} + depth3 * ${o} + depth4 + ${m};
      vec2 uv = uvFromFlat(${h}, ${f}, index);
      return sampleTexture(${n}, uv);
    }
  `}function sd(e){let t=e.name,n=v.sizeFromShape(e.shapeInfo.logicalShape);return n<2?`return ${t};`:`
    for (int i = 0; i < ${n}; i++) {
      if (i == index) {
        return ${t}[i];
      }
    }
  `}function qee(e,t){let n=e.name,s=n.charAt(0).toUpperCase()+n.slice(1),r="get"+s+"AtOutCoords",a=e.shapeInfo.logicalShape.length,o=t.logicalShape.length,i=FS(e.shapeInfo.logicalShape,t.logicalShape),l=wt(o),u=o-a,c,p=["x","y","z","w","u","v"];a===0?c="":o<2&&i.length>=1?c="coords = 0;":c=i.map(x=>`coords.${p[x+u]} = 0;`).join(`
`);let d="";o<2&&a>0?d="coords":d=e.shapeInfo.logicalShape.map((x,A)=>`coords.${p[A+u]}`).join(", ");let h="return outputValue;",m=v.sizeFromShape(e.shapeInfo.logicalShape)===1,y=v.sizeFromShape(t.logicalShape)===1;if(a===1&&!m&&!y)h=`
      return vec4(outputValue.xy, outputValue.xy);
    `;else if(m&&!y)o===1?h=`
        return vec4(outputValue.x, outputValue.x, 0., 0.);
      `:h=`
        return vec4(outputValue.x);
      `;else if(i.length){let x=a-2,A=a-1;i.indexOf(x)>-1&&i.indexOf(A)>-1?h="return vec4(outputValue.x);":i.indexOf(x)>-1?h="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":i.indexOf(A)>-1&&(h="return vec4(outputValue.xx, outputValue.zz);")}return`
    vec4 ${r}() {
      ${l} coords = getOutputCoords();
      ${c}
      vec4 outputValue = get${s}(${d});
      ${h}
    }
  `}function Xee(e,t){let n=e.name,s=n.charAt(0).toUpperCase()+n.slice(1),r="get"+s+"AtOutCoords",a=t.texShape,o=e.shapeInfo.texShape,i=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&i===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(o,a))return`
      float ${r}() {
        return sampleTexture(${n}, resultUV);
      }
    `;let u=wt(l),c=FS(e.shapeInfo.logicalShape,t.logicalShape),p=l-i,d,h=["x","y","z","w","u","v"];i===0?d="":l<2&&c.length>=1?d="coords = 0;":d=c.map(m=>`coords.${h[m+p]} = 0;`).join(`
`);let f="";return l<2&&i>0?f="coords":f=e.shapeInfo.logicalShape.map((m,g)=>`coords.${h[g+p]}`).join(", "),`
    float ${r}() {
      ${u} coords = getOutputCoords();
      ${d}
      return get${s}(${f});
    }
  `}function wt(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function Gx(e,t,n){let{newShape:s,keptDims:r}=v.squeezeShape(t),a=t.length,o=e&&a===3&&t[0]===1,i=o?t.slice(1):s,l=!e&&a>1&&!v.arraysEqual(t,n)&&s.length<a||o;return{useSqueezeShape:l,uniformShape:l?i:t,keptDims:r}}function rd(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function ad(e,t){return t.map(n=>e[n]).join(", ")}function Kee(e,t,n,s){let r=n.map((c,p)=>{let d={logicalShape:c.shape,texShape:c.isUniform?null:c.texData.texShape,isUniform:c.isUniform,isPacked:c.isUniform?!1:c.texData.isPacked,flatOffset:null};return c.texData!=null&&c.texData.slice!=null&&c.texData.slice.flatOffset>0&&(d.flatOffset=c.texData.slice.flatOffset),{name:t.variableNames[p],shapeInfo:d}}),a=r.map(c=>c.shapeInfo),o={logicalShape:s.shape,texShape:s.texData.texShape,isUniform:!1,isPacked:s.texData.isPacked,flatOffset:null},i=hee(r,o,t),l=hS(e.gl,i),u=e.createProgram(l);return X().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:l,source:i,webGLProgram:u,inShapeInfos:a,outShapeInfo:o,uniformLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,inShapesLocations:null,inTexShapesLocations:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:Object.assign({program:t,fragmentShader:l,source:i,webGLProgram:u,inShapeInfos:a,outShapeInfo:o},zS(e,t,u))}function zS(e,t,n){let s={},r={},a={},o=[],i,l,u,c=null,p=null;p=e.getUniformLocation(n,"NAN",!1),X().getNumber("WEBGL_VERSION")===1&&(c=e.getUniformLocation(n,"INFINITY",!1));let d=!1;for(let h=0;h<t.variableNames.length;h++){let f=t.variableNames[h];s[f]=e.getUniformLocation(n,f,d),s[`offset${f}`]=e.getUniformLocation(n,`offset${f}`,d),t.enableShapeUniforms&&(r[`${f}Shape`]=e.getUniformLocation(n,`${f}Shape`,d),a[`${f}TexShape`]=e.getUniformLocation(n,`${f}TexShape`,d))}return t.enableShapeUniforms&&(i=e.getUniformLocation(n,"outShape",d),u=e.getUniformLocation(n,"outShapeStrides",d),l=e.getUniformLocation(n,"outTexShape",d)),t.customUniforms&&t.customUniforms.forEach((h,f)=>{o[f]=e.getUniformLocation(n,h.name,d)}),{uniformLocations:s,customUniformLocations:o,infLoc:c,nanLoc:p,inShapesLocations:r,inTexShapesLocations:a,outShapeLocation:i,outShapeStridesLocation:u,outTexShapeLocation:l}}function d7(e,t){if(e.length!==t.length)throw Error(`Binary was compiled with ${e.length} inputs, but was executed with ${t.length} inputs`);e.forEach((n,s)=>{let r=n.logicalShape,a=t[s],o=a.shape;if(!v.arraysEqual(r,o))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${r} and ${o} must match`);if(n.isUniform&&a.isUniform)return;let i=n.texShape,l=a.isUniform?null:a.texData.texShape;if(!v.arraysEqual(i,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${i} and ${l} must match`)})}function Zee(e,t,n,s,r){t.program.enableShapeUniforms||(d7(t.inShapeInfos,n),d7([t.outShapeInfo],[s]));let a=s.texData.texture,o=s.texData.texShape;s.texData.isPacked?e.setOutputPackedMatrixTexture(a.texture,o[0],o[1]):e.setOutputMatrixTexture(a.texture,o[0],o[1]),e.setProgram(t.webGLProgram),X().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((l,u)=>{let c=t.program.variableNames[u],p=t.uniformLocations[c],d=t.uniformLocations[`offset${c}`],h=t.inShapesLocations[`${c}Shape`],f=t.inTexShapesLocations[`${c}TexShape`];if(h){let{uniformShape:m}=Gx(t.program.packedInputs,l.shape,l.texData.texShape);switch(m.length){case 1:e.gl.uniform1iv(h,new Int32Array(m));break;case 2:e.gl.uniform2iv(h,new Int32Array(m));break;case 3:e.gl.uniform3iv(h,new Int32Array(m));break;case 4:e.gl.uniform4iv(h,new Int32Array(m));break;default:break}}if(f&&e.gl.uniform2i(f,l.texData.texShape[0],l.texData.texShape[1]),p!=null){if(l.isUniform){if(v.sizeFromShape(l.shape)<2)e.gl.uniform1f(p,l.uniformValues[0]);else{let m=l.uniformValues;m instanceof Float32Array||(m=new Float32Array(m)),e.gl.uniform1fv(p,m)}return}l.texData.slice!=null&&d!=null&&e.gl.uniform1i(d,l.texData.slice.flatOffset),e.setInputMatrixTexture(l.texData.texture.texture,p,u)}});let i=t.outShapeLocation;if(i)switch(s.shape.length){case 1:e.gl.uniform1iv(i,new Int32Array(s.shape));break;case 2:e.gl.uniform2iv(i,new Int32Array(s.shape));break;case 3:e.gl.uniform3iv(i,new Int32Array(s.shape));break;case 4:e.gl.uniform4iv(i,new Int32Array(s.shape));break;default:break}if(t.outShapeStridesLocation){let l=v.computeStrides(s.shape);switch(s.shape.length){case 2:e.gl.uniform1iv(t.outShapeStridesLocation,new Int32Array(l));break;case 3:e.gl.uniform2iv(t.outShapeStridesLocation,new Int32Array(l));break;case 4:e.gl.uniform3iv(t.outShapeStridesLocation,new Int32Array(l));break;default:break}}t.outTexShapeLocation&&e.gl.uniform2i(t.outTexShapeLocation,s.texData.texShape[0],s.texData.texShape[1]),t.program.customUniforms&&r&&t.program.customUniforms.forEach((l,u)=>{let c=t.customUniformLocations[u],p=r[u];if(l.type==="float")e.gl.uniform1fv(c,p);else if(l.type==="vec2")e.gl.uniform2fv(c,p);else if(l.type==="vec3")e.gl.uniform3fv(c,p);else if(l.type==="vec4")e.gl.uniform4fv(c,p);else if(l.type==="int")e.gl.uniform1iv(c,p);else if(l.type==="ivec2")e.gl.uniform2iv(c,p);else if(l.type==="ivec3")e.gl.uniform3iv(c,p);else if(l.type==="ivec4")e.gl.uniform4iv(c,p);else throw Error(`uniform type ${l.type} is not supported yet.`)}),e.executeProgram()}function Yee(e,t,n){let s="";t.concat(n).forEach(o=>{let i=o.texData!=null&&o.texData.slice!=null&&o.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!o.isUniform){let l=o.texData.texShape,{useSqueezeShape:u,uniformShape:c,keptDims:p}=Gx(e.packedInputs,o.shape,l),d="",h="",f="";if(c.length===1&&e.packedInputs){let w=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];d=`${w[0]>1}_${w[1]>1}`}else if(c.length===2&&!e.packedInputs)h=`${c[0]>1}_${c[1]>1}`;else if(c.length>2&&!e.packedInputs){let w=v.computeStrides(c);f=`${w[0]===l[1]}_${w[w.length-1]===l[1]}`}let m=o.shape.length,g=c.length===2&&v.arraysEqual(o.shape,l),y=v.sizeFromShape(o.shape)===1,x=C.getBroadcastDims(o.shape,n.shape),A=!e.packedInputs&&m===n.shape.length&&v.arraysEqual(l,n.texData.texShape),b=e.packedInputs||c.length>2?"":`${l[0]>1}_${l[1]>1}`;s+=`${m}_${A}_${u?p:""}_${c.length}_${y}_${x}_${g}_${d}_${h}_${f}_${b}_${i}`}else{let l=o.isUniform?"uniform":o.texData.texShape;s+=`${o.shape}_${l}_${i}`}});let r=e.userCode,a=e.constructor.name;return a+="_"+s+"_"+r+`${X().getNumber("WEBGL_VERSION")}`,a}function xs(e){return X().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var Jee=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=Rp.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=as();this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length),this.userCode=`
      ivec3 outCoordsFromFlatIndex(int index) {
        ${this.enableShapeUniforms?x2(["r","c","d"],e):nu(["r","c","d"],e)}
        return ivec3(r, c, d);
      }

      void main() {
        ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));
        int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);

        vec4 result = vec4(0.);

        for (int i=0; i<4; i++) {
          int flatIndex = index + i;
          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
          result[i] = getA(rc.x, rc.y, rc.z);
        }

        ${t.output} = result;
      }
    `}},Qee=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=Rp.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=as();this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length),this.userCode=`
      ivec3 outCoordsFromFlatIndex(int index) {
        ${this.enableShapeUniforms?x2(["r","c","d"],e):nu(["r","c","d"],e)}
        return ivec3(r, c, d);
      }

      void main() {
        ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));
        int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);

        vec4 result = vec4(0.);

        for (int i=0; i<4; i++) {
          int flatIndex = index + i;
          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));
        }

        ${t.output} = result;
      }
    `}},ete=class{constructor(e){this.variableNames=["A"],this.outTexUsage=qs.DOWNLOAD;let t=as();this.outputShape=e,this.userCode=`
      ${PS}

      void main() {
        float x = getAAtOutCoords();
        ${t.output} = encode_float(x);
      }
    `}},tte=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=qs.DOWNLOAD;let t=as();this.outputShape=e,this.userCode=`
      ${PS}

      void main() {
        ivec3 coords = getOutputCoords();
        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
        ${t.output} = encode_float(x);
      }
    `}},nte=class{constructor(e,t=!1){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=as();this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length);let s="result";t&&(s="floor(result * 255. + 0.5)"),this.userCode=`
      ${this.enableShapeUniforms?Ux():Vx(e)}

      void main() {
        ivec3 coords = getOutputCoords();

        int flatIndex = getFlatIndex(coords);
        int offset = imod(flatIndex, 4);

        flatIndex = idiv(flatIndex, 4, 1.);

        int r = flatIndex / texShape[1];
        int c = imod(flatIndex, texShape[1]);
        vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
        vec4 values = ${n.texture2D}(A, uv);

        float result;

        if(offset == 0) {
          result = values[0];
        } else if(offset == 1) {
          result = values[1];
        } else if(offset == 2) {
          result = values[2];
        } else {
          result = values[3];
        }

        ${n.output} = vec4(${s}, 0., 0., 0.);
      }
    `}},ste=class{constructor(e,t=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=as();this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length);let s="",r="result";t&&(r="floor(result * 255. + 0.5)");for(let a=0;a<=1;a++)for(let o=0;o<=1;o++){let i=a*2+o;s+=`
          localCoords = coords;
          if(localCoords[2] + ${o} < ${this.enableShapeUniforms?"outShape[2]":`${e[2]}`}) {
          localCoords[2] += ${o};
          if (localCoords[1] + ${a} < ${this.enableShapeUniforms?"outShape[1]":`${e[1]}`}) {
            localCoords[1] += ${a};

            flatIndex = getFlatIndex(localCoords);
            offset = imod(flatIndex, 4);

            flatIndex = idiv(flatIndex, 4, 1.);

            int r = flatIndex / texShape[1];
            int c = imod(flatIndex, texShape[1]);
            vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
            values = ${n.texture2D}(A, uv);

            if (offset == 0) {
              result[${i}] = values[0];
            } else if (offset == 1) {
              result[${i}] = values[1];
            } else if (offset == 2) {
              result[${i}] = values[2];
            } else {
              result[${i}] = values[3];
            }
          }
        }
        `}this.userCode=`
        ${this.enableShapeUniforms?Ux():Vx(e)}

        void main() {
          ivec3 coords = getOutputCoords();

          vec4 result = vec4(0.);
          int flatIndex, r, c, offset;
          ivec3 localCoords;
          vec2 uv;
          vec4 values;

          ${s}

          ${n.output} = ${r};
        }
    `}},LS={};Ve(LS,{bindVertexProgramAttributeStreams:()=>XS,createBufferFromOutputTexture:()=>YS,createFloat16MatrixTexture:()=>GS,createFloat16PackedMatrixTexture:()=>qS,createFloat32MatrixTexture:()=>US,createIndexBuffer:()=>VS,createPackedMatrixTexture:()=>jS,createUnsignedBytesMatrixTexture:()=>HS,createVertexBuffer:()=>WS,createVertexShader:()=>BS,downloadByteEncodedFloatMatrixFromOutputTexture:()=>QS,downloadFloat32MatrixFromBuffer:()=>JS,downloadMatrixFromPackedOutputTexture:()=>t9,downloadPackedMatrixFromBuffer:()=>e9,getInternalFormatForFloat16MatrixTexture:()=>jx,getInternalFormatForFloat16PackedMatrixTexture:()=>Kx,getInternalFormatForFloat32MatrixTexture:()=>Hx,getInternalFormatForPackedMatrixTexture:()=>Xx,getInternalFormatForUnsignedBytesMatrixTexture:()=>qx,uploadDenseMatrixToTexture:()=>KS,uploadPixelDataToTexture:()=>ZS});function BS(e){let t=as(),n=`${t.version}
    precision highp float;
    ${t.attribute} vec3 clipSpacePos;
    ${t.attribute} vec2 uv;
    ${t.varyingVs} vec2 resultUV;

    void main() {
      gl_Position = vec4(clipSpacePos, 1);
      resultUV = uv;
    }`;return pS(e,n)}function WS(e){let t=new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]);return gS(e,t)}function VS(e){let t=new Uint16Array([0,1,2,2,1,3]);return yS(e,t)}function Fh(e,t,n,s,r,a){xS(t,n);let o=AS(e),i=e.TEXTURE_2D;return Ie(e,()=>e.bindTexture(i,o)),Ie(e,()=>e.texParameteri(i,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),Ie(e,()=>e.texParameteri(i,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),Ie(e,()=>e.texParameteri(i,e.TEXTURE_MIN_FILTER,e.NEAREST)),Ie(e,()=>e.texParameteri(i,e.TEXTURE_MAG_FILTER,e.NEAREST)),X().getNumber("WEBGL_VERSION")===1?Ie(e,()=>e.texImage2D(i,0,s,t,n,0,r,a,null)):Ie(e,()=>e.texStorage2D(i,1,s,t,n)),Ie(e,()=>e.bindTexture(e.TEXTURE_2D,null)),{texture:o,texShape:[n,t]}}function Hx(e){return e.internalFormatFloat}function US(e,t,n,s){let[r,a]=Ph(t,n);return Fh(e,r,a,Hx(s),s.textureFormatFloat,e.FLOAT)}function jx(e){return e.internalFormatHalfFloat}function GS(e,t,n,s){let[r,a]=Ph(t,n);return Fh(e,r,a,jx(s),s.textureFormatFloat,s.textureTypeHalfFloat)}function qx(e){return e.downloadTextureFormat}function HS(e,t,n,s){let[r,a]=Ph(t,n);return Fh(e,r,a,qx(s),e.RGBA,e.UNSIGNED_BYTE)}function Xx(e){return e.internalFormatPackedFloat}function jS(e,t,n,s){let[r,a]=ed(t,n);return Fh(e,r,a,Xx(s),e.RGBA,e.FLOAT)}function Kx(e){return e.internalFormatPackedHalfFloat}function qS(e,t,n,s){let[r,a]=ed(t,n);return Fh(e,r,a,Kx(s),e.RGBA,s.textureTypeHalfFloat)}function XS(e,t,n){return Ie(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),ty(e,t,"clipSpacePos",n,3,20,0)&&ty(e,t,"uv",n,2,20,12)}function KS(e,t,n,s,r,a){Ie(e,()=>e.bindTexture(e.TEXTURE_2D,t));let o,i,l;r instanceof Uint8Array?(o=new Uint8Array(n*s*4),i=e.UNSIGNED_BYTE,l=e.RGBA):(o=new Float32Array(n*s*4),i=e.FLOAT,l=a.internalFormatPackedFloat),o.set(r),X().getNumber("WEBGL_VERSION")===2?Ie(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,n,s,e.RGBA,i,o)):Ie(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,n,s,0,e.RGBA,i,o)),Ie(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function ZS(e,t,n){Ie(e,()=>e.bindTexture(e.TEXTURE_2D,t)),n.data instanceof Uint8Array?X().getNumber("WEBGL_VERSION")===2?Ie(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,n.width,n.height,e.RGBA,e.UNSIGNED_BYTE,n.data)):Ie(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,n.width,n.height,0,e.RGBA,e.UNSIGNED_BYTE,n.data)):X().getNumber("WEBGL_VERSION")===2?Ie(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,e.RGBA,e.UNSIGNED_BYTE,n)):Ie(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,n)),Ie(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function YS(e,t,n,s){let r=e.createBuffer();Ie(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,r));let i=4*4*t*n;return Ie(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,i,e.STREAM_READ)),Ie(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,0)),Ie(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),r}function JS(e,t,n){let s=e,r=new Float32Array(n);return s.bindBuffer(s.PIXEL_PACK_BUFFER,t),s.getBufferSubData(s.PIXEL_PACK_BUFFER,0,r),s.bindBuffer(s.PIXEL_PACK_BUFFER,null),r}function QS(e,t,n,s){let[r,a]=Ph(t,n),o=4,i=new Uint8Array(QQ(t*n,o));return Ie(e,()=>e.readPixels(0,0,r,a,s.downloadTextureFormat,e.UNSIGNED_BYTE,i)),new Float32Array(i.buffer)}function e9(e,t,n,s,r,a,o,i){let l=e,u=new Float32Array(eee(a,o));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,u),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),u}function t9(e,t,n){let s=new Float32Array(t*n*4);return Ie(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,s)),s}var Hu=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=X().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,A2(t,e)):this.gl=Dr(t);let n="WEBGL_color_buffer_float",s="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),X().getNumber("WEBGL_VERSION")===1){let r="OES_texture_float",a="OES_texture_half_float";if(this.textureFloatExtension=lp(this.gl,r),Xs(this.gl,a))this.textureHalfFloatExtension=lp(this.gl,a);else if(X().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(n),Xs(this.gl,s))this.colorBufferHalfFloatExtension=lp(this.gl,s);else if(X().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(n="EXT_color_buffer_float",Xs(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(Xs(this.gl,s))this.colorBufferHalfFloatExtension=this.gl.getExtension(s);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=WS(this.gl),this.indexBuffer=VS(this.gl),this.framebuffer=bS(this.gl),this.textureConfig=Bx(this.gl,this.textureHalfFloatExtension)}get debug(){return X().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),this.outputTexture!=null&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");let e=this.gl;Ie(e,()=>e.finish()),Ie(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),Ie(e,()=>e.deleteFramebuffer(this.framebuffer)),Ie(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),Ie(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),Ie(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),US(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),GS(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),HS(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),ZS(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,s){this.throwIfDisposed(),KS(this.gl,e,t,n,s,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),qS(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),jS(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(ny(this.gl,this.framebuffer),this.outputTexture=null),Ie(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>QS(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,s,r,a){return e9(this.gl,e,t,n,s,r,a,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return JS(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let s=YS(this.gl,t,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),s}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,n;if(X().getBool("WEBGL_FENCE_API_ENABLED")){let s=e,r=s.fenceSync(s.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let a=s.clientWaitSync(r,0,0);return a===s.ALREADY_SIGNALED||a===s.CONDITION_SATISFIED},t=r}else X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>t9(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl;this.vertexShader==null&&(this.vertexShader=BS(t));let n=fS(t);return Ie(t,()=>t.attachShader(n,this.vertexShader)),Ie(t,()=>t.attachShader(n,e)),mS(t,n),this.debug&&tm(t,n),this.vertexAttrsAreBound||(this.setProgram(n),this.vertexAttrsAreBound=XS(t,this.program,this.vertexBuffer)),n}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&Ie(this.gl,()=>this.gl.deleteProgram(e))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&tm(this.gl,this.program),Ie(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?wS(this.gl,e,t):kS(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),Ie(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}setInputMatrixTexture(e,t,n){this.throwIfDisposed(),this.throwIfNoProgram(),IS(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[s,r]=ed(t,n);this.setOutputMatrixTextureDriver(e,s,r)}setOutputMatrixWriteRegion(e,t,n,s){this.setOutputMatrixWriteRegionDriver(n,e,s,t)}setOutputPackedMatrixWriteRegion(e,t,n,s){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&tm(this.gl,this.program),up(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;this.debug&&this.debugValidate(),Ie(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),Ie(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=lp(this.gl,X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension}getQueryTimerExtensionWebGL2(){return this.getQueryTimerExtension()}getQueryTimerExtensionWebGL1(){return this.getQueryTimerExtension()}beginQuery(){if(X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,s=this.getQueryTimerExtensionWebGL2(),r=n.createQuery();return n.beginQuery(s.TIME_ELAPSED_EXT,r),r}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,n=this.getQueryTimerExtensionWebGL2();t.endQuery(n.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await v.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let n=this.gl;return n.getQueryParameter(e,n.QUERY_RESULT)/1e6}else{let n=this.getQueryTimerExtensionWebGL1();return n.getQueryObjectEXT(e,n.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let n=this.gl,s=this.getQueryTimerExtensionWebGL2(),r=n.getQueryParameter(e,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(s.GPU_DISJOINT_EXT)),r&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),s=n.getQueryObjectEXT(e,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),s&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=rte(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:n}=this.itemsToPoll[t];n()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),!(this.itemsToPoll.length>1)&&v.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0))}bindTextureToFrameBuffer(e){this.throwIfDisposed(),nm(this.gl,e,this.framebuffer),this.debug&&up(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(nm(this.gl,this.outputTexture,this.framebuffer),this.debug&&up(this.gl)):ny(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let n=t();return this.unbindTextureToFrameBuffer(),n}setOutputMatrixTextureDriver(e,t,n){this.throwIfDisposed();let s=this.gl;nm(s,e,this.framebuffer),this.debug&&up(s),this.outputTexture=e,Ie(s,()=>s.viewport(0,0,t,n)),Ie(s,()=>s.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,s){this.throwIfDisposed(),Ie(this.gl,()=>this.gl.scissor(e,t,n,s))}throwIfDisposed(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")}throwIfNoProgram(){if(this.program==null)throw new Error("No GPU program is currently set.")}};function rte(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{addImpl:ate,bincountImpl:n9,bincountReduceImpl:ote,ceilImpl:ite,concatImpl:lte,equalImpl:ute,expImpl:cte,expm1Impl:dte,floorImpl:pte,gatherNdImpl:hte,gatherV2Impl:fte,greaterImpl:mte,greaterEqualImpl:gte,lessImpl:yte,lessEqualImpl:Ate,linSpaceImpl:xte,logImpl:bte,maxImpl:vte,maximumImpl:wte,minimumImpl:kte,multiplyImpl:Ite,negImpl:Ste,notEqualImpl:Cte,prodImpl:Tte,rangeImpl:Nte,rsqrtImpl:Ete,scatterImpl:Rte,sigmoidImpl:_te,simpleAbsImpl:s9,sliceImpl:Dte,sparseFillEmptyRowsImpl:$te,sparseReshapeImpl:Pte,sparseSegmentReductionImpl:r9,sqrtImpl:Fte,stridedSliceImpl:Ote,stringNGramsImpl:Mte,stringSplitImpl:zte,stringToHashBucketFastImpl:Lte,subImpl:Bte,tileImpl:Wte,topKImpl:Vte,transposeImpl:Zx,uniqueImpl:Ute}=Sx;function a9(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function Qn(e,t){return t===1?[e]:a9(e,t)}function Gte(e,t){if(e===1)return"rc";let n="";for(let s=0;s<e;s++)n+=t[s],s<e-1&&(n+=",");return n}var Hte=class{constructor(e){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.enableShapeUniforms=xs(this.outputShape.length),this.rank===0)this.userCode=`
        void main() {
          setOutput(vec4(getA(), 0., 0., 0.));
        }
      `;else{let t=Qn("rc",this.rank),n=wt(this.rank),s=this.getOutOfBoundsCondition(t),r=this.getSetup(t),a=this.getOutput(t);this.userCode=`
        void main() {
          ${n} rc = getOutputCoords();

          if(${s}) {
            setOutput(vec4(0));
          } else {
            ${r}

            setOutput(vec4(${a}));
          }
        }
      `}}getSourceCoordsArr(e){let t=[];for(let n=0;n<=1;n++)for(let s=0;s<=1;s++){let r=`${n===0?"r":"rp1"}, ${s===0?"c":"cp1"}`;for(let a=2;a<this.rank;a++)r=`${e[e.length-1-a]},`+r;t.push(r)}return t}getOutOfBoundsCondition(e){if(this.rank===1)return`rc > ${this.enableShapeUniforms?"outShape":this.outputShape[0]}`;let t="";for(let n=this.rank-2;n<this.rank;n++)t+=`${e[n]} >= ${this.enableShapeUniforms?`outShape[${n}]`:this.outputShape[n]}`,n<this.rank-1&&(t+="||");return t}getSetup(e){if(this.rank===1)return"";let t=e.slice(-2),n=this.enableShapeUniforms?`outShape[${this.rank} - 1]`:this.outputShape[this.rank-1],s=this.enableShapeUniforms?`outShape[${this.rank} - 2]`:this.outputShape[this.rank-2];return`
      int r = ${t[0]};
      int c = ${t[1]};
      int rp1 = r + 1;
      int cp1 = c + 1;

      bool cEdge = cp1 >= ${n};
      bool rEdge = rp1 >= ${s};
    `}getOutput(e){let t=this.getSourceCoordsArr(e);return this.rank===1?`getA(rc), (rc + 1 >= ${this.enableShapeUniforms?"outShape":this.outputShape[0]} ? 0. : getA(rc + 1)), 0, 0`:`getA(${t[0]}),
            cEdge ? 0. : getA(${t[1]}),
            rEdge ? 0. : getA(${t[2]}),
            rEdge || cEdge ? 0. : getA(${t[3]})`}},o9=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length);let n="";for(let s=0;s<4;s++){let r="thisRC = rc;";s%2===1&&(r+="thisRC.z += 1;"),s>1&&(r+="thisRC.y += 1;"),n+=`
        ${r}
        ${s>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
          int flatIndex = getFlatIndex(thisRC);

          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));

          result[${s}] =
            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
        ${s>0?"}":""}
      `}this.userCode=`
      ${jte(t,this.enableShapeUniforms)}
      ${this.enableShapeUniforms?Ux():Vx(e)}

      void main() {
        ivec3 rc = getOutputCoords();

        vec4 result = vec4(0.);

        ivec3 thisRC;
        int rows = ${this.enableShapeUniforms?"outShape[1]":e[1]};
        int cols = ${this.enableShapeUniforms?"outShape[2]":e[2]};

        ${n}

        setOutput(result);
      }
    `}};function jte(e,t){return`
    ivec3 inputCoordsFromReshapedOutCoords(int index) {
      ${t?pee(["r","c","d"],"inputShape"):nu(["r","c","d"],e)}
      return ivec3(r, c, d);
    }
  `}var qte=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let s=h7(t,n),r=f7(e,s,n);r in this.freeTextures||(this.freeTextures[r]=[]),r in this.usedTextures||(this.usedTextures[r]=[]);let a=p7(e,s,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[r].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=a,this.log();let i=this.freeTextures[r].shift();return this.usedTextures[r].push(i),i}let o;return s===Sn.PACKED_2X2_FLOAT32?o=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):s===Sn.PACKED_2X2_FLOAT16?o=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):s===Sn.UNPACKED_FLOAT32?o=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):s===Sn.UNPACKED_FLOAT16?o=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):s===Sn.PACKED_4X1_UNSIGNED_BYTE&&(o=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[r].push(o),this.numUsedTextures++,this._numBytesAllocated+=a,this.log(),o}releaseTexture(e,t,n,s){if(this.freeTextures==null)return;let r=h7(n,s),a=f7(t,r,s);a in this.freeTextures||(this.freeTextures[a]=[]);let o=p7(t,r,this.gpgpu.gl,this.gpgpu.textureConfig,s),i=X().get("WEBGL_DELETE_TEXTURE_THRESHOLD");i!==-1&&this._numBytesAllocated>i?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=o):(this.freeTextures[a].push(e),this.numFreeTextures++,this._numBytesFree+=o),this.numUsedTextures--;let l=this.usedTextures[a],u=l.indexOf(e);if(u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(u,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function Xte(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F)return 16;if(t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;if(t===n.RGBA8)return 4;throw new Error(`Unknown internal format ${t}`)}function p7(e,t,n,s,r){let a=Kte(t,s),o;if(r){let[l,u]=ed(e[0],e[1]);o=l*u}else{let[l,u]=Ph(e[0],e[1]);o=l*u}let i=Xte(n,a);return o*i}function Kte(e,t){switch(e){case Sn.PACKED_2X2_FLOAT32:return Xx(t);case Sn.PACKED_2X2_FLOAT16:return Kx(t);case Sn.UNPACKED_FLOAT32:return Hx(t);case Sn.UNPACKED_FLOAT16:return jx(t);case Sn.PACKED_4X1_UNSIGNED_BYTE:return qx(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function Zte(e){return X().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?Sn.PACKED_2X2_FLOAT32:Sn.UNPACKED_FLOAT32:e?Sn.PACKED_2X2_FLOAT16:Sn.UNPACKED_FLOAT16}function h7(e,t){if(e===qs.UPLOAD)return Sn.PACKED_2X2_FLOAT32;if(e===qs.RENDER||e==null)return Zte(t);if(e===qs.DOWNLOAD||e===qs.PIXELS)return Sn.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function f7(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var da=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length),this.userCode=`
      float unaryOperation(float x) {
        ${t}
      }

      void main() {
        float x = getAAtOutCoords();
        float y = unaryOperation(x);

        setOutput(y);
      }
    `}},hr="if (isnan(x)) return x;",Yte="return x;",m7="return abs(x);",Jte="return (x >= 0.0) ? x : (exp(x) - 1.0);",Qte=hr+`
  return (x < 0.0) ? 0.0 : x;
`,ene=hr+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,$u="return x;",tne="return 1.0 / (1.0 + exp(-1.0 * x));",nne="return x;",sne=`
  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;
`,rne=`
  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;
`,ane=`
  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;
`,one="return 1.0 / (1.0 + exp(-1.0 * x));",Vi=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length),this.userCode=`
      vec4 unaryOperation(vec4 x) {
        ${t}
      }

      void main() {
        vec4 x = getAAtOutCoords();
        vec4 y = unaryOperation(x);

        setOutput(y);
      }
    `}},ine=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length);let t=e.length,n=Qn("rc",t),s=wt(t),r=Gte(t,n),a=n.slice(-2),o=t<=1?"rc":`vec2(${a.join(",")})`;this.userCode=`
      void main() {
        ${s} rc = getOutputCoords();
        vec4 packedInput = getA(${r});

        setOutput(getChannel(packedInput, ${o}));
      }
    `}},lne=dr.whereImpl,une=1e-7,cne=1e-4,Kf={};function dne(e){return e in Kf||(Kf[e]={}),Kf[e]}var pne=X().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),hne=600;function fne(){return X().global.screen==null?1024:X().global.screen.height*X().global.screen.width*window.devicePixelRatio*hne/1024/1024}var od=class extends uc{constructor(e){if(super(),this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.pendingDeletes=0,this.disposed=!1,!X().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let t;if(e!=null){if(e instanceof Hu)t=e;else{let n=Dr(X().getNumber("WEBGL_VERSION"),e);t=new Hu(n)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let n=Dr(X().getNumber("WEBGL_VERSION"));t=new Hu(n),this.binaryCache=dne(X().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=t,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new qte(this.gpgpu),this.numMBBeforeWarning=fne(),this.texData=new Op(this,sn())}nextDataId(){return od.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}write(e,t,n){if((X().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||X().getBool("DEBUG"))&&this.checkNumericalProblems(e),n==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let s={id:this.nextDataId()};return this.texData.set(s,{shape:t,dtype:n,values:e,usage:qs.UPLOAD,refCount:1}),s}refCount(e){return this.texData.has(e)?this.texData.get(e).refCount:0}incRef(e){let t=this.texData.get(e);t.refCount++}decRef(e){if(this.texData.has(e)){let t=this.texData.get(e);t.refCount--}}move(e,t,n,s,r){if(X().getBool("DEBUG")&&this.checkNumericalProblems(t),s==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:s,values:t,usage:qs.UPLOAD,refCount:r})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:s,complexTensorInfos:r,slice:a,shape:o,isPacked:i}=t;if(a!=null){let p;i?p=new Vi(o,$u):p=new da(o,$u);let d=this.runWebGLProgram(p,[{dataId:e,shape:o,dtype:s}],s),h=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),h}if(n!=null)return this.convertAndCacheOnCPU(e);if(s==="string")return n;let l=this.activeTimers!=null,u;l&&(u=v.now());let c;if(s==="complex64"){let p=this.readSync(r.real.dataId),d=this.readSync(r.imag.dataId);c=C.mergeRealAndImagArrays(p,d)}else c=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-u),this.convertAndCacheOnCPU(e,c)}async read(e){if(this.pendingRead.has(e)){let h=this.pendingRead.get(e);return new Promise(f=>h.push(f))}let t=this.texData.get(e),{values:n,shape:s,slice:r,dtype:a,complexTensorInfos:o,isPacked:i}=t;if(r!=null){let h;i?h=new Vi(s,$u):h=new da(s,$u);let f=this.runWebGLProgram(h,[{dataId:e,shape:s,dtype:a}],a),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(X().getBool("DEBUG")&&!X().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&X().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,u;if(a!=="complex64"&&X().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let h=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(h.texture.texture,...qf(s))}this.pendingRead.set(e,[]),a!=="complex64"&&await this.gpgpu.createAndWaitForFence();let c;if(a==="complex64"){let h=await Promise.all([this.read(o.real.dataId),this.read(o.imag.dataId)]),f=h[0],m=h[1];c=C.mergeRealAndImagArrays(f,m)}else if(l==null)c=this.getValuesFromTexture(e);else{let h=v.sizeFromShape(s);c=this.gpgpu.downloadFloat32MatrixFromBuffer(l,h)}if(u!=null&&this.disposeIntermediateTensorInfo(u),l!=null){let h=this.gpgpu.gl;Ie(h,()=>h.deleteBuffer(l))}let p=this.convertAndCacheOnCPU(e,c),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(h=>h(p)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&sn().removeDataId(e,this),this.pendingDeletes--),p}readToGPU(e,t={}){let n=this.texData.get(e),{values:s,shape:r,slice:a,dtype:o,isPacked:i,texture:l}=n;if(o==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(a!=null){let d;i?d=new Vi(r,$u):d=new da(r,$u);let h=this.runWebGLProgram(d,[{dataId:e,shape:r,dtype:o}],o),f=this.readToGPU(h,t);return this.disposeIntermediateTensorInfo(h),f}if(l==null)throw s!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let u=this.decode(e,t.customTexShape),c=sn().makeTensorFromTensorInfo(u),p=this.texData.get(u.dataId);return Object.assign({tensorRef:c},p.texture)}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let n=t.map(s=>v.decodeString(s));return Le(e.shape,e.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return Le(e.shape,e.dtype,t)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!cS(n))throw X().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:s}=this.texData.get(e),r=v.sizeFromShape(t);if(X().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let p=this.decode(e),d=this.texData.get(p.dataId),h=this.gpgpu.downloadMatrixFromPackedTexture(d.texture.texture,...qf(t)).subarray(0,r);return this.disposeIntermediateTensorInfo(p),h}let a=X().getBool("WEBGL_PACK")&&s===!0,o=a?sm(t):t,i=a?new tte(o):new ete(o),l=this.runWebGLProgram(i,[{shape:o,dtype:n,dataId:e}],"float32"),u=this.texData.get(l.dataId),c=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture.texture,u.texShape[0],u.texShape[1]).subarray(0,r);return this.disposeIntermediateTensorInfo(l),c}timerAvailable(){return X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(e){let t=this.activeTimers,n=[],s=!1;this.programTimersStack==null?(this.programTimersStack=n,s=!0):this.activeTimers.push(n),this.activeTimers=n,e();let r=v.flatten(this.activeTimers.map(i=>i.query)).filter(i=>i!=null),a=v.flatten(this.activeTimers.map(i=>i.name)).filter(i=>i!=null);this.activeTimers=t,s&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let i=await Promise.all(r);o.kernelMs=v.sum(i),o.getExtraProfileInfo=()=>i.map((l,u)=>({name:a[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else o.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,o})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:s,usage:r,isPacked:a,slice:o}=this.texData.get(e),i=o&&o.origDataId||e,l=this.dataRefCount.get(i);l>1?this.dataRefCount.set(i,l-1):(this.dataRefCount.delete(i),t!=null&&(this.numBytesInGPU-=this.computeBytes(s,n),this.textureManager.releaseTexture(t,s,r,a)));let u=this.texData.get(e);u.texture=null,u.texShape=null,u.isPacked=!1,u.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture.texture}getDataInfo(e){return this.texData.get(e)}shouldExecuteOnCPU(e,t=pne){return X().getBool("WEBGL_CPU_FORWARD")&&e.every(n=>this.texData.get(n.dataId).texture==null&&v.sizeFromShape(n.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){C.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return lne(e.shape,t)}packedUnaryOp(e,t,n){let s=new Vi(e.shape,t),r=this.compileAndRun(s,[e],n);return sn().makeTensorFromTensorInfo(r)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let s=s9(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,s)}if(X().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,m7,e.dtype);let t=new da(e.shape,m7),n=this.compileAndRun(t,[e]);return sn().makeTensorFromTensorInfo(n)}makeTensorInfo(e,t,n){let s;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let r=n.map(a=>v.encodeString(a));s=this.write(r,e,t)}else s=this.write(n,e,t);return this.texData.get(s).usage=null,{dataId:s,shape:e,dtype:t}}makeOutput(e,t,n){return sn().makeTensorFromTensorInfo(this.makeTensorInfo(e,t,n),this)}unpackTensor(e){let t=new ine(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new Hte(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[nl(e.shape),...sl(e.shape)],s={dtype:e.dtype,shape:n,dataId:e.dataId},r=[nl(t),...sl(t)],a=new o9(r,n),o=!0,i=[n],l=this.runWebGLProgram(a,[s],e.dtype,i,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}decode(e,t){let n=this.texData.get(e),{isPacked:s,shape:r,dtype:a}=n;if(t!=null){let p=v.sizeFromShape(r),d=t[0]*t[1]*4;v.assert(p<=d,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let o=sm(r),i;s?i=new Qee(o):i=new Jee(o);let l=!0,u=[t!=null?t:qf(o)],c=this.runWebGLProgram(i,[{shape:o,dtype:a,dataId:e}],a,u,l,t);return{dtype:a,shape:r,dataId:c.dataId}}runWebGLProgram(e,t,n,s,r=!1,a){let o=this.makeTensorInfo(e.outputShape,n),i=this.texData.get(o.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===Rp.DENSE){let g=a!=null?a:qf(e.outputShape);i.texShape=g.map(y=>y*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),v.sizeFromShape(o.shape)===0)return i.values=v.getTypedArrayFromDType(o.dtype,0),o;let l=[],u=t.map(g=>{if(g.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let y=this.texData.get(g.dataId);if(y.texture==null){if(!e.packedInputs&&v.sizeFromShape(g.shape)<=X().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:g.shape,texData:null,isUniform:!0,uniformValues:y.values};e.packedInputs&&(y.isPacked=!0,y.shape=g.shape)}if(this.uploadToGPU(g.dataId),!!y.isPacked!=!!e.packedInputs)g=y.isPacked?this.unpackTensor(g):this.packTensor(g),l.push(g),y=this.texData.get(g.dataId);else if(y.isPacked&&!_p(y.shape,g.shape)){let x=g,A=g.shape;g.shape=y.shape,g=this.packedReshape(g,A),l.push(g),y=this.texData.get(g.dataId),x.shape=A}return{shape:g.shape,texData:y,isUniform:!1}});this.uploadToGPU(o.dataId);let c={shape:o.shape,texData:i,isUniform:!1},p=Yee(e,u,c),d=this.getAndSaveBinary(p,()=>Kee(this.gpgpu,e,u,c)),h=this.activeTimers!=null,f;h&&(f=this.startTimer()),X().get("ENGINE_COMPILE_ONLY")||Zee(this.gpgpu,d,u,c,s),l.forEach(g=>this.disposeIntermediateTensorInfo(g)),h&&(f=this.endTimer(f),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(f)}));let m=X().get("WEBGL_FLUSH_THRESHOLD");if(m>0){let g=v.now();g-this.lastGlFlushTime>m&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=g)}if(!X().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&r===!1){let g=this.unpackTensor(o);return this.disposeIntermediateTensorInfo(o),g}return o}compileAndRun(e,t,n,s,r=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,s,r)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(X().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(t=>{this.gpgpu.deleteProgram(this.binaryCache[t].webGLProgram),delete this.binaryCache[t]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=J(()=>{if(!X().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=X().getBool("DEBUG");X().set("DEBUG",!1);let t=this.abs(Se(1e-8)).dataSync()[0];if(X().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?une:cne}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:s,values:r,texture:a,usage:o,isPacked:i}=t;if(a!=null)return;let l=this.activeTimers!=null,u;l&&(u=v.now());let c=t.texShape;if(c==null&&(c=TS(n,i),t.texShape=c),r!=null){let p=sm(n),d,h=c[1],f=c[0],m=r instanceof Uint8Array||r instanceof Uint8ClampedArray;(i||!m)&&([h,f]=ed(c[0],c[1])),i?d=new ste(p,m):d=new nte(p,m);let g=m?[f,h]:c,y=this.makeTensorInfo(g,s),x=this.texData.get(y.dataId);m?x.usage=qs.PIXELS:x.usage=qs.UPLOAD,x.texShape=g,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(y.dataId),h,f,r);let A=[[f,h]],b=!0,w=this.runWebGLProgram(d,[y],s,A,b),k=this.texData.get(w.dataId);t.texShape=k.texShape,t.isPacked=k.isPacked,t.usage=k.usage,X().get("ENGINE_COMPILE_ONLY")?this.disposeData(w.dataId):(t.texture=k.texture,t.values=null,this.texData.delete(w.dataId)),this.disposeIntermediateTensorInfo(y),l&&(this.uploadWaitMs+=v.now()-u)}else{let p=this.acquireTexture(c,o,s,i);t.texture=p}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:s}=n;return this.releaseGPUData(e),t!=null&&(n.values=mne(t,s)),n.values}acquireTexture(e,t,n,s){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let r=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${r} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,s)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}checkCompileCompletion(){for(let[,e]of Object.entries(this.binaryCache))this.checkCompletion_(e)}async checkCompileCompletionAsync(){let e=[];if(this.gpgpu.parallelCompilationExtension){for(let[,t]of Object.entries(this.binaryCache))e.push(this.checkCompletionAsync_(t));return Promise.all(e)}else{for(let[,t]of Object.entries(this.binaryCache)){let n=new Promise(s=>{try{this.checkCompletion_(t),s(!0)}catch(r){throw r}});e.push(n)}return Promise.all(e)}}async checkCompletionAsync_(e){return this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(e):(await jA(),this.checkCompletionAsync_(e))}checkCompletion_(e){if(this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.gl.LINK_STATUS)===!1)throw console.log(this.gpgpu.gl.getProgramInfoLog(e.webGLProgram)),this.gpgpu.gl.getShaderParameter(e.fragmentShader,this.gpgpu.gl.COMPILE_STATUS)===!1?(Wx(e.source,this.gpgpu.gl.getShaderInfoLog(e.fragmentShader)),new Error("Failed to compile fragment shader.")):new Error("Failed to link vertex and fragment shaders.");return!0}getUniformLocations(){for(let[,e]of Object.entries(this.binaryCache)){let{uniformLocations:t,customUniformLocations:n,infLoc:s,nanLoc:r,inShapesLocations:a,inTexShapesLocations:o,outShapeLocation:i,outShapeStridesLocation:l,outTexShapeLocation:u}=zS(this.gpgpu,e.program,e.webGLProgram);e.uniformLocations=t,e.customUniformLocations=n,e.infLoc=s,e.nanLoc=r,e.inShapesLocations=a,e.inTexShapesLocations=o,e.outShapeLocation=i,e.outShapeStridesLocation=l,e.outTexShapeLocation=u}}};od.nextDataId=0;function mne(e,t){if(t==="float32"||t==="complex64")return e;if(t==="int32"||t==="bool"){let n=t==="int32"?new Int32Array(e.length):new Uint8Array(e.length);for(let s=0;s<n.length;++s)n[s]=Math.round(e[s]);return n}else throw new Error(`Unknown dtype ${t}`)}var gne="3.19.0";function i9(){X().set("WEBGL_FORCE_F16_TEXTURES",!0)}sh.isBrowser()&&jl("webgl",()=>new od,2);var yne={forceHalfFloat:i9},l9=`
  if (isnan(a)) return a;
  if (isnan(b)) return b;
`,lc=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=C.assertAndGetBroadcastShape(t,n),this.enableShapeUniforms=xs(this.outputShape.length),this.userCode=`
      float binaryOperation(float a, float b) {
        ${e}
      }

      void main() {
        float a = getAAtOutCoords();
        float b = getBAtOutCoords();
        setOutput(binaryOperation(a, b));
      }
    `}},b2=`
  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;
`,Oh=class{constructor(e,t,n,s=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=C.assertAndGetBroadcastShape(t,n);let r=this.outputShape.length;this.enableShapeUniforms=xs(r);let a="";if(s)if(r===0||v.sizeFromShape(this.outputShape)===1)a=`
          result.y = 0.;
          result.z = 0.;
          result.w = 0.;
        `;else if(a=`
          ${wt(r)} coords = getOutputCoords();
        `,r===1)this.enableShapeUniforms?a+=`
            result.y = (coords + 1) >= outShape ? 0. : result.y;
            result.z = 0.;
            result.w = 0.;
          `:a+=`
            result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
            result.z = 0.;
            result.w = 0.;
          `;else{let i=Qn("coords",r);this.enableShapeUniforms?a+=`
            bool nextRowOutOfBounds =
              (${i[r-2]} + 1) >= outShape[${r} - 2];
            bool nextColOutOfBounds =
              (${i[r-1]} + 1) >= outShape[${r} - 1];
            result.y = nextColOutOfBounds ? 0. : result.y;
            result.z = nextRowOutOfBounds ? 0. : result.z;
            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
          `:a+=`
            bool nextRowOutOfBounds =
              (${i[r-2]} + 1) >= ${this.outputShape[r-2]};
            bool nextColOutOfBounds =
              (${i[r-1]} + 1) >= ${this.outputShape[r-1]};
            result.y = nextColOutOfBounds ? 0. : result.y;
            result.z = nextRowOutOfBounds ? 0. : result.z;
            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
          `}this.userCode=`
      vec4 binaryOperation(vec4 a, vec4 b) {
        ${e}
      }

      void main() {
        vec4 a = getAAtOutCoords();
        vec4 b = getBAtOutCoords();

        vec4 result = binaryOperation(a, b);
        ${a}

        setOutput(result);
      }
    `}};function Ps(e){let{inputs:t,backend:n}=e,{x:s}=t;return n.incRef(s.dataId),{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}var Ane={kernelName:Ro,backendName:"webgl",kernelFunc:Ps};function di(e){let{inputs:t,backend:n}=e,{real:s,imag:r}=t,a=n.makeTensorInfo(s.shape,"complex64"),o=n.texData.get(a.dataId),i=Ps({inputs:{x:s},backend:n}),l=Ps({inputs:{x:r},backend:n});return o.complexTensorInfos={real:i,imag:l},a}var xne={kernelName:zp,backendName:"webgl",kernelFunc:di},u9="return (a < 0.) ? b * a : a;",c9=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function bne(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{alpha:a}=s,o=n.makeTensorInfo([],"float32",v.createScalarValue(a,"float32")),i=X().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Oh(c9,r.shape,o.shape):new lc(u9,r.shape,o.shape),l=n.runWebGLProgram(i,[r,o],"float32");return n.disposeIntermediateTensorInfo(o),l}var vne={kernelName:_o,backendName:"webgl",kernelFunc:bne},d9="return (a < 0.) ? b * a : a;",p9=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function wne(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t,a=X().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Oh(p9,s.shape,r.shape):new lc(d9,s.shape,r.shape);return n.runWebGLProgram(a,[s,r],"float32")}var kne={kernelName:Uo,backendName:"webgl",kernelFunc:wne},id="if (isnan(x)) return x;",Ine=`
  if (isnan(a)) return a;
  if (isnan(b)) return b;
`,Sne=`
  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 ct({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:s}){return({inputs:r,backend:a})=>{let{x:o}=r,i=a,l=s||o.dtype;if(i.shouldExecuteOnCPU([o])&&n!=null){let p=i.texData.get(o.dataId),d=n(p.values,l);return i.makeTensorInfo(o.shape,l,d)}let u=X().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return u?c=new Vi(o.shape,t):c=new da(o.shape,e),i.runWebGLProgram(c,[o],l)}}function Rn({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:s=!1,cpuKernelImpl:r,dtype:a}){return({inputs:o,backend:i})=>{let{a:l,b:u}=o,c=i;if(s&&l.dtype==="complex64"){let f=c.texData.get(l.dataId),m=c.texData.get(u.dataId),[g,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(A=>{let[b,w]=A,k={dataId:b.dataId,dtype:b.dtype,shape:l.shape},S={dataId:w.dataId,dtype:w.dtype,shape:u.shape},E=new lc(e,l.shape,u.shape);return c.runWebGLProgram(E,[k,S],On(b.dtype,w.dtype))}),x=di({inputs:{real:g,imag:y},backend:c});return c.disposeIntermediateTensorInfo(g),c.disposeIntermediateTensorInfo(y),x}let p=a||On(l.dtype,u.dtype);if((l.dtype==="string"||u.dtype==="string"||c.shouldExecuteOnCPU([l,u]))&&r!=null){let f=c.texData.get(l.dataId).values,m=c.texData.get(u.dataId).values,g=l.dtype==="string"?C.fromUint8ToStringArray(f):f,y=l.dtype==="string"?C.fromUint8ToStringArray(m):m,[x,A]=r(l.shape,u.shape,g,y,p),b=c.makeTensorInfo(A,p),w=c.texData.get(b.dataId);return w.values=x,b}let d=X().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,h;return d?h=new Oh(t,l.shape,u.shape,n):h=new lc(e,l.shape,u.shape),c.runWebGLProgram(h,[l,u],p)}}function v2(e,t=!1){if(e==="linear")return t?nne:Yte;if(e==="relu")return t?rne:Qte;if(e==="elu")return t?sne:Jte;if(e==="relu6")return t?ane:ene;if(e==="prelu")return t?p9:d9;if(e==="leakyrelu")return t?c9:u9;if(e==="sigmoid")return t?one:tne;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var h9=class{constructor(e,t,n,s=!1,r=!1,a=!1,o=null,i=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n,this.enableShapeUniforms=xs(this.outputShape.length);let u=s?e[1]:e[2],c=Math.ceil(u/2),p=s?"i * 2, rc.y":"rc.y, i * 2",d=r?"rc.z, i * 2":"i * 2, rc.z",h=s?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",g="";o&&(i?m=`vec4 activation(vec4 a) {
          vec4 b = getPreluActivationWeightsAtOutCoords();
          ${o}
        }`:l?m=`vec4 activation(vec4 a) {
          vec4 b = getLeakyreluAlphaAtOutCoords();
          ${o}
        }`:m=`vec4 activation(vec4 x) {
          ${o}
        }`,g="result = activation(result);");let y=a?"result += getBiasAtOutCoords();":"";a&&this.variableNames.push("bias"),i&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let x="rc.x",A="rc.x";e[0]<t[0]?x=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(A=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
      ${m}
      // Don't use uniform for sharedDimensionPacked for performance.
      const float sharedDimension = ${c}.0;

      vec4 dot2x2ARowBCol(ivec3 rc) {
        vec4 result = vec4(0);
        for (int i = 0; i < ${c}; i++) {
          int batchA = ${x};
          int batchB = ${A};
          vec4 a = getMatrixA(batchA, ${p});
          vec4 b = getMatrixB(batchB, ${d});

          // These swizzled products need to be separately added.
          // See: https://github.com/tensorflow/tfjs/issues/1735
          result += (${h[0]} * ${f[0]});
          result += (${h[1]} * ${f[1]});
        }
        return result;
      }

      void main() {
        ivec3 rc = getOutputCoords();
        vec4 result = dot2x2ARowBCol(rc);

        ${y}

        ${g}

        setOutput(result);
      }
    `}},g7={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},y7=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=C.assertAndGetBroadcastShape(t,n),this.userCode=`
      float binaryOpComplex(
          float areal, float aimag, float breal, float bimag) {
        ${e}
      }

      void main() {
        float areal = getARealAtOutCoords();
        float aimag = getAImagAtOutCoords();
        float breal = getBRealAtOutCoords();
        float bimag = getBImagAtOutCoords();
        setOutput(binaryOpComplex(areal, aimag, breal, bimag));
      }
    `}},A7="return a * b;";function Yx(e){let{inputs:t,backend:n}=e,{a:s,b:r}=t,a=C.upcastType(s.dtype,r.dtype);if(s.dtype==="complex64"){let i=n.texData.get(s.dataId),l=n.texData.get(r.dataId),u=new y7(g7.REAL,s.shape,r.shape),c=new y7(g7.IMAG,s.shape,r.shape),p=[{dataId:i.complexTensorInfos.real.dataId,dtype:i.complexTensorInfos.real.dtype,shape:s.shape},{dataId:i.complexTensorInfos.imag.dataId,dtype:i.complexTensorInfos.imag.dtype,shape:s.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:r.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:r.shape}],d=n.runWebGLProgram(u,p,"float32"),h=n.runWebGLProgram(c,p,"float32"),f=di({inputs:{real:d,imag:h},backend:n});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),f}if(n.shouldExecuteOnCPU([s,r])){let i=n.texData.get(s.dataId),l=n.texData.get(r.dataId),[u,c]=Ite(s.shape,r.shape,i.values,l.values,a),p=n.makeTensorInfo(c,a),d=n.texData.get(p.dataId);return d.values=u,p}let o;return X().getBool("WEBGL_PACK_BINARY_OPERATIONS")?o=new Oh(A7,s.shape,r.shape):o=new lc(A7,s.shape,r.shape),n.runWebGLProgram(o,[s,r],a)}var Cne={kernelName:Bo,backendName:"webgl",kernelFunc:Yx};function Tne(e,t,n){let s=[nl(e.shape),...sl(e.shape)],r={dtype:e.dtype,shape:s,dataId:e.dataId},a=[nl(t),...sl(t)],o=new o9(a,s),i=!0,l=[s],u=n.runWebGLProgram(o,[r],e.dtype,l,i);return{dataId:u.dataId,shape:t,dtype:u.dtype}}function be(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{shape:a}=s,o=n,i=v.sizeFromShape(r.shape),l=v.inferFromImplicitShape(a,i),u=v.sizeFromShape(l);v.assert(i===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${r.shape}) has ${i} elements. The new shape and old shape must have the same number of elements.`);let c=o.texData.get(r.dataId);return c.isPacked&&!_p(r.shape,l)&&!(c.texture!==null&&_p(c.shape,l))?Tne(r,l,o):(o.incRef(r.dataId),{dataId:r.dataId,shape:l,dtype:r.dtype})}var Nne={kernelName:Rl,backendName:"webgl",kernelFunc:be},x7=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:s,inSize:r,outSize:a}=e;this.outputShape=[s,a];let o=Math.floor(n/4)*4,i=n%4,l="sumValue += dot(values, ones);";if(t!=null){let c=1/t;l=`sumValue += dot(values * ${v.isInt(c)?c.toPrecision(2):c}, ones);`}let u="";r%n>0&&(u=`
        if (inIdx < 0 || inIdx >= ${r}) {
          return 0.0;
        }
      `),this.userCode=`
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float getValue(int batch, int inIdx) {
        ${u}
        return getX(batch, inIdx);
      }

      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = outIdx * ${n};

        float sumValue = 0.0;

        for (int i = 0; i < ${o}; i += 4) {
          int inIdx = inOffset + i;
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          ${l}
        }

        int inIdx = inOffset + ${o};
        if (${i===1}) {
          vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);

          ${l}
        } else if (${i===2}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1), 0.0, 0.0);

          ${l}
        } else if (${i===3}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2), 0.0);

          ${l}
        }
        setOutput(sumValue);
      }
    `}},Ene=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:s,inSize:r,outSize:a}=e;this.outputShape=[s,a];let o="0.0",i="";t==="prod"?o="1.0":t==="min"?(o="1.0 / 1e-20",i="min"):t==="max"&&(o="-1.0 / 1e-20",i="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let u=Math.floor(n/4)*4,c=n%4,p=`
      if (${t==="sum"}) {
        sumValue += dot(values, ones);
      } else if (${t==="prod"}) {
        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);
        prodValue *= tmp[0] * tmp[1];
      } else {
        minMaxValue = ${i}(values, minMaxValue);
        if (${t==="min"} || ${t==="max"}) {
          minMaxValue = ${i}(values, minMaxValue);
          bvec4 isNaN = isnan(values);
          if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) {
            minMaxValue = vec4(NAN);
          }
        }
      }
    `,d="vec4";t==="all"?(o="1.0",p=`
        bool reducedAllValue = all(values);
        float floatedReducedAllValue = float(reducedAllValue);
        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
      `,d="bvec4"):t==="any"&&(o="0.0",p=`
        bool reducedAnyValue = any(values);
        float floatedReducedAnyValue = float(reducedAnyValue);
        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
      `,d="bvec4");let h="";r%n>0&&(h=`
        if (inIdx < 0 || inIdx >= ${r}) {
          return initializationValue;
        }
      `),this.userCode=`
      const float initializationValue = ${o};
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float getValue(int batch, int inIdx) {
        ${h}
        return getX(batch, inIdx);
      }

      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = outIdx * ${n};

        vec4 minMaxValue = vec4(${o});
        float prodValue = 1.0;
        float sumValue = 0.0;
        float allValue = 1.0;
        float anyValue = 0.0;

        for (int i = 0; i < ${u}; i += 4) {
          int inIdx = inOffset + i;
          ${d} values = ${d}(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          ${p}
        }

        int inIdx = inOffset + ${u};
        if (${c===1}) {
          ${d} values = ${d}(
            getValue(batch, inIdx),
            initializationValue,
            initializationValue,
            initializationValue
          );

          ${p}
        } else if (${c===2}) {
          ${d} values = ${d}(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            initializationValue,
            initializationValue
          );

          ${p}
        } else if (${c===3}) {
          ${d} values = ${d}(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            initializationValue
          );

          ${p}
        }
        setOutput(${l});
      }
    `}};function Rne(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let n=t.length?t[t.length-1].outSize:e[1],s=C.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:s,outSize:Math.ceil(n/s)})}return t}function ru(e,t,n,s){let r=Rne(e.shape),a=e;for(let o=0;o<r.length;o++){let{inSize:i,windowSize:l,outSize:u}=r[o],c,p;n==="mean"?c=o===0?new x7({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u},i):new x7({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u}):c=new Ene({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u},n),p=a,a=s.runWebGLProgram(c,[a],t),p.dataId!==e.dataId&&s.disposeIntermediateTensorInfo(p)}return a}var _ne=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let a=0;a<n.length;a++)n[a]=e[t[a]];this.outputShape=n,this.rank=n.length;let s=wt(this.rank),r=Dne(t);this.userCode=`
    void main() {
      ${s} resRC = getOutputCoords();
      setOutput(getA(${r}));
    }
    `}};function Dne(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],s=new Array(t);for(let r=0;r<e.length;r++)s[e[r]]=n[r];return s.join()}var $ne=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(e.length);for(let u=0;u<n.length;u++)n[u]=e[t[u]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let s=wt(this.rank),r=a9("rc",this.rank),a=new Array(this.rank);for(let u=0;u<t.length;u++)a[t[u]]=r[u];let o=`vec2(${a.slice(-2).join()})`,i=`++${r[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${a.join()}), ${o})`;this.userCode=`
    void main() {
      ${s} rc = getOutputCoords();
      vec4 result = vec4(0.);
      result[0] = ${l};
      if(${i}) {
        result[1] = ${l};
      }
      --${r[this.rank-1]};
      if(++${r[this.rank-2]} < ${n[this.rank-2]}) {
        result[2] = ${l};
        if(${i}) {
          result[3] = ${l};
        }
      }
      setOutput(result);
    }
    `}};function w2(e,t,n){let s=X().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new $ne(e.shape,t):new _ne(e.shape,t);return n.runWebGLProgram(s,[e],e.dtype)}function Pne(e,t,n,s){let r=t,a=e.shape.length,o=v.parseAxisParam(r,e.shape),i=o,l=C.getAxesPermutation(i,a),u=l!=null,c=e;u&&(c=w2(e,l,s),i=C.getInnerMostAxes(i.length,a)),C.assertAxesAreInnerMostDims("sum",i,a);let[p,d]=C.computeOutAndReduceShapes(c.shape,i),h=p;n&&(h=C.expandShapeToKeepDim(p,o));let f=v.sizeFromShape(d),g=v.sizeFromShape(e.shape)/f,y=be({inputs:{x:c},attrs:{shape:[g,f]},backend:s}),x=nh(e.dtype),A=ru(y,x,"sum",s),b=be({inputs:{x:A},attrs:{shape:h},backend:s});return s.disposeIntermediateTensorInfo(y),s.disposeIntermediateTensorInfo(A),u&&s.disposeIntermediateTensorInfo(c),b}function k2(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return Pne(r,a,o,n)}var Fne={kernelName:Qo,backendName:"webgl",kernelFunc:k2};function ts(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{perm:a}=s,o=n,i=r.shape.length,l=new Array(i);for(let c=0;c<l.length;c++)l[c]=r.shape[a[c]];let u;if(o.shouldExecuteOnCPU([r])){let p=o.texData.get(r.dataId).values,d=Zx(p,r.shape,r.dtype,a,l);u=o.makeTensorInfo(l,r.dtype);let h=o.texData.get(u.dataId);h.values=d}else u=w2(r,a,o);return u}var One={kernelName:Gr,backendName:"webgl",kernelFunc:ts},f9=1e3;function Pm({a:e,b:t,transposeA:n,transposeB:s,backend:r,bias:a=null,preluActivationWeights:o=null,leakyreluAlpha:i=0,activation:l=null}){let u=e.shape.length,c=t.shape.length,p=n?e.shape[u-2]:e.shape[u-1],d=s?t.shape[c-1]:t.shape[c-2],h=n?e.shape[u-1]:e.shape[u-2],f=s?t.shape[c-2]:t.shape[c-1],m=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(m),x=v.sizeFromShape(g),b=ql.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,f]);v.assert(p===d,()=>`Error in matMul: inner shapes (${p}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${s} must match.`);let w=n?[y,p,h]:[y,h,p],k=s?[x,f,d]:[x,d,f],S=be({inputs:{x:e},backend:r,attrs:{shape:w}}),E=be({inputs:{x:t},backend:r,attrs:{shape:k}}),R=[S,E],P=Math.max(y,x),_=n?S.shape[1]:S.shape[2],$=a!=null,T=o!=null,F=l==="leakyrelu",G=l!=null?v2(l,!0):null,q=$||T||F||G!=null,z;if((h===1||f===1)&&_>f9&&q===!1){let B=S,ee=E;n&&(B=ts({inputs:{x:S},backend:r,attrs:{perm:[0,2,1]}}),R.push(B)),s&&(ee=ts({inputs:{x:E},backend:r,attrs:{perm:[0,2,1]}}),R.push(ee));let Q=f!==1,oe=f===1,Y=B;Q&&(Y=be({inputs:{x:B},backend:r,attrs:{shape:[P,_,1]}}),R.push(Y));let ae=f===1?2:1,le=ee;oe&&(le=be({inputs:{x:ee},backend:r,attrs:{shape:[P,1,_]}}),R.push(le));let ye=Yx({inputs:{a:Y,b:le},backend:r});z=k2({inputs:{x:ye},backend:r,attrs:{axis:ae,keepDims:!0}}),R.push(ye)}else{let B=On(e.dtype,t.dtype),ee=new h9(w,k,[P,h,f],n,s,$,G,T,F),Q=[S,E];if(a!=null&&Q.push(a),T&&Q.push(o),F){let oe=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));Q.push(oe),R.push(oe)}z=r.runWebGLProgram(ee,Q,B)}let Z=be({inputs:{x:z},backend:r,attrs:{shape:b}});R.push(z);for(let B of R)r.disposeIntermediateTensorInfo(B);return Z}function Mne(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=s;return Pm({a:r,b:a,transposeA:l,transposeB:u,backend:n,bias:o,preluActivationWeights:i,leakyreluAlpha:p,activation:c})}var zne={kernelName:Ya,backendName:"webgl",kernelFunc:Mne},b7="return abs(x);";function Lne(e){let{inputs:t,backend:n}=e,{x:s}=t;if(n.shouldExecuteOnCPU([s])&&s.dtype!=="complex64"){let a=n.texData.get(s.dataId),o=s9(a.values);return n.makeTensorInfo(s.shape,s.dtype,o)}let r;return X().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new Vi(s.shape,b7):r=new da(s.shape,b7),n.runWebGLProgram(r,[s],s.dtype)}var Bne={kernelName:ol,backendName:"webgl",kernelFunc:Lne},Wne=hr+`
  if (abs(x) > 1.) {
    return NAN;
  }
  return acos(x);
`,Vne=ct({opSnippet:Wne}),Une={kernelName:dc,backendName:"webgl",kernelFunc:Vne},Gne=hr+`
  if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,Hne=ct({opSnippet:Gne}),jne={kernelName:pc,backendName:"webgl",kernelFunc:Hne},v7="return a + b;",qne=Rn({opSnippet:v7,packedOpSnippet:v7,supportsComplex:!0,cpuKernelImpl:ate}),Xne={kernelName:Aa,backendName:"webgl",kernelFunc:qne},Kne=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((r,a)=>`T${a}`);let n=[];this.variableNames.forEach(r=>{n.push(`float v${r} = get${r}AtOutCoords();`)});let s=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
      void main() {
        ${n.join(`
        `)}

        float result = ${s};
        setOutput(result);
      }
    `}},Zne=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((r,a)=>`T${a}`);let n=[];this.variableNames.forEach(r=>{n.push(`vec4 v${r} = get${r}AtOutCoords();`)});let s=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
      void main() {
        ${n.join(`
        `)}

        vec4 result = ${s};
        setOutput(result);
      }
    `}};function om(e){let{inputs:t,backend:n}=e,s=t;if(s.length===1)return Ps({inputs:{x:s[0]},backend:n});if(s.length>X().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let l=Math.floor(s.length/2),u=om({inputs:s.slice(0,l),backend:n}),c=om({inputs:s.slice(l),backend:n});return om({inputs:[u,c],backend:n})}let r=s.map(l=>l.dtype).reduce((l,u)=>On(l,u)),a=s.map(l=>l.shape),i=X().getBool("WEBGL_PACK")?new Zne(s[0].shape,a):new Kne(s[0].shape,a);return n.runWebGLProgram(i,s,r)}var Yne={kernelName:co,backendName:"webgl",kernelFunc:om};function Jne(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=v.parseAxisParam(a,r.shape),u=l,c=C.getAxesPermutation(u,i),p=r;c!=null&&(p=ts({inputs:{x:r},backend:n,attrs:{perm:c}}),u=C.getInnerMostAxes(u.length,i)),C.assertAxesAreInnerMostDims("all",u,i);let[d,h]=C.computeOutAndReduceShapes(p.shape,u),f=v.sizeFromShape(h),m=be({inputs:{x:p},backend:n,attrs:{shape:[-1,f]}}),g=ru(m,m.dtype,"all",n),y;if(o){let x=C.expandShapeToKeepDim(d,l);y=be({inputs:{x:g},backend:n,attrs:{shape:x}})}else y=be({inputs:{x:g},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(p),y}var Qne={kernelName:hc,backendName:"webgl",kernelFunc:Jne};function ese(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=v.parseAxisParam(a,r.shape),u=l,c=C.getAxesPermutation(u,i),p=r;c!=null&&(p=ts({inputs:{x:r},backend:n,attrs:{perm:c}}),u=C.getInnerMostAxes(u.length,i)),C.assertAxesAreInnerMostDims("any",u,i);let[d,h]=C.computeOutAndReduceShapes(p.shape,u),f=v.sizeFromShape(h),m=be({inputs:{x:p},backend:n,attrs:{shape:[-1,f]}}),g=ru(m,m.dtype,"any",n),y;if(o){let x=C.expandShapeToKeepDim(d,l);y=be({inputs:{x:g},backend:n,attrs:{shape:x}})}else y=be({inputs:{x:g},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(p),y}var tse={kernelName:fc,backendName:"webgl",kernelFunc:ese},nse=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:s,batchSize:r,outSize:a}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[r,a];let o=t==="max"?">":"<",i=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = outIdx * ${s};

        int bestIndex = inOffset;
        float bestValue = getA(batch, bestIndex);

        for (int i = 0; i < ${s}; i++) {
          int inIdx = ${i};
          float candidate = getA(batch, inIdx);
          if (candidate ${o} bestValue) {
            bestValue = candidate;
            bestIndex = inIdx;
          }
        }
        setOutput(float(bestIndex));
      }
    `}},sse=class{constructor(e,t,n,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let r=e[e.length-1],a=Math.ceil(r/t);this.outputShape=e.slice(0,-1),a>1&&this.outputShape.push(a),s||this.variableNames.push("bestIndicesA");let o=this.outputShape,i=o.length,l=wt(i),u=Qn("coords",i),c,p;if(a===1){p=i+1;let S=wt(p);c=`
        ${S} sourceLocR = ${S}(${u.join()}, 0);
        ++${u[i-1]};
        ${S} sourceLocG = ${S}(${u.join()}, 0);
        ++${u[i-2]};
        ${S} sourceLocA = ${S}(${u.join()}, 0);
        --${u[i-1]};
        ${S} sourceLocB = ${S}(${u.join()}, 0);
        --${u[i-2]};`}else p=i,c=`
        ${l} sourceLocR = coords;
        ++${u[i-1]};
        ${l} sourceLocG = coords;
        ++${u[i-2]};
        ${l} sourceLocA = coords;
        --${u[i-1]};
        ${l} sourceLocB = coords;
        --${u[i-2]};`;let d=["x","y","z","w","u","v"].slice(0,p),h="."+d[p-1],f=d.map(S=>"int "+S),m=Qn("sourceLocR",p-1).concat("inIdx.r"),g=Qn("sourceLocG",p-1).concat("inIdx.g"),y=Qn("sourceLocB",p-1).concat("inIdx.b"),x=Qn("sourceLocA",p-1).concat("inIdx.a"),A=n==="max"?"greaterThan":"lessThan",b=s?"":`
          inIdx = round(vec4(getBestIndicesAChannel(${m.join()}),
                             getBestIndicesAChannel(${g.join()}),
                             getBestIndicesAChannel(${y.join()}),
                             getBestIndicesAChannel(${x.join()})));`,w=`vec4(
            getAChannel(${m.join()}),
            hasNextCol ? getAChannel(${g.join()}) : 0.,
            hasNextRow ? getAChannel(${y.join()}) : 0.,
            hasNextRow && hasNextCol ? getAChannel(${x.join()}) : 0.)`,k=s?"":`
      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()}));
      }
      ${k}
      void main() {
        ${l} coords = getOutputCoords();
        bool hasNextCol = ${u[i-1]} < ${o[i-1]-1};
        bool hasNextRow = ${u[i-2]} < ${o[i-2]-1};
        ${c}
        ivec4 srcIdx = ivec4(sourceLocR${h}, sourceLocG${h},
          sourceLocB${h}, sourceLocA${h}) * ${t};
        ivec4 inIdx = srcIdx;
        vec4 bestIndex = vec4(inIdx);
        vec4 bestValue = ${w};

        for (int i = 0; i < ${t}; i++) {
          inIdx = srcIdx;
          ${b}
          vec4 candidate = ${w};
          bvec4 nan = isnan(candidate);
          bvec4 replace = bvec4(
            vec4(${A}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));

          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,
                           replace.y  ? candidate.y : bestValue.y,
                           replace.z  ? candidate.z : bestValue.z,
                           replace.w  ? candidate.w : bestValue.w);
          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));
          srcIdx++;
        }
        setOutput(bestIndex);
      }
    `}};function m9(e,t,n,s=null){let r=t.shape[0],a=t.shape[1];s!=null&&(r=s.shape[0],a=s.shape[1]);let o=C.computeOptimalWindowSize(a),i={windowSize:o,inSize:a,batchSize:r,outSize:Math.ceil(a/o)},l=new nse(i,n,s==null),u=[t];s!=null&&u.push(s);let c=e.runWebGLProgram(l,u,"int32");if(c.shape[1]===1)return c;let p=m9(e,t,n,c);return e.disposeIntermediateTensorInfo(c),p}function g9(e,t,n,s=null){let r=s!=null?s.shape:t.shape,a=r[r.length-1],o=C.computeOptimalWindowSize(a),i=new sse(r,o,n,s==null),l=s==null?[t]:[t,s],u=e.runWebGLProgram(i,l,"int32");if(u.shape.length===t.shape.length){let c=g9(e,t,n,u);return e.disposeIntermediateTensorInfo(u),c}return u}function y9(e,t,n,s){let r=[n];if(C.assertAxesAreInnerMostDims("arg"+s.charAt(0).toUpperCase()+s.slice(1),r,t.shape.length),!X().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let a=[],o=e.texData.get(t.dataId),i=o!==null&&o.isPacked,l=t;i&&(l=e.unpackTensor(t),a.push(l));let[u,c]=C.computeOutAndReduceShapes(l.shape,r),p=v.sizeFromShape(c),d=be({inputs:{x:l},backend:e,attrs:{shape:[-1,p]}});a.push(d);let h=m9(e,d,s);a.push(h);let f=be({inputs:{x:h},backend:e,attrs:{shape:u}});return a.forEach(m=>e.disposeIntermediateTensorInfo(m)),f}return g9(e,t,s)}function rse(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=ts({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMax",[o[0]],l.shape.length);let c=y9(n,l,o[0],"max");return u.forEach(p=>n.disposeIntermediateTensorInfo(p)),c}var ase={kernelName:po,backendName:"webgl",kernelFunc:rse};function ose(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=ts({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMin",[o[0]],l.shape.length);let c=y9(n,l,o[0],"min");return u.forEach(p=>n.disposeIntermediateTensorInfo(p)),c}var ise={kernelName:mc,backendName:"webgl",kernelFunc:ose},lse=hr+`
  if (abs(x) > 1.) {
    return NAN;
  }
  return asin(x);
`,use=ct({opSnippet:lse}),cse={kernelName:gc,backendName:"webgl",kernelFunc:use},dse=hr+"return log(x + sqrt(x * x + 1.0));",pse=ct({opSnippet:dse}),hse={kernelName:yc,backendName:"webgl",kernelFunc:pse},fse=hr+`
  return atan(x);
`,mse=ct({opSnippet:fse}),gse={kernelName:Ac,backendName:"webgl",kernelFunc:mse},yse=Ine+`
  return atan(a, b);
`,Ase=`
  vec4 result = atan(a, b);
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  `+Sne+`
  return result;
`,xse=Rn({opSnippet:yse,packedOpSnippet:Ase}),bse={kernelName:bc,backendName:"webgl",kernelFunc:xse},vse=hr+`
  if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernelName:xc,backendName:"webgl",kernelFunc:wse},Dp=class{constructor(e,t,n,s=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,o=e.strideHeight,i=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterHeight,p=e.effectiveFilterWidth,d=e.padInfo.top,h=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,g=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let S=">=";this.userCode=`
        const ivec2 strides = ivec2(${o}, ${i});
        const ivec2 pads = ivec2(${d}, ${h});

        void main() {
          ivec4 coords = getOutputCoords();
          int batch = coords[0];
          int d = coords[3];

          ivec2 xRCCorner = coords.yz * strides - pads;
          int xRCorner = xRCCorner.x;
          int xCCorner = xRCCorner.y;

          // max/min x(?, ?, d) to get y(yR, yC, d).
          // ? = to be determined
          float minMaxValue = 0.0;
          float minMaxValueFound = 0.0;
          int minMaxPosition = 0;
          float avgValue = 0.0;

          for (int wR = 0; wR < ${c};
              wR += ${l}) {
            int xR = xRCorner + wR;

            if (xR < 0 || xR >= ${e.inHeight}) {
              continue;
            }

            for (int wC = 0; wC < ${p};
                wC += ${u}) {
              int xC = xCCorner + wC;

              if (xC < 0 || xC >= ${e.inWidth}) {
                continue;
              }

              float value = getX(batch, xR, xC, d);

              // If a min / max value has already been found, use it. If not,
              // use the current value.
              float currMinMaxValue = mix(
                  value, minMaxValue, minMaxValueFound);
              if (value ${S} currMinMaxValue) {
                minMaxValue = value;
                minMaxValueFound = 1.0;
                minMaxPosition = ${s?r?m:g:`wR * ${p} + wC`};
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;return}let x="max",A=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(A="avgValue / count");let b=Math.floor(a/4)*4,w=a%4,k=`
      if (${f}) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ${x}(values, minMaxValue);
      }
    `;this.userCode=`
      const ivec2 strides = ivec2(${o}, ${i});
      const ivec2 pads = ivec2(${d}, ${h});
      const float initializationValue = ${y};
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float count = 0.0;

      float getValue(int batch, int xR, int xC, int d) {
        if (xC < 0 || xC >= ${e.inWidth}) {
          return initializationValue;
        }
        count += 1.0;
        return getX(batch, xR, xC, d);
      }

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d = coords[3];

        ivec2 xRCCorner = coords.yz * strides - pads;
        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        // max/min x(?, ?, d) to get y(yR, yC, d).
        // ? = to be determined
        vec4 minMaxValue = vec4(${y});
        float avgValue = 0.0;
        count = 0.0;

        for (int wR = 0; wR < ${c};
            wR += ${l}) {
          int xR = xRCorner + wR;

          if (xR < 0 || xR >= ${e.inHeight}) {
            continue;
          }

          for (int wC = 0; wC < ${b}; wC += 4) {
            int xC = xCCorner + wC * ${u};

            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ${u}, d),
              getValue(batch, xR, xC + 2 * ${u}, d),
              getValue(batch, xR, xC + 3 * ${u}, d)
            );

            ${k}
          }

          int xC = xCCorner + ${b};
          if (${w===1}) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              initializationValue,
              initializationValue,
              initializationValue
            );

            ${k}
          } else if (${w===2}) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ${u}, d),
              initializationValue,
              initializationValue
            );

            ${k}
          } else if (${w===3}) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ${u}, d),
              getValue(batch, xR, xC + 2 * ${u}, d),
              initializationValue
            );

            ${k}
          }
        }
        setOutput(${A});
      }
    `}},Jx=class{constructor(e,t,n,s=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,o=e.strideDepth,i=e.strideHeight,l=e.strideWidth,u=e.dilationDepth,c=e.dilationHeight,p=e.dilationWidth,d=e.effectiveFilterDepth,h=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,g=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let x=t==="avg",A="0.0";if(x||(A="-1.0 / 1e-20"),n){let R=">=";this.userCode=`
        const ivec3 strides =
            ivec3(${o}, ${i}, ${l});
        const ivec3 pads = ivec3(${m}, ${g}, ${y});

        void main() {
          ivec5 coords = getOutputCoords();
          int batch = coords.x;
          int ch = coords.u;

          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
          int xDCorner = xCorner.x;
          int xRCorner = xCorner.y;
          int xCCorner = xCorner.z;

          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).
          // ? = to be determined
          float minMaxValue = 0.0;
          float minMaxValueFound = 0.0;
          int minMaxPosition = 0;

          for (int wD = 0; wD < ${d};
              wD += ${u}) {
            int xD = xDCorner + wD;

            if (xD < 0 || xD >= ${e.inDepth}) {
              continue;
            }

            for (int wR = 0; wR < ${h};
                wR += ${c}) {
              int xR = xRCorner + wR;

              if (xR < 0 || xR >= ${e.inHeight}) {
                continue;
              }

              for (int wC = 0; wC < ${f};
                  wC += ${p}) {
                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 ${R} currMinMaxValue) {
                  minMaxValue = value;
                  minMaxValueFound = 1.0;
                  minMaxPosition = ${s?r?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${h} * ${f} +
                      wR * ${f} + wC`};
                }
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;return}let b="max",w=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(w="avgValue / count");let k=Math.floor(a/4)*4,S=a%4,E=`
      if (${x}) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ${b}(values, minMaxValue);
      }
    `;this.userCode=`
      const ivec3 strides =
        ivec3(${o}, ${i}, ${l});
      const ivec3 pads = ivec3(${m}, ${g}, ${y});
      const float initializationValue = ${A};
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float count = 0.0;

      float getValue(int batch, int xD, int xR, int xC, int ch) {
        if (xC < 0 || xC >= ${e.inWidth}) {
          return initializationValue;
        }
        count += 1.0;
        return getX(batch, xD, xR, xC, ch);
      }

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int ch = coords.u;

        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
        int xDCorner = xCorner.x;
        int xRCorner = xCorner.y;
        int xCCorner = xCorner.z;

        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
        // ? = to be determined
        vec4 minMaxValue = vec4(${A});
        float avgValue = 0.0;
        count = 0.0;

        for (int wD = 0; wD < ${d};
            wD += ${u}) {
          int xD = xDCorner + wD;

          if (xD < 0 || xD >= ${e.inDepth}) {
            continue;
          }

          for (int wR = 0; wR < ${h};
            wR += ${c}) {
            int xR = xRCorner + wR;

            if (xR < 0 || xR >= ${e.inHeight}) {
              continue;
            }

            for (int wC = 0; wC < ${k}; wC += 4) {
              int xC = xCCorner + wC * ${p};

              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ${p}, ch),
                getValue(batch, xD, xR, xC + 2 * ${p}, ch),
                getValue(batch, xD, xR, xC + 3 * ${p}, ch)
              );

              ${E}
            }

            int xC = xCCorner + ${k};
            if (${S===1}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                initializationValue,
                initializationValue,
                initializationValue
              );

              ${E}
            } else if (${S===2}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ${p}, ch),
                initializationValue,
                initializationValue
              );

              ${E}
            } else if (${S===3}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ${p}, ch),
                getValue(batch, xD, xR, xC + 2 * ${p}, ch),
                initializationValue
              );

              ${E}
            }
          }
          setOutput(${w});
        }
      }
    `}};function Ise(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;td(r,"avgPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;v.assert(C.eitherStridesOrDilationsAreOne(o,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=C.computePool2DInfo(r.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Ps({inputs:{x:r},backend:n});let p=new Dp(c,"avg",!1);return n.runWebGLProgram(p,[r],"float32")}var Sse={kernelName:ho,backendName:"webgl",kernelFunc:Ise};function Cse(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l,dataFormat:u}=s,c=[1,1,1],p=C.computePool3DInfo(r.shape,a,o,c,i,l,u),d=new Jx(p,"avg",!1);return n.runWebGLProgram(d,[r],"float32")}var Tse={kernelName:Mp,backendName:"webgl",kernelFunc:Cse},Nse=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,s=e.strideHeight,r=e.strideWidth,a=e.dilationHeight,o=e.dilationWidth,i=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=i-1-e.padInfo.top,c=l-1-e.padInfo.left,p=1/(t*n);this.userCode=`
      const ivec2 pads = ivec2(${u}, ${c});
      const float avgMultiplier = float(${p});

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];

        ivec2 dyRCCorner = coords.yz - pads;
        int dyRCorner = dyRCCorner.x;
        int dyCCorner = dyRCCorner.y;

        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${i};
            wR += ${a}) {
          float dyR = float(dyRCorner + wR) / ${s}.0;

          if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          for (int wC = 0; wC < ${l};
            wC+= ${o}) {
            float dyC = float(dyCCorner + wC) / ${r}.0;

            if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            float dyValue = getDy(b, idyR, idyC, d);

            dotProd += dyValue * avgMultiplier;
          }
        }
        setOutput(dotProd);
      }
    `}},Ese=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,s=e.filterWidth,r=e.strideDepth,a=e.strideHeight,o=e.strideWidth,i=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,p=e.effectiveFilterHeight,d=e.effectiveFilterWidth,h=c-1-e.padInfo.front,f=p-1-e.padInfo.top,m=d-1-e.padInfo.left,g=1/(t*n*s);this.userCode=`
      const ivec3 pads = ivec3(${h}, ${f}, ${m});
      const float avgMultiplier = float(${g});

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int ch = coords.u;

        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
        int dyDCorner = dyCorner.x;
        int dyRCorner = dyCorner.y;
        int dyCCorner = dyCorner.z;

        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get
        // dx(xD, xR, xC, ch).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;

        for (int wD = 0; wD < ${c};
            wD += ${i}) {
          float dyD = float(dyDCorner + wD) / ${r}.0;

          if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
            continue;
          }
          int idyD = int(dyD);

          for (int wR = 0; wR < ${p};
              wR += ${l}) {
            float dyR = float(dyRCorner + wR) / ${a}.0;

            if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
                fract(dyR) > 0.0) {
              continue;
            }
            int idyR = int(dyR);

            for (int wC = 0; wC < ${d};
                wC += ${u}) {
              float dyC = float(dyCCorner + wC) / ${o}.0;

              if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
                  fract(dyC) > 0.0) {
                continue;
              }
              int idyC = int(dyC);

              float dyValue = getDy(batch, idyD, idyR, idyC, ch);

              dotProd += dyValue * avgMultiplier;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function Rse(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=s,p=[1,1,1],d=C.computePool3DInfo(o.shape,i,l,p,u,c),h=new Ese(d);return n.runWebGLProgram(h,[r],o.dtype)}var _se={kernelName:Gm,backendName:"webgl",kernelFunc:Rse};function Dse(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a;td([r,a],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=s,c=C.computePool2DInfo(o.shape,i,l,1,u),p=new Nse(c);return n.runWebGLProgram(p,[r],o.dtype)}var $se={kernelName:Um,backendName:"webgl",kernelFunc:Dse};function Pse(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;return Pm({a:r,b:a,transposeA:o,transposeB:i,backend:n})}var Fse={kernelName:fo,backendName:"webgl",kernelFunc:Pse},Ose=class{constructor(e,t,n,s,r,a){this.outputShape=[],this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,n);let o="0.0";s!=null&&(C.assertAndGetBroadcastShape(e,s),this.variableNames.push("offset"),o="getOffsetAtOutCoords()");let i="1.0";r!=null&&(C.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),i="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
      void main() {
        float x = getXAtOutCoords();
        float mean = getMeanAtOutCoords();
        float variance = getVarianceAtOutCoords();
        float offset = ${o};
        float scale = ${i};
        float inv = scale * inversesqrt(variance + float(${a}));
        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
      }
    `}},Mse=class{constructor(e,t,n,s,r,a){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,n);let o="vec4(0.0)";s!=null&&(C.assertAndGetBroadcastShape(e,s),this.variableNames.push("offset"),o="getOffsetAtOutCoords()");let i="vec4(1.0)";r!=null&&(C.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),i="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
      void main() {
        vec4 offset = ${o};
        vec4 scale = ${i};

        vec4 x = getXAtOutCoords();
        vec4 mean = getMeanAtOutCoords();
        vec4 variance = getVarianceAtOutCoords();

        vec4 inv = scale * inversesqrt(variance + vec4(${a}));

        setOutput((x - mean) * inv + offset);
      }
    `}},zse=({inputs:e,backend:t,attrs:n})=>{let{x:s,mean:r,variance:a,offset:o,scale:i}=e;v.assert(r.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(o==null||r.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(i==null||r.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let u=[s,r,a],c=null;o!=null&&(c=o.shape,u.push(o));let p=null;i!=null&&(p=i.shape,u.push(i));let d=X().getBool("WEBGL_PACK_NORMALIZATION")?new Mse(s.shape,r.shape,a.shape,c,p,l):new Ose(s.shape,r.shape,a.shape,c,p,l);return t.runWebGLProgram(d,u,u[0].dtype)},Lse={kernelName:No,backendName:"webgl",kernelFunc:zse},Bse=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=wt(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let n=Wse(this.rank),s,r=e.map((a,o)=>`sourceLoc.${ay[o]} = start[${o}] + coords.${ay[o]};`);s=`
        ${t} sourceLoc;
        ${t} coords = getOutputCoords();
        ${r.join(`
`)}
      `,this.userCode=`
      void main() {
        ${s}
        setOutput(getSource(${n}));
      }
    `}},ay=["x","y","z","w","u","v"];function Wse(e){if(e===1)return"sourceLoc";if(e<=6)return ay.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var Vse=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=wt(this.rank),n=Qn("coords",this.rank),s=Qn("sourceLoc",this.rank),r=this.rank===1?"sourceLoc":`vec2(${s.slice(-2).join()})`,a=`getChannel(getSource(${s.join()}), ${r})`,o=`
      result.x = ${a};
      if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
        ++${s[this.rank-1]};
        result.y = ${a};
        --${s[this.rank-1]};
      }
    `,i=this.rank===1?"":`
      --${n[this.rank-1]};
      if (++${n[this.rank-2]} < ${e[this.rank-2]}) {
        ++${s[this.rank-2]};
        result.z = ${a};
        if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
          ++${s[this.rank-1]};
          result.w = ${a};
        }
      }
    `,l=this.rank<=4?`sourceLoc = coords +
            ${t}(${e.map((u,c)=>`start[${c}]`).join()});`:e.map((u,c)=>`${s[c]} = ${n[c]} + start[${c}];`).join(`
`);this.userCode=`
      void main() {
        ${t} coords = getOutputCoords();
        ${t} sourceLoc;
        ${l}
        vec4 result = vec4(0.);
        ${o}
        ${i}
        setOutput(result);
      }
    `}};function Use(e,t,n,s){let r=s.texData.get(e.dataId),a=s.makeTensorInfo(n,e.dtype),o=s.texData.get(a.dataId);Object.assign(o,r),o.refCount=1,o.shape=n,o.dtype=e.dtype;let i=Ut.computeFlatOffset(t,v.computeStrides(e.shape));r.slice&&(i+=r.slice.flatOffset),o.slice={flatOffset:i,origDataId:r.slice&&r.slice.origDataId||e.dataId};let l=s.dataRefCount.get(o.slice.origDataId)||1;return s.dataRefCount.set(o.slice.origDataId,l+1),a}function ld(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,size:o}=s,[i,l]=Ut.parseSliceParams(r,a,o);if(Ut.assertParamsValid(r,i,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,r.dtype,[]);if(n.shouldExecuteOnCPU([r])||r.dtype==="string"){let p=n.texData.get(r.dataId),d=Dte(p.values,i,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,d)}let{isPacked:u}=n.texData.get(r.dataId),c=Ut.isSliceContinous(r.shape,i,l);if(u||!c){let p=X().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Vse(l):new Bse(l),d=[i];return n.runWebGLProgram(p,[r],r.dtype,d)}return n.uploadToGPU(r.dataId),Use(r,i,l,n)}var Gse={kernelName:Fl,backendName:"webgl",kernelFunc:ld},Hse=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s;v.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let i=a.reduce((x,A)=>x*A),l=C.getReshaped(r.shape,a,i),u=C.getPermuted(l.length,a.length),c=C.getReshapedPermuted(r.shape,a,i),p=C.getSliceBeginCoords(o,a.length),d=C.getSliceSize(c,o,a.length),h=[],f=be({inputs:{x:r},backend:n,attrs:{shape:l}}),m=ts({inputs:{x:f},backend:n,attrs:{perm:u}}),g=be({inputs:{x:m},backend:n,attrs:{shape:c}}),y=ld({inputs:{x:g},backend:n,attrs:{begin:p,size:d}});return h.push(f),h.push(m),h.push(g),h.forEach(x=>n.disposeIntermediateTensorInfo(x)),y},jse={kernelName:il,backendName:"webgl",kernelFunc:Hse};function qse(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o}=s,i=n.readSync(r.dataId),l=n.readSync(a.dataId),u=n9(i,l,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,u)}var Xse={kernelName:Hm,backendName:"webgl",kernelFunc:qse};function Kse(e){let{inputs:t,backend:n}=e,{s0:s,s1:r}=t,a=n.readSync(s.dataId),o=n.readSync(r.dataId),i=C.assertAndGetBroadcastShape(Array.from(a),Array.from(o));return n.makeTensorInfo([i.length],"int32",Int32Array.from(i))}var Zse={kernelName:jm,backendName:"webgl",kernelFunc:Kse},Yse="return float(a != b);",A9=Rn({opSnippet:Yse,cpuKernelImpl:Cte,dtype:"bool"}),Jse={kernelName:Il,backendName:"webgl",kernelFunc:A9};function Mh(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.texData.get(s.dataId);return Ps({inputs:{x:r.complexTensorInfos.real},backend:n})}var Qse={kernelName:jp,backendName:"webgl",kernelFunc:Mh},ere="return float(int(x));";function tre(e,t){let n=new da(e.shape,ere),s=t.runWebGLProgram(n,[e],"int32");return{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}function oy(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dtype:a}=s;if(a==="complex64"){if(r.dtype==="complex64")return Ps({inputs:{x:r},backend:n});let o=Wt(r.shape),i=oy({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=di({inputs:{real:i,imag:o},backend:n});return o.dispose(),n.disposeIntermediateTensorInfo(i),l}if(r.dtype==="complex64"){let o=Mh({inputs:{input:r},backend:n}),i=oy({inputs:{x:o},backend:n,attrs:{dtype:a}});return n.disposeIntermediateTensorInfo(o),i}if(!v.hasEncodingLoss(r.dtype,a)){let o=Ps({inputs:{x:r},backend:n});return{dataId:o.dataId,shape:o.shape,dtype:a}}if(a==="int32")return tre(r,n);if(a==="bool"){let o=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),l=A9({inputs:{a:r,b:o},backend:n});return n.disposeIntermediateTensorInfo(o),l}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${a}`)}var nre={kernelName:mo,backendName:"webgl",kernelFunc:oy},w7="return ceil(x);",sre=ct({opSnippet:w7,packedOpSnippet:w7,cpuKernelImpl:ite}),rre={kernelName:go,backendName:"webgl",kernelFunc:sre},are=class{constructor(e){this.variableNames=["A"],this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=`

      void main() {
        float value = getAAtOutCoords();
        if (isnan(value)) {
          setOutput(value);
          return;
        }

        setOutput(clamp(value, minVal, maxVal));
      }
    `}},ore=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=`
      void main() {
        vec4 value = getAAtOutCoords();

        if (any(isnan(value))) {
          setOutput(value);
          return;
        }

        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
      }
    `}};function ire(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{clipValueMin:a,clipValueMax:o}=s,i;X().getBool("WEBGL_PACK_CLIP")?i=new ore(r.shape):i=new are(r.shape);let l=[[a],[o]];return n.runWebGLProgram(i,[r],r.dtype,l)}var lre={kernelName:xa,backendName:"webgl",kernelFunc:ire},ure=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
      void main() {
        float re = abs(getRealAtOutCoords());
        float im = abs(getImagAtOutCoords());
        float mx = max(re, im);

        // sadly the length function in glsl is not underflow-safe
        // (at least not on Intel GPUs). So the safe solution is
        // to ensure underflow-safety in all cases.
        setOutput(
          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
        );
      }
    `}};function k7(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function cre(e){let{inputs:t,backend:n}=e,{x:s}=t,r=n.texData.get(s.dataId),a=new ure(s.shape),o=[k7(s,r.complexTensorInfos.real),k7(s,r.complexTensorInfos.imag)];return n.runWebGLProgram(a,o,o[0].dtype)}var dre={kernelName:Lp,backendName:"webgl",kernelFunc:cre},pre=class{constructor(e){this.outputShape=[],this.outputShape=C.computeOutShape(e,1),this.variableNames=e.map((a,o)=>`T${o}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let a=1;a<t.length;a++)t[a]=t[a-1]+e[a][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let a=1;a<t.length;a++){let o=t[a-1];n.push(`else if (yC < ${t[a]}) setOutput(getT${a}(yR, yC-${o}));`)}let s=t.length,r=t[t.length-1];n.push(`else setOutput(getT${s}(yR, yC-${r}));`),this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int yR = coords.x;
        int yC = coords.y;

        ${n.join(`
        `)}
      }
    `}},hre=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=C.computeOutShape(e,t);let n=this.outputShape,s=n.length,r=wt(s),a=Qn("coords",s),o=["x","y","z","w","u","v"].slice(0,s);this.variableNames=e.map((f,m)=>`T${m}`);let i=new Array(e.length-1);i[0]=e[0][t];for(let f=1;f<i.length;f++)i[f]=i[f-1]+e[f][t];let l=o[t],u=o.slice(-2),c=o.join(),p=`if (${l} < ${i[0]}) {
        return getChannel(
            getT0(${c}), vec2(${u.join()}));
        }`;for(let f=1;f<i.length;f++){let m=i[f-1];p+=`
        if (${l} < ${i[f]}  && ${l} >= ${i[f-1]}) {
          return getChannel(
            getT${f}(${Zf(o,l,m)}),
            vec2(${Zf(u,l,m)}));
        }`}let d=i.length,h=i[i.length-1];p+=`
        return getChannel(
          getT${d}(${Zf(o,l,h)}),
          vec2(${Zf(u,l,h)}));`,this.userCode=`
      float getValue(${o.map(f=>"int "+f)}) {
        ${p}
      }

      void main() {
        ${r} coords = getOutputCoords();
        vec4 result = vec4(getValue(${a}), 0., 0., 0.);

        ${a[s-1]} = ${a[s-1]} + 1;
        if (${a[s-1]} < ${n[s-1]}) {
          result.g = getValue(${a});
        }

        ${a[s-2]} = ${a[s-2]} + 1;
        if (${a[s-2]} < ${n[s-2]}) {
          result.a = getValue(${a});
        }

        ${a[s-1]} = ${a[s-1]} - 1;
        if (${a[s-2]} < ${n[s-2]} &&
            ${a[s-1]} < ${n[s-1]}) {
          result.b = getValue(${a});
        }
        setOutput(result);
      }
    `}};function Zf(e,t,n){let s=e.indexOf(t);return e.map((a,o)=>o===s?`${a} - ${n}`:a).join()}function I2(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.texData.get(s.dataId);return Ps({inputs:{x:r.complexTensorInfos.imag},backend:n})}var fre={kernelName:Up,backendName:"webgl",kernelFunc:I2};function cp(e,t,n){let s=e[0].dtype;if(s==="complex64"){let p=e.map(g=>Mh({inputs:{input:g},backend:n})),d=e.map(g=>I2({inputs:{input:g},backend:n})),h=cp(p,t,n),f=cp(d,t,n),m=di({inputs:{real:h,imag:f},backend:n});return p.forEach(g=>n.disposeIntermediateTensorInfo(g)),d.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),m}let r=n.shouldExecuteOnCPU(e);if(s==="string"&&(r=!0),r){let p=e.map(x=>{let A=v.sizeFromShape(x.shape.slice(t));return be({inputs:{x},backend:n,attrs:{shape:[-1,A]}})}),d=p.map(x=>({vals:n.readSync(x.dataId),shape:x.shape})),h=C.computeOutShape(p.map(x=>x.shape),1),f=p[0].shape[0]===1,m=lte(d,h,s,f),g=C.computeOutShape(e.map(x=>x.shape),t),y=n.makeTensorInfo(g,s,m);return p.forEach(x=>n.disposeIntermediateTensorInfo(x)),y}let a=X().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(e.length>a){let p=[];for(let h=0;h<e.length;h+=a){let f=e.slice(h,h+a);p.push(cp(f,t,n))}let d=cp(p,t,n);for(let h of p)n.disposeIntermediateTensorInfo(h);return d}if(X().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let p=new hre(e.map(d=>d.shape),t);return n.runWebGLProgram(p,e,s)}let{tensors2D:o,outShape:i}=mre(e,t,n),l=new pre(o.map(p=>p.shape)),u=n.runWebGLProgram(l,o,s);o.forEach(p=>n.disposeIntermediateTensorInfo(p));let c=be({inputs:{x:u},attrs:{shape:i},backend:n});return n.disposeIntermediateTensorInfo(u),c}function mre(e,t,n){let s=C.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>be({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:s}}function x9(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s,a=v.parseAxisParam(r,t[0].shape)[0],o=C.computeOutShape(t.map(u=>u.shape),a);if(v.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let i=t.filter(u=>v.sizeFromShape(u.shape)>0);if(i.length===1)return Ps({inputs:{x:i[0]},backend:n});let l=i.map(u=>u.shape);return C.assertParamsConsistent(l,a),cp(i,a,n)}var gre={kernelName:ll,backendName:"webgl",kernelFunc:x9},b9=class{constructor(e,t=!1,n=null,s=!1,r=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let a=e.padInfo.top,o=e.padInfo.left,i=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,c=e.dilationWidth,p=e.filterHeight,d=e.filterWidth,h=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",g=m?1:2,y=m?2:3,x=m?3:1,A="",b="";n&&(s?A=`float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ${n}
        }`:r?A=`float activation(float a) {
          float b = getLeakyreluAlphaAtOutCoords();
          ${n}
        }`:A=`
          float activation(float x) {
            ${n}
          }
        `,b="result = activation(result);");let w=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${A}

      const ivec2 strides = ivec2(${i}, ${l});
      const ivec2 pads = ivec2(${a}, ${o});

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d2 = coords[${x}];

        ivec2 xRCCorner =
            ivec2(coords[${g}], coords[${y}]) * strides - pads;
        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${p}; wR++) {
          int xR = xRCorner + wR * ${u};

          if (xR < 0 || xR >= ${e.inHeight}) {
            continue;
          }

          for (int wC = 0; wC < ${d}; wC++) {
            int xC = xCCorner + wC * ${c};

            if (xC < 0 || xC >= ${e.inWidth}) {
              continue;
            }

            for (int d1 = 0; d1 < ${h}; d1 += 4) {
              vec4 wValues = vec4(
                getW(wR, wC, d1, d2),
                getW(wR, wC, d1 + 1, d2),
                getW(wR, wC, d1 + 2, d2),
                getW(wR, wC, d1 + 3, d2)
              );

              if (${m}) {
                vec4 xValues = vec4(
                  getX(batch, xR, xC, d1),
                  getX(batch, xR, xC, d1 + 1),
                  getX(batch, xR, xC, d1 + 2),
                  getX(batch, xR, xC, d1 + 3)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec4 xValues = vec4(
                  getX(batch, d1, xR, xC),
                  getX(batch, d1 + 1, xR, xC),
                  getX(batch, d1 + 2, xR, xC),
                  getX(batch, d1 + 3, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }
            }

            if (${f===1}) {

              if (${m}) {
                dotProd +=
                    getX(batch, xR, xC, ${h}) *
                    getW(wR, wC, ${h}, d2);
              } else {
                dotProd +=
                    getX(batch, ${h}, xR, xC) *
                    getW(wR, wC, ${h}, d2);
              }

            } else if (${f===2}) {
              vec2 wValues = vec2(
                getW(wR, wC, ${h}, d2),
                getW(wR, wC, ${h} + 1, d2)
              );

              if (${m}) {
                vec2 xValues = vec2(
                  getX(batch, xR, xC, ${h}),
                  getX(batch, xR, xC, ${h} + 1)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec2 xValues = vec2(
                  getX(batch, ${h}, xR, xC),
                  getX(batch, ${h} + 1, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }

            } else if (${f===3}) {
              vec3 wValues = vec3(
                getW(wR, wC, ${h}, d2),
                getW(wR, wC, ${h} + 1, d2),
                getW(wR, wC, ${h} + 2, d2)
              );

              if (${m}) {
                vec3 xValues = vec3(
                  getX(batch, xR, xC, ${h}),
                  getX(batch, xR, xC, ${h} + 1),
                  getX(batch, xR, xC, ${h} + 2)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec3 xValues = vec3(
                  getX(batch, ${h}, xR, xC),
                  getX(batch, ${h} + 1, xR, xC),
                  getX(batch, ${h} + 2, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }

            }
          }
        }

        float result = dotProd;
        ${w}
        ${b}
        setOutput(result);
      }
    `}},yre=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,s=e.padInfo.left,r=e.strideDepth,a=e.strideHeight,o=e.strideWidth,i=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.filterDepth,p=e.filterHeight,d=e.filterWidth,h=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
      const ivec3 strides = ivec3(${r}, ${a}, ${o});
      const ivec3 pads = ivec3(${t}, ${n}, ${s});

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int d2 = coords.u;

        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
        int xFCorner = xFRCCorner.x;
        int xRCorner = xFRCCorner.y;
        int xCCorner = xFRCCorner.z;

        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get
        // y(yF, yR, yC, d2). ? = to be determined. : = across all
        // values in that axis.
        float dotProd = 0.0;
        for (int wF = 0; wF < ${c}; wF++) {
          int xF = xFCorner + wF * ${i};

          if (xF < 0 || xF >= ${e.inDepth}) {
            continue;
          }

          for (int wR = 0; wR < ${p}; wR++) {
            int xR = xRCorner + wR * ${l};

            if (xR < 0 || xR >= ${e.inHeight}) {
              continue;
            }

            for (int wC = 0; wC < ${d}; wC++) {
              int xC = xCCorner + wC * ${u};

              if (xC < 0 || xC >= ${e.inWidth}) {
                continue;
              }

              for (int d1 = 0; d1 < ${h}; d1 += 4) {
                vec4 xValues = vec4(
                  getX(batch, xF, xR, xC, d1),
                  getX(batch, xF, xR, xC, d1 + 1),
                  getX(batch, xF, xR, xC, d1 + 2),
                  getX(batch, xF, xR, xC, d1 + 3)
                );
                vec4 wValues = vec4(
                  getW(wF, wR, wC, d1, d2),
                  getW(wF, wR, wC, d1 + 1, d2),
                  getW(wF, wR, wC, d1 + 2, d2),
                  getW(wF, wR, wC, d1 + 3, d2)
                );

                dotProd += dot(xValues, wValues);
              }

              if (${f===1}) {
                dotProd +=
                  getX(batch, xF, xR, xC, ${h}) *
                  getW(wF, wR, wC, ${h}, d2);
              } else if (${f===2}) {
                vec2 xValues = vec2(
                  getX(batch, xF, xR, xC, ${h}),
                  getX(batch, xF, xR, xC, ${h} + 1)
                );
                vec2 wValues = vec2(
                  getW(wF, wR, wC, ${h}, d2),
                  getW(wF, wR, wC, ${h} + 1, d2)
                );
                dotProd += dot(xValues, wValues);
              } else if (${f===3}) {
                vec3 xValues = vec3(
                  getX(batch, xF, xR, xC, ${h}),
                  getX(batch, xF, xR, xC, ${h} + 1),
                  getX(batch, xF, xR, xC, ${h} + 2)
                );
                vec3 wValues = vec3(
                  getW(wF, wR, wC, ${h}, d2),
                  getW(wF, wR, wC, ${h} + 1, d2),
                  getW(wF, wR, wC, ${h} + 2, d2)
                );
                dotProd += dot(xValues, wValues);
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}},Are=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec4"},{name:"pad",type:"ivec2"},{name:"stride",type:"ivec2"},{name:"dilation",type:"ivec2"},{name:"inChannels",type:"int"},{name:"itemsPerBlockRow",type:"int"},{name:"outWidth",type:"int"}],this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length);let{dataFormat:n}=t,s=as(),r=n==="channelsLast",a=r?1:2,o=r?2:3,i=this.enableShapeUniforms?"if(blockIndex < outShape[2] && pos < outShape[1]) {":`if(blockIndex < ${e[2]} && pos < ${e[1]}) {`,l="";for(let u=0;u<=1;u++)for(let c=0;c<=1;c++)l+=`
          blockIndex = rc.z + ${c};
          pos = rc.y + ${u};

          ${i}
            offsetY = int(blockIndex / outWidth) * stride[0] - pad[0];
            d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow);

            if(d0 < inputShape[${a}] && d0 >= 0) {
              // Use custom imod instead mod. On Intel GPU, mod may generate
              // unexpected value.
              // https://github.com/tensorflow/tfjs/issues/5447
              offsetX = imod(blockIndex, outWidth) * stride[1] - pad[1];
              d1 = offsetX + dilation[1] * (imod(pos, itemsPerBlockRow) /
                  inChannels);

              if(d1 < inputShape[${o}] && d1 >= 0) {

                ch = imod(pos, inChannels);

                if (${r}) {
                  innerDims = vec2(d1, ch);
                  result[${u*2+c}] = getChannel(
                    getA(rc.x, d0, int(innerDims.x),
                    int(innerDims.y)), innerDims);
                } else {
                  innerDims = vec2(d0, d1);
                  result[${u*2+c}] = getChannel(
                    getA(rc.x, ch, int(innerDims.x),
                    int(innerDims.y)), innerDims);
                }
              }
            }
          }
        `;this.userCode=`
      void main() {
        ivec3 rc = getOutputCoords();

        vec4 result = vec4(0);

        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
        vec2 innerDims;

        ${l}

        ${s.output} = result;
      }
    `}};function Fm(e,t){let n=e.length;return n>=3?t?[...e.slice(0,-3),e[n-3]*e[n-2],e[n-1]]:[...e.slice(0,-3),e[n-3],e[n-2]*e[n-1]]:!t&&n===1&&e[0]>1?[e[0],1]:null}function v9({x:e,filter:t,convInfo:n,backend:s,bias:r=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let l=e.shape,u=s.texData.get(e.dataId),c=n.inChannels,p=l[0]*l[1]*l[2],d=n.outChannels,h=n.dataFormat==="channelsLast",f=!1,m=!1,g,y=[];if(a!=null){let b=Fm(a.shape,h);b!=null&&(a=be({inputs:{x:a},backend:s,attrs:{shape:b}}),y.push(a))}if(r!=null){let b=Fm(r.shape,h);b!=null&&(r=be({inputs:{x:r},backend:s,attrs:{shape:b}}),y.push(r))}if(!((p===1||d===1)&&c>f9)&&u.isPacked&&h&&u.texture!=null&&l[2]%2!==0&&v.arraysEqual(u.shape.slice(-3),l.slice(-3))){let b=l[0]*l[1]*(l[2]+1),w={dataId:e.dataId,shape:[1,b,n.inChannels],dtype:e.dtype},k=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,v.assert(_p(u.shape,w.shape),()=>`packed reshape ${u.shape} to ${w.shape} isn't free`);let S=be({inputs:{x:t},backend:s,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(S);let E=Pm({a:w,b:S,backend:s,transposeA:f,transposeB:m,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o}),R=s.texData.get(E.dataId);v.assert(R.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=k,R.shape=n.outShape,g=Ps({inputs:{x:E},backend:s}),g.shape=n.outShape,y.push(E)}else{let b=n.outHeight*n.outWidth,w=be({inputs:{x:e},backend:s,attrs:{shape:h?[n.batchSize,b,n.inChannels]:[n.batchSize,n.inChannels,b]}}),k=be({inputs:{x:t},backend:s,attrs:{shape:[1,n.inChannels,n.outChannels]}}),S=Pm({a:h?w:k,b:h?k:w,transposeA:!h,transposeB:m,backend:s,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o});g=be({inputs:{x:S},backend:s,attrs:{shape:n.outShape}}),y.push(w),y.push(k),y.push(S)}for(let b of y)s.disposeIntermediateTensorInfo(b);return g}function w9({x:e,filter:t,convInfo:n,backend:s,bias:r=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let{filterWidth:l,filterHeight:u,inChannels:c,outWidth:p,outHeight:d,dataFormat:h}=n,f=h==="channelsLast",m=l*u*c,g=d*p,y=[n.batchSize,m,g],x=!0,A=!1,b=[];if(a!=null){let Z=Fm(a.shape,f);Z!=null&&(a=be({inputs:{x:a},backend:s,attrs:{shape:Z}}),b.push(a))}if(r!=null){let Z=Fm(r.shape,f);Z!=null&&(r=be({inputs:{x:r},backend:s,attrs:{shape:Z}}),b.push(r))}let w=be({inputs:{x:t},backend:s,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});b.push(w);let k=new Are(y,n),S=[e.shape,[n.padInfo.top,n.padInfo.left],[n.strideHeight,n.strideWidth],[n.dilationHeight,n.dilationWidth],[n.inChannels],[n.filterWidth*n.inChannels],[n.outWidth]],E=s.runWebGLProgram(k,[e],"float32",S),R=be({inputs:{x:E},backend:s,attrs:{shape:y}});b.push(E),b.push(R);let P=r!=null,_=a!=null,$=i==="leakyrelu",T=i?v2(i,!0):null,F=new h9(f?R.shape:w.shape,f?w.shape:R.shape,f?[n.batchSize,g,n.outChannels]:[n.batchSize,n.outChannels,g],x,A,P,T,_,$),G=f?[R,w]:[w,R];if(r&&G.push(r),_&&G.push(a),$){let Z=s.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));G.push(Z),b.push(Z)}let q=s.runWebGLProgram(F,G,"float32"),z=be({inputs:{x:q},backend:s,attrs:{shape:n.outShape}});b.push(q);for(let Z of b)s.disposeIntermediateTensorInfo(Z);return z}function xre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=s,p=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,a.shape,o,u,i,c,!1,p),h;if(d.filterHeight===1&&d.filterWidth===1&&d.dilationHeight===1&&d.dilationWidth===1&&d.strideHeight===1&&d.strideWidth===1&&(d.padInfo.type==="SAME"||d.padInfo.type==="VALID"))h=v9({x:r,filter:a,convInfo:d,backend:n});else if(X().getBool("WEBGL_CONV_IM2COL"))h=w9({x:r,filter:a,convInfo:d,backend:n});else{let m=new b9(d);h=n.runWebGLProgram(m,[r,a],"float32")}let f=be({inputs:{x:h},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(h),f}var bre={kernelName:yo,backendName:"webgl",kernelFunc:xre},vre=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,s=e.padInfo.top,r=e.padInfo.left,a=e.dataFormat==="channelsLast";this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int wR = coords.x;
        int wC = coords.y;
        int d1 = coords.z;
        int d2 = coords.w;

        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;

        for (int b = 0; b < ${e.batchSize}; b++) {
          for (int yR = 0; yR < ${e.outHeight}; yR++) {
            int xR = wR + yR * ${t} - ${s};

            if (xR < 0 || xR >= ${e.inHeight}) {
              continue;
            }

            for (int yC = 0; yC < ${e.outWidth}; yC++) {
              int xC = wC + yC * ${n} - ${r};

              if (xC < 0 || xC >= ${e.inWidth}) {
                continue;
              }

              if (${a}) {
                float dyValue = getDy(b, yR, yC, d2);
                float xValue = getX(b, xR, xC, d1);
                dotProd += (xValue * dyValue);
              } else {
                float dyValue = getDy(b, d2, yR, yC);
                float xValue = getX(b, d1, xR, xC);
                dotProd += (xValue * dyValue);
              }

            }
          }
        }
        setOutput(dotProd);
      }
    `}},wre=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,s=e.strideHeight,r=e.strideWidth,a=e.dataFormat==="channelsLast",o=t-1-e.padInfo.top,i=n-1-e.padInfo.left,l=a?1:2,u=a?2:3,c=a?3:1;this.userCode=`
      const ivec2 pads = ivec2(${o}, ${i});

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d1 = coords[${c}];

        ivec2 dyCorner = ivec2(coords[${l}], coords[${u}]) - pads;
        int dyRCorner = dyCorner.x;
        int dyCCorner = dyCorner.y;

        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${t}; wR++) {
          float dyR = float(dyRCorner + wR) / ${s}.0;

          if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          int wRPerm = ${t} - 1 - wR;

          for (int wC = 0; wC < ${n}; wC++) {
            float dyC = float(dyCCorner + wC) / ${r}.0;

            if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            int wCPerm = ${n} - 1 - wC;

            for (int d2 = 0; d2 < ${e.outChannels}; d2++) {

              if (${a}) {
                float xValue = getDy(batch, idyR, idyC, d2);
                float wValue = getW(wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              } else {
                float xValue = getDy(batch, d2, idyR, idyC);
                float wValue = getW(wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              }

            }
          }
        }
        setOutput(dotProd);
      }
    `}},kre=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,s=e.strideWidth,r=e.padInfo.front,a=e.padInfo.top,o=e.padInfo.left;this.userCode=`
      void main() {
        ivec5 coords = getOutputCoords();
        int wF = coords.x;
        int wR = coords.y;
        int wC = coords.z;
        int d1 = coords.w;
        int d2 = coords.u;

        float dotProd = 0.0;

        for (int b = 0; b < ${e.batchSize}; b++) {
          for (int yF = 0; yF < ${e.outDepth}; yF++) {
            int xF = wF + yF * ${t} - ${r};

            if (xF < 0 || xF >= ${e.inDepth}) {
              continue;
            }

            for (int yR = 0; yR < ${e.outHeight}; yR++) {
              int xR = wR + yR * ${n} - ${a};

              if (xR < 0 || xR >= ${e.inHeight}) {
                continue;
              }

              for (int yC = 0; yC < ${e.outWidth}; yC++) {
                int xC = wC + yC * ${s} - ${o};

                if (xC < 0 || xC >= ${e.inWidth}) {
                  continue;
                }

                float dyValue = getDy(b, yF, yR, yC, d2);
                float xValue = getX(b, xF, xR, xC, d1);
                dotProd += (xValue * dyValue);
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}},Ire=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,s=e.filterWidth,r=e.strideDepth,a=e.strideHeight,o=e.strideWidth,i=t-1-e.padInfo.front,l=n-1-e.padInfo.top,u=s-1-e.padInfo.left;this.userCode=`
      const ivec3 pads = ivec3(${i}, ${l}, ${u});

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int d1 = coords.u;


        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
        int dyFCorner = dyCorner.x;
        int dyRCorner = dyCorner.y;
        int dyCCorner = dyCorner.z;

        float dotProd = 0.0;
        for (int wF = 0; wF < ${t}; wF++) {
          float dyF = float(dyFCorner + wF) / ${r}.0;

          if (dyF < 0.0 || dyF >= ${e.outDepth}.0 || fract(dyF) > 0.0) {
            continue;
          }
          int idyF = int(dyF);

          int wFPerm = ${t} - 1 - wF;

          for (int wR = 0; wR < ${n}; wR++) {
            float dyR = float(dyRCorner + wR) / ${a}.0;

            if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
              fract(dyR) > 0.0) {
              continue;
            }
            int idyR = int(dyR);

            int wRPerm = ${n} - 1 - wR;

            for (int wC = 0; wC < ${s}; wC++) {
              float dyC = float(dyCCorner + wC) / ${o}.0;

              if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
                  fract(dyC) > 0.0) {
                continue;
              }
              int idyC = int(dyC);

              int wCPerm = ${s} - 1 - wC;

              for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
                float xValue = getDy(batch, idyF, idyR, idyC, d2);
                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function Sre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,filterShape:c}=s,p=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,c,o,1,i,u,!1,p),h=new vre(d);return n.runWebGLProgram(h,[r,a],"float32")}var Cre={kernelName:qm,backendName:"webgl",kernelFunc:Sre};function Tre(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{inputShape:o,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=s,p=C.convertConv2DDataFormat(u),d=C.computeConv2DInfo(o,a.shape,i,1,l,c,!1,p),h=new wre(d);return n.runWebGLProgram(h,[r,a],"float32")}var Nre={kernelName:Ao,backendName:"webgl",kernelFunc:Tre};function Ere(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l}=s,u=C.computeConv3DInfo(r.shape,a.shape,o,l,i),c=new yre(u);return n.runWebGLProgram(c,[r,a],"float32")}var Rre={kernelName:Bp,backendName:"webgl",kernelFunc:Ere};function _re(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,filterShape:l}=s,u=C.computeConv3DInfo(r.shape,l,o,1,i),c=new kre(u);return n.runWebGLProgram(c,[r,a],"float32")}var Dre={kernelName:Xm,backendName:"webgl",kernelFunc:_re};function $re(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{pad:o,strides:i,inputShape:l}=s,u=C.computeConv3DInfo(l,a.shape,i,1,o),c=new Ire(u);return n.runWebGLProgram(c,[r,a],"float32")}var Pre={kernelName:Km,backendName:"webgl",kernelFunc:$re},Fre=id+`
  return cos(x);
`,Ore=ct({opSnippet:Fre}),Mre={kernelName:xo,backendName:"webgl",kernelFunc:Ore},zre=`
  float e2x = exp(-x);
  return (e2x + 1.0 / e2x) / 2.0;
`,Lre=ct({opSnippet:zre}),Bre={kernelName:bo,backendName:"webgl",kernelFunc:Lre},Wre=class{constructor(e,t,n,s,r){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[a,o,i,l]=e,[u]=t,[c,p]=n;this.outputShape=[u,c,p,l];let d=s==="bilinear"?1:0,[h,f]=[`${o-1}.0`,`${i-1}.0`],[m,g,y]=c>1?[`${(o-1)/(c-1)}`,"(y2-y1) * height_ratio",`y1*${h} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${h}`],[x,A,b]=p>1?[`${(i-1)/(p-1)}`,"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=`
      const float height_ratio = float(${m});
      const float width_ratio = float(${x});
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int y = coords[1];
        int x = coords[2];
        int d = coords[3];

        // get box vals
        float y1 = getBoxes(b,0);
        float x1 = getBoxes(b,1);
        float y2 = getBoxes(b,2);
        float x2 = getBoxes(b,3);

        // get image in batch index
        int bInd = round(getBoxInd(b));
        if(bInd < 0 || bInd >= ${a}) {
          return;
        }

        float height_scale = ${g};
        float width_scale = ${A};

        float in_y = ${y};
        if( in_y < 0.0 || in_y > ${h} ) {
          setOutput(float(${r}));
          return;
        }
        float in_x = ${b};
        if( in_x < 0.0 || in_x > ${f} ) {
          setOutput(float(${r}));
          return;
        }

        vec2 sourceFracIndexCR = vec2(in_x,in_y);
        if(${d} == 1) {
          // Compute the four integer indices.
          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));

          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);

          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);

          float top = topLeft + (topRight - topLeft) * fracCR.x;
          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
          float newValue = top + (bottom - top) * fracCR.y;
          setOutput(newValue);
        } else {
          // Compute the coordinators of nearest neighbor point.
          ivec2 sourceNearestCR = ivec2(floor(
            sourceFracIndexCR + vec2(0.5,0.5)));
          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
          setOutput(newValue);
        }
      }
    `}},Vre=e=>{let{inputs:t,backend:n,attrs:s}=e,{image:r,boxes:a,boxInd:o}=t,{cropSize:i,method:l,extrapolationValue:u}=s,c=new Wre(r.shape,a.shape,i,l,u);return n.runWebGLProgram(c,[r,a,o],"float32")},Ure={kernelName:cl,backendName:"webgl",kernelFunc:Vre},$p;(function(e){e.Prod="*",e.Sum="+"})($p||($p={}));var I7=class{constructor(e,t,n,s){this.op=e,this.outputShape=t,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];let r=this.outputShape.length,a=this.op===$p.Prod?"1.0":"0.0",o=n?a:`getX(${S7(r,"coords",this.op)})`,i=this.outputShape[this.outputShape.length-1],l="",u="";n?(l=s?`end != ${i-1}`:"end != 0",u=s?"end + 1":"end - 1"):(l=s?`end + pow2 < ${i}`:"end >= pow2",u=s?"end + pow2":"end - pow2"),this.userCode=`
      void main() {
        ${wt(r)} coords = getOutputCoords();
        int end = ${C7(r,"coords",this.op)};
        float val = ${o};
        int pow2 = int(pow(2.0, index));
        if (${l}) {
          int idx = ${u};
          ${C7(r,"coords",this.op)} = idx;
          val ${this.op}= getX(${S7(r,"coords",this.op)});
        }
        setOutput(val);
      }
    `}};function S7(e,t,n){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw new Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function C7(e,t,n){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw new Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function k9(e,t,n,s,r,a){let o=t.shape.length,i=C.getAxesPermutation([s],o),l=t;i!=null&&(l=ts({inputs:{x:t},backend:n,attrs:{perm:i}}));let u=C.getInnerMostAxes(1,o)[0];if(u!==o-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${s}`);let c=l.shape[u],p=Ps({inputs:{x:l},backend:n});for(let d=0;d<=Math.ceil(Math.log2(c))-1;d++){let h=new I7(e,l.shape,!1,a),f=[[d]],m=p;p=n.runWebGLProgram(h,[p],p.dtype,f),n.disposeIntermediateTensorInfo(m)}if(r){let d=new I7(e,l.shape,r,a),h=p;p=n.runWebGLProgram(d,[p],p.dtype),n.disposeIntermediateTensorInfo(h)}if(i!=null){let d=C.getUndoAxesPermutation(i),h=ts({inputs:{x:p},backend:n,attrs:{perm:d}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(l),h}return p}function Gre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;return k9($p.Prod,r,n,a,o,i)}var Hre={kernelName:ul,backendName:"webgl",kernelFunc:Gre};function jre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;return k9($p.Sum,r,n,a,o,i)}var qre={kernelName:vo,backendName:"webgl",kernelFunc:jre};function Xre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o,binaryOutput:i}=s;if(r.shape.length===1){let l=n.readSync(r.dataId),u=n.readSync(a.dataId),c=n9(l,u,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,c)}else if(r.shape.length===2){let l=n.bufferSync(r),u=n.bufferSync(a),c=ote(l,u,o,i);return n.makeTensorInfo(c.shape,a.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var Kre={kernelName:Zm,backendName:"webgl",kernelFunc:Xre},Zre=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 Yre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockSize:a,dataFormat:o}=s,i=r.shape[0],l=o==="NHWC"?r.shape[1]:r.shape[2],u=o==="NHWC"?r.shape[2]:r.shape[3],c=o==="NHWC"?r.shape[3]:r.shape[1],p=l*a,d=u*a,h=c/(a*a),f=o==="NHWC"?[i,p,d,h]:[i,h,p,d],m=new Zre(f,a,o);return n.runWebGLProgram(m,[r],r.dtype)}var Jre={kernelName:dl,backendName:"webgl",kernelFunc:Yre},I9=class{constructor(e,t=!1,n=null,s=!1,r=!1){this.variableNames=["x","W"],this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=xs(this.outputShape.length);let a=e.filterHeight,o=e.filterWidth,i=e.outChannels/e.inChannels,l="",u="";n&&(s?l=`float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ${n}
        }`:r?l=`float activation(float a) {
          float b = getLeakyreluAlphaAtOutCoords();
          ${n}
        }`:l=`
          float activation(float x) {
            ${n}
          }
        `,u="result = activation(result);");let c=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${l}

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords.x;
        ivec2 xRCCorner = coords.yz * strides - pads;
        int d2 = coords.w;
        int d1 = d2 / ${i};
        int q = d2 - d1 * ${i};

        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.
        for (int wR = 0; wR < ${a}; wR++) {
          int xR = xRCorner + wR * dilations[0];

          if (xR < 0 || xR >= inDims[0]) {
            continue;
          }

          for (int wC = 0; wC < ${o}; wC++) {
            int xC = xCCorner + wC * dilations[1];

            if (xC < 0 || xC >= inDims[1]) {
              continue;
            }

            float xVal = getX(batch, xR, xC, d1);
            float wVal = getW(wR, wC, d1, q);
            dotProd += xVal * wVal;
          }
        }

        float result = dotProd;
        ${c}
        ${u}
        setOutput(result);
      }
    `}},S9=class{constructor(e,t=!1,n=null,s=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=xs(this.outputShape.length);let a=e.outChannels/e.inChannels,o=e.padInfo.left,i=e.strideWidth,l=e.dilationWidth,u=e.filterHeight,c=e.filterWidth,p=c,d=`
      int xR; int xC; int xCOffset;
      vec4 wTexel; vec4 previous; vec4 final;`;for(let g=0;g<c;g++)d+=`
          vec4 xTexelC${g*2};
          int xTexelC${g*2}Ready;
          vec4 xTexelC${g*2+1};
          int xTexelC${g*2+1}Ready;
          vec4 xC${g};`;d+=`
    for (int r = 0; r < ${u}; r++) {
      `;for(let g=0;g<c;g++)d+=`
          xTexelC${g*2} = vec4(0.0);
          xTexelC${g*2}Ready = 0;
          xTexelC${g*2+1} = vec4(0.0);
          xTexelC${g*2+1}Ready = 0;
          xC${g} = vec4(0.0);`;d+=`
        xR = xRCorner + r * dilations[0];
        if (xR >=0 && xR < inDims[0]) {
      `;for(let g=0;g<(p+1)/2;g++){let y=g*2;if(d+=`
          xC = xCCorner + ${y*l};
          `,i===1){if(y<c&&(o%2===1?(d+=`
                xCOffset = xC + 1;
                if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y}Ready == 0) {
                  xTexelC${y} = getX(batch, xR, xCOffset, d1);

                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if (xCOffset + 1 >= inDims[1]) {
                    xTexelC${y}.zw = vec2(0.0);
                  }
                  xTexelC${y}Ready = 1;
                }
              `,l===1&&y>0?d+=`
                xC${y} = vec4(xTexelC${y-2}.zw, xTexelC${y}.xy);
                `:d+=`
                  xCOffset = xC + 1 - 2;

                  if (xCOffset >= 0 && xCOffset < inDims[1]) {
                    previous = getX(batch, xR, xCOffset, d1);

                    // Need to manually clear unused channels in case
                    // we're reading from recycled texture.
                    if (xCOffset + 1 >= inDims[1]) {
                      previous.zw = vec2(0.0);
                    }

                    xC${y} = vec4(previous.zw, xTexelC${y}.xy);
                  } else {
                    xC${y} = vec4(0.0, 0.0, xTexelC${y}.xy);
                  }
                  `):d+=`
                if (xC >= 0 && xC < inDims[1] && xTexelC${y}Ready == 0) {
                  xTexelC${y} = getX(batch, xR, xC, d1);
                  if (xC + 1 >= inDims[1]) {
                    xTexelC${y}.zw = vec2(0.0);
                  }
                  xTexelC${y}Ready = 1;
                }

                xC${y} = xTexelC${y};
                `,y+1<c)){let x=o%2===0?v.nearestLargerEven(l):l;l%2===0&&o%2===1||l%2!==0&&o%2!==1?(d+=`
                  xCOffset = xC + imod(pads[1], 2) + ${x};

                  if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y+1}Ready == 0) {
                    xTexelC${y+1} = getX(batch, xR, xCOffset, d1);

                    // Need to manually clear unused channels in case
                    // we're reading from recycled texture.
                    if (xCOffset + 1 >= inDims[1]) {
                      xTexelC${y+1}.zw = vec2(0.0);
                    }
                    xTexelC${y+1}Ready = 1;
                  }
                  `,l>1&&(d+=`
                    xCOffset -= 2;
                    if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y}Ready == 0) {
                      xTexelC${y} = getX(batch, xR, xCOffset, d1);
                      xTexelC${y}Ready = 1;
                    }
                    `),d+=`
                  xC${y+1} = vec4(xTexelC${y}.zw, xTexelC${y+1}.xy);
                  `):x===1?d+=`
                    xC${y+1} = xTexelC${y};
                    `:d+=`
                    xCOffset = xC + ${x};

                    if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y+1}Ready == 0) {
                      xTexelC${y+1} = getX(batch, xR, xCOffset, d1);
                      if (xCOffset + 1 >= inDims[1]) {
                        xTexelC${y+1}.zw = vec2(0.0);
                      }
                      xTexelC${y+1}Ready = 1;
                    }

                    xC${y+1} = xTexelC${y+1};
                    `}}else y<c&&(o%2===1?(d+=`
                xCOffset = xC + 1 - strides[1];
                if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y}Ready == 0) {
                  xTexelC${y} = getX(batch, xR, xCOffset, d1);
                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if (xCOffset + 1 >= inDims[1]) {
                    xTexelC${y}.zw = vec2(0.0);
                  }
                  xTexelC${y}Ready = 1;
                }

                if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${y+1}Ready == 0) {
                  xTexelC${y+1} = getX(batch, xR, xC + 1, d1);
                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if (xC + 2 >= inDims[1]) {
                    xTexelC${y+1}.zw = vec2(0.0);
                  }
                  xTexelC${y+1}Ready = 1;
                }

                xC${y} = vec4(xTexelC${y}.zw, xTexelC${y+1}.zw);
              `,y+1<c&&(d+=`
                  final = vec4(0.0);
                  xCOffset = xC + 1 + strides[1];
                  if(xCOffset >= 0 && xCOffset < inDims[1]) {
                    final = getX(batch, xR, xCOffset, d1);
                  }
                  xC${y+1} = vec4(xTexelC${y+1}.xy, final.xy);
                `)):(d+=`
                if(xC >= 0 && xC < inDims[1] && xTexelC${y}Ready == 0) {
                  xTexelC${y} = getX(batch, xR, xC, d1);
                  if (xC + 1 >= inDims[1]) {
                    xTexelC${y}.zw = vec2(0.0);
                  }
                  xTexelC${y}Ready = 1;
                }

                xCOffset = xC + strides[1];
                if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y+1}Ready == 0) {
                  xTexelC${y+1} = getX(batch, xR, xCOffset, d1);
                  if (xCOffset + 1 >= inDims[1]) {
                    xTexelC${y+1}.zw = vec2(0.);
                  }
                  xTexelC${y+1}Ready = 1;
                }

                xC${y} = vec4(
                  xTexelC${y}.xy, xTexelC${y+1}.xy);
              `,y+1<c&&(d+=`
                  xC${y+1} = vec4(xTexelC${y}.zw, xTexelC${y+1}.zw);
                `)));y<c&&(d+=`
            wTexel = getW(r, ${y}, d1, q);
            dotProd += xC${y} * vec4(wTexel.xz, wTexel.xz);
          `,y+1<c&&(d+=`
              wTexel = getW(r, ${y+1}, d1, q);
              dotProd += xC${y+1} * vec4(wTexel.xz, wTexel.xz);
            `))}d+=`
    }
  `,d+=`
      }
    `;let h="",f="";n&&(s?h=`vec4 activation(vec4 a) {
          vec4 b = getPreluActivationWeightsAtOutCoords();
          ${n}
        }`:r?h=`vec4 activation(vec4 a) {
          vec4 b = getLeakyreluAlphaAtOutCoords();
          ${n}
        }`:h=`vec4 activation(vec4 x) {
          ${n}
        }`,f="result = activation(result);");let m=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${h}

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords.x;
        ivec2 xRCCorner = coords.yz * strides - pads;
        int d2 = coords.w;
        int d1 = d2 / ${a};
        int q = d2 - d1 * ${a};
        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.
        vec4 dotProd = vec4(0.000000000000001);

        ${d}

        vec4 result = dotProd - vec4(0.000000000000001);
        ${m}
        ${f}
        setOutput(result);
      }
    `}};function Qre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l,dimRoundingMode:u}=s,c=l;c==null&&(c=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(o,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${o} and dilations '${c}'`);let p=C.computeConv2DInfo(r.shape,a.shape,o,c,i,u,!0),d;X().getBool("WEBGL_PACK_DEPTHWISECONV")&&p.strideWidth<=2&&p.outChannels/p.inChannels===1?d=new S9(p):d=new I9(p);let h=[[p.padInfo.top,p.padInfo.left],[p.strideHeight,p.strideWidth],[p.dilationHeight,p.dilationWidth],[p.inHeight,p.inWidth]];return n.runWebGLProgram(d,[r,a],"float32",h)}var eae={kernelName:wo,backendName:"webgl",kernelFunc:Qre},tae=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,s=e.padInfo.top,r=e.padInfo.left,a=e.outChannels/e.inChannels;this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int wR = coords.x;
        int wC = coords.y;
        int d1 = coords.z;
        int dm = coords.w;
        int d2 = d1 * ${a} + dm;

        float dotProd = 0.0;

        // TO DO: Vec4 over the batch size
        for (int b = 0; b < ${e.batchSize}; b++) {
          for (int yR = 0; yR < ${e.outHeight}; yR++) {
            int xR = wR + yR * ${t} - ${s};

            if (xR < 0 || xR >= ${e.inHeight}) {
              continue;
            }

            for (int yC = 0; yC < ${e.outWidth}; yC++) {
              int xC = wC + yC * ${n} - ${r};

              if (xC < 0 || xC >= ${e.inWidth}) {
                continue;
              }

              float dyValue = getDy(b, yR, yC, d2);
              float xValue = getX(b, xR, xC, d1);
              dotProd += (xValue * dyValue);
            }
          }
        }
        setOutput(dotProd);
      }
    `}},nae=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,s=e.strideHeight,r=e.strideWidth,a=t-1-e.padInfo.top,o=n-1-e.padInfo.left,i=e.outChannels/e.inChannels;this.userCode=`
      const ivec2 pads = ivec2(${a}, ${o});

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d1 = coords[3];
        ivec2 dyCorner = coords.yz - pads;
        int dyRCorner = dyCorner.x;
        int dyCCorner = dyCorner.y;

        float dotProd = 0.0;

        for (int wR = 0; wR < ${t}; wR++) {
          float dyR = float(dyRCorner + wR) / ${s}.0;

          if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          int wRPerm = ${t} - 1 - wR;

          for (int wC = 0; wC < ${n}; wC++) {
            float dyC = float(dyCCorner + wC) / ${r}.0;

            if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            int wCPerm = ${n} - 1 - wC;

            // TO DO: Vec4 over the channelMul
            for (int dm = 0; dm < ${i}; dm++) {
              int d2 = d1 * ${i} + dm;
              float xValue = getDy(batch, idyR, idyC, d2);
              float wValue = getW(wRPerm, wCPerm, d1, dm);
              dotProd += xValue * wValue;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function sae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,filterShape:c}=s,p=C.computeConv2DInfo(r.shape,c,o,i,l,u,!0),d=new tae(p);return n.runWebGLProgram(d,[r,a],"float32")}var rae={kernelName:Ym,backendName:"webgl",kernelFunc:sae};function aae(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=s,p=C.computeConv2DInfo(c,a.shape,o,i,l,u,!0),d=new nae(p);return n.runWebGLProgram(d,[r,a],"float32")}var oae={kernelName:Jm,backendName:"webgl",kernelFunc:aae},iae=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
      void main() {
          ivec2 coords = getOutputCoords();
          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
          setOutput(val);
      }
    `}};function lae(e){let{inputs:t,backend:n}=e,{x:s}=t,r=[...s.shape,...s.shape],a=v.sizeFromShape(s.shape),o=be({inputs:{x:s},backend:n,attrs:{shape:[a]}}),i=new iae(a),l=n.runWebGLProgram(i,[o],o.dtype),u=be({inputs:{x:l},backend:n,attrs:{shape:r}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(l),u}var uae={kernelName:Qm,backendName:"webgl",kernelFunc:lae},cae=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:s,strideHeight:r,strideWidth:a,filterHeight:o,filterWidth:i,dilationHeight:l,dilationWidth:u}=e,{top:c,left:p}=s;this.userCode=`
      const ivec2 strides = ivec2(${r}, ${a});
      const ivec2 pads = ivec2(${c}, ${p});
      const float neg_infinity = -3.4e38;

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords.x;
        int d1 = coords.w;
        ivec2 outTopLeftCorner =
            coords.yz * strides - pads;
        int hBeg = outTopLeftCorner.x;
        int wBeg = outTopLeftCorner.y;

        float curVal = neg_infinity;
        for (int h = 0; h < ${o}; h++) {
          int hIn = hBeg + h * ${l};

          if (hIn >= 0 && hIn < ${t}) {
            for (int w = 0; w < ${i}; w++) {
              int wIn = wBeg + w * ${u};

              if (wIn >= 0 && wIn < ${n}) {
                float xVal = getX(batch, hIn, wIn, d1);
                float wVal = getW(h, w, d1);

                float val = xVal + wVal;
                if (val > curVal) {
                  curVal = val;
                }
              }
            }
          }
        }

        float result = curVal;
        setOutput(result);
      }
    `}};function dae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l}=s,u=C.computeDilation2DInfo(r.shape,a.shape,o,i,"NHWC",l),c,p=new cae(u);c=n.runWebGLProgram(p,[r,a],"float32");let d=be({inputs:{x:c},backend:n,attrs:{shape:u.outShape}});return n.disposeIntermediateTensorInfo(c),d}var pae={kernelName:Wp,backendName:"webgl",kernelFunc:dae};function hae(e){let{inputs:t,backend:n,attrs:s}=e,{equation:r}=s,a=t,{allDims:o,summedDims:i,idDims:l}=C.decodeEinsumEquation(r,a.length);C.checkEinsumDimSizes(o.length,l,a);let{path:u,steps:c}=C.getEinsumComputePath(i,l),p=c.length,d=null,h=o.length,f=[];for(let m=0;m<p;++m){for(let g of c[m]){let{permutationIndices:y,expandDims:x}=C.getEinsumPermutation(h,l[g]),A;C.isIdentityPermutation(y)?A=a[g]:(A=ts({inputs:{x:a[g]},backend:n,attrs:{perm:y}}),f.push(A));let b=A.shape.slice();for(let w=0;w<x.length;++w)b.splice(x[w],0,1);v.arraysEqual(A.shape,b)||(A=be({inputs:{x:A},backend:n,attrs:{shape:b}}),f.push(A)),d===null?d=A:(d=Yx({inputs:{a:A,b:d},backend:n}),f.push(d))}m<p-1&&(u[m]>=0&&(d=k2({inputs:{x:d},backend:n,attrs:{axis:u[m]-(o.length-h),keepDims:!1}}),f.push(d)),h--)}for(let m of f)m!==d&&n.disposeIntermediateTensorInfo(m);return d}var fae={kernelName:Vp,backendName:"webgl",kernelFunc:hae},mae="return (x >= 0.0) ? x : (exp(x) - 1.0);",gae=`
  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;
`,yae=ct({opSnippet:mae,packedOpSnippet:gae}),Aae={kernelName:Io,backendName:"webgl",kernelFunc:yae},xae="return (b >= 1.0) ? a : a * (b + 1.0);",bae=`
  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,vae=e=>{let{inputs:t,backend:n}=e,{dy:s,y:r}=t,a=X().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Oh(bae,s.shape,r.shape):new lc(xae,s.shape,r.shape);return n.runWebGLProgram(a,[s,r],s.dtype)},wae={kernelName:e0,backendName:"webgl",kernelFunc:vae},kae=`
  return vec4(equal(a, b));
`,Iae="return float(a == b);",Sae=Rn({opSnippet:Iae,packedOpSnippet:kae,dtype:"bool",cpuKernelImpl:ute}),Cae={kernelName:pl,backendName:"webgl",kernelFunc:Sae},Tae=`
  // Error function is calculated approximately with elementary function.
  // See "Handbook of Mathematical Functions with Formulas,
  // Graphs, and Mathematical Tables", Abramowitz and Stegun.
  float p = ${C.ERF_P};
  float a1 = ${C.ERF_A1};
  float a2 = ${C.ERF_A2};
  float a3 = ${C.ERF_A3};
  float a4 = ${C.ERF_A4};
  float a5 = ${C.ERF_A5};

  float sign = sign(x);
  x = abs(x);
  float t = 1.0 / (1.0 + p * x);
  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
`,Nae=ct({opSnippet:Tae}),Eae={kernelName:vc,backendName:"webgl",kernelFunc:Nae},Rae=id+`
  return exp(x);
`,_ae=`
  vec4 result = exp(x);
  bvec4 isNaN = isnan(x);
  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`,C9=ct({opSnippet:Rae,packedOpSnippet:_ae,cpuKernelImpl:cte,dtype:"float32"}),Dae={kernelName:So,backendName:"webgl",kernelFunc:C9};function iy(e){let{inputs:t,attrs:n,backend:s}=e,{dim:r}=n,{input:a}=t,o=a.shape.length,i=a.shape.slice(),l=r;return r<0&&(v.assert(-(o+1)<=r,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+r+1),i.splice(l,0,1),be({inputs:{x:a},backend:s,attrs:{shape:i}})}var $ae={kernelName:hl,backendName:"webgl",kernelFunc:iy},T7="return exp(x) - 1.0;",Pae=ct({opSnippet:T7,packedOpSnippet:T7,cpuKernelImpl:dte}),Fae={kernelName:fl,backendName:"webgl",kernelFunc:Pae},N7=class{constructor(e,t,n){this.variableNames=["real","imag"];let s=t[1];this.outputShape=t;let r=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,a=n?`${s}.0`:"1.0",o;if(e==="real")o="return real * expR - imag * expI;";else if(e==="imag")o="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
      const float exponentMultiplier = ${r};

      float unaryOpComplex(float real, float expR, float imag, float expI) {
        ${o}
      }

      float mulMatDFT(int batch, int index) {
        float indexRatio = float(index) / float(${s});
        float exponentMultiplierTimesIndexRatio =
            exponentMultiplier * indexRatio;

        float result = 0.0;

        for (int i = 0; i < ${s}; i++) {
          // x = (-2|2 * PI / N) * index * i;
          float x = exponentMultiplierTimesIndexRatio * float(i);
          float expR = cos(x);
          float expI = sin(x);
          float real = getReal(batch, i);
          float imag = getImag(batch, i);

          result +=
              unaryOpComplex(real, expR, imag, expI) / ${a};
        }

        return result;
      }

      void main() {
        ivec2 coords = getOutputCoords();
        setOutput(mulMatDFT(coords[0], coords[1]));
      }
    `}};function T9(e,t,n){let s=n.texData.get(e.dataId),r=v.sizeFromShape(e.shape),a=e.shape[e.shape.length-1],o=r/a,i=be({inputs:{x:e},backend:n,attrs:{shape:[o,a]}}),l=i.shape,u=new N7("real",l,t),c=new N7("imag",l,t),p=[{dataId:s.complexTensorInfos.real.dataId,dtype:s.complexTensorInfos.real.dtype,shape:l},{dataId:s.complexTensorInfos.imag.dataId,dtype:s.complexTensorInfos.imag.dtype,shape:l}],d=n.runWebGLProgram(u,p,"float32"),h=n.runWebGLProgram(c,p,"float32"),f=di({inputs:{real:d,imag:h},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h);let m=be({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(f),m}function Oae(e){let{inputs:t,backend:n}=e,{input:s}=t;return T9(s,!1,n)}var Mae={kernelName:t0,backendName:"webgl",kernelFunc:Oae},zae=class{constructor(e,t){this.outputShape=[],this.customUniforms=[{name:"value",type:"float"}],this.variableNames=["x"],this.outputShape=e,this.userCode=`
      void main() {
        // Input can be obtained from uniform value.
        setOutput(value);
      }
    `}};function zh(e){let{backend:t,attrs:n}=e,{shape:s,value:r}=n,{dtype:a}=n;if(a=a||v.inferDtype(r),a==="string"){let o=v.getArrayFromDType(a,v.sizeFromShape(s));return o.fill(r),t.makeTensorInfo(s,a,o)}else{let o=new zae(s,r),i=[[r]];return t.runWebGLProgram(o,[],a,i)}}var Lae={kernelName:wc,backendName:"webgl",kernelFunc:zh},Bae=class{constructor(e){this.variableNames=["Image"],this.outputShape=[];let t=e[2];this.outputShape=e,this.userCode=`
        void main() {
          ivec4 coords = getOutputCoords();
          int x = coords[2];

          int coordX = ${t} - x - 1;
          float outputValue;
          if(coordX >= 0 && coordX < ${t}) {
            outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
          } else {
            outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
          }
          setOutput(outputValue);
        }
    `}},Wae={kernelName:ml,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,s=t,r=new Bae(n.shape);return s.runWebGLProgram(r,[n],n.dtype)}},E7="return floor(x);",Vae=ct({opSnippet:E7,packedOpSnippet:E7,cpuKernelImpl:pte}),Uae={kernelName:Co,backendName:"webgl",kernelFunc:Vae},Gae=`
  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;
  }
`,Hae=`
  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);
`,jae=Rn({opSnippet:Gae,packedOpSnippet:Hae,dtype:"int32"}),qae={kernelName:To,backendName:"webgl",kernelFunc:jae},Xae=class{constructor(e){this.variableNames=["A"];let t=as(),[n,s]=e;this.outputShape=e,this.userCode=`
      void main() {
        ivec3 coords = getOutputCoords();
        int texR = coords[0];
        int texC = coords[1];
        int depth = coords[2];
        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${s}.0, ${n}.0);

        vec4 values = ${t.texture2D}(A, uv);
        float value;
        if (depth == 0) {
          value = values.r;
        } else if (depth == 1) {
          value = values.g;
        } else if (depth == 2) {
          value = values.b;
        } else if (depth == 3) {
          value = values.a;
        }

        setOutput(floor(value * 255.0 + 0.5));
      }
    `}},Kae=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=as(),[n,s]=e;this.outputShape=e,this.userCode=`
      void main() {
        ivec3 coords = getOutputCoords();
        int texR = coords[0];
        int texC = coords[1];
        int depth = coords[2];

        vec4 result = vec4(0.);

        for(int row=0; row<=1; row++) {
          for(int col=0; col<=1; col++) {
            texC = coords[1] + row;
            depth = coords[2] + col;

            vec2 uv = (vec2(texC, texR) + halfCR) /
                       vec2(${s}.0, ${n}.0);
            vec4 values = ${t.texture2D}(A, uv);
            float value;
            if (depth == 0) {
              value = values.r;
            } else if (depth == 1) {
              value = values.g;
            } else if (depth == 2) {
              value = values.b;
            } else if (depth == 3) {
              value = values.a;
            }

            result[row * 2 + col] = floor(value * 255.0 + 0.5);
          }
        }

        ${t.output} = result;
      }
    `}},Zae={kernelName:xp,backendName:"webgl",kernelFunc:Yae},Pu;function Yae(e){let{inputs:t,backend:n,attrs:s}=e,{pixels:r}=t,{numChannels:a}=s,o=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,i=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,[l,u]=o?[r.videoWidth,r.videoHeight]:[r.width,r.height],c=[u,l],p=[u,l,a];(i||o)&&(Pu==null&&(Pu=document.createElement("canvas").getContext("2d")),Pu.canvas.width=l,Pu.canvas.height=u,Pu.drawImage(r,0,0,l,u),r=Pu.canvas);let d=n.makeTensorInfo(c,"int32");n.texData.get(d.dataId).usage=qs.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),r);let h=X().getBool("WEBGL_PACK")?new Kae(p):new Xae(p),f=n.runWebGLProgram(h,[d],"int32");return n.disposeData(d.dataId),f}function Jae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=s,m=C.convertConv2DDataFormat(c),g=C.computeConv2DInfo(r.shape,a.shape,l,p,u,d,!1,m),y,x=[];if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))y=v9({x:r,filter:a,convInfo:g,backend:n,bias:o,activation:h,preluActivationWeights:i,leakyreluAlpha:f});else if(X().getBool("WEBGL_CONV_IM2COL"))y=w9({x:r,filter:a,convInfo:g,backend:n,bias:o,activation:h,preluActivationWeights:i,leakyreluAlpha:f});else{let b=o!=null,w=i!=null,k=h==="leakyrelu",S=h?v2(h,!1):null,E=new b9(g,b,S,w,k),R=[r,a],P=(_,$)=>{if($==="NCHW"&&_.shape.length===1&&_.shape[0]!==1){let T=be({inputs:{x:_},backend:n,attrs:{shape:[_.shape[0],1,1]}});return x.push(T),T}return _};if(b&&R.push(P(o,c)),w&&R.push(P(i,c)),k){let _=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));R.push(_),x.push(_)}y=n.runWebGLProgram(E,R,"float32")}let A=be({inputs:{x:y},backend:n,attrs:{shape:g.outShape}});return x.push(y),x.forEach(b=>n.disposeIntermediateTensorInfo(b)),A}var Qae={kernelName:Ja,backendName:"webgl",kernelFunc:Jae};function eoe(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dimRoundingMode:p,activation:d,leakyreluAlpha:h}=s,f=[],m=c;m==null&&(m=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let g=C.computeConv2DInfo(r.shape,a.shape,l,m,u,p,!0),y=X().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,x=d?v2(d,y):null,A=[r,a],b=o!=null,w=i!=null,k=d==="leakyrelu";if(b&&A.push(o),w&&A.push(i),k){let P=n.makeTensorInfo([],"float32",v.createScalarValue(h,"float32"));A.push(P),f.push(P)}let S;y?S=new S9(g,b,x,w,k):S=new I9(g,b,x,w,k);let E=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],R=n.runWebGLProgram(S,A,"float32",E);return f.forEach(P=>n.disposeIntermediateTensorInfo(P)),R}var toe={kernelName:Qa,backendName:"webgl",kernelFunc:eoe},noe=class{constructor(e,t,n,s){this.sliceDim=e,this.strides=t,this.paramsShape=s,this.variableNames=["x","indices"],this.outputShape=n;let r=wt(t.length),a=wt(n.length),o=this.sliceDim>1?"strides[j]":"strides",i=wt(s.length),l=s.length>1?"paramsShape[j]":"paramsShape";this.userCode=`
        ${r} strides = ${r}(${this.strides});
        ${i} paramsShape = ${i}(${this.paramsShape});
         void main() {
          ${a} coords = getOutputCoords();
          int flattenIndex = 0;
          bool out_of_bounds = false;
          for (int j = 0; j < ${this.sliceDim}; j++) {
            int index = round(getIndices(coords[0], j));
            out_of_bounds = out_of_bounds || index < 0;
            out_of_bounds = out_of_bounds || index >= ${l};
            flattenIndex += index * ${o};
          }
          setOutput(out_of_bounds ? 0.0 : getX(flattenIndex, coords[1]));
        }
      `}};function soe(e){let{inputs:t,backend:n}=e,{params:s,indices:r}=t,a=r.shape,o=a[a.length-1],i=v.sizeFromShape(s.shape),[l,u,c,p]=C.prepareAndValidate(s,r),d=be({inputs:{x:r},backend:n,attrs:{shape:[u,o]}}),h=be({inputs:{x:s},backend:n,attrs:{shape:[v.sizeFromShape(s.shape)/c,c]}});if(n.shouldExecuteOnCPU([s,r])||s.dtype==="string"){let y=n.readSync(r.dataId),x=n.bufferSync(s),A=hte(y,x,s.dtype,u,o,c,p,s.shape,i);return n.makeTensorInfo(l,s.dtype,A.values)}let f=new noe(o,p,[u,c],s.shape),m=n.runWebGLProgram(f,[h,d],h.dtype),g=be({inputs:{x:m},backend:n,attrs:{shape:l}});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(m),g}var roe={kernelName:yl,backendName:"webgl",kernelFunc:soe},aoe=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=wt(this.rank),s=ooe(e,2);this.userCode=`
      void main() {
        ${n} resRC = getOutputCoords();
        int index = int(getIndices(resRC.x, resRC.z));
        float inBounds = (index >= 0) && (index < ${e[2]}) ? 1.0 : 0.0;
        setOutput(inBounds * getA(${s}));
      }
    `}};function ooe(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],s=[];for(let r=0;r<e.length;r++)r===2?s.push("index"):s.push(`${n[r]}`);return s.join()}function N9(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,indices:a}=t,{axis:o,batchDims:i}=s,l=v.parseAxisParam(o,r.shape)[0];if(X().get("DEBUG")){let x=n.readSync(a.dataId),A=r.shape[l];for(let b=0;b<x.length;++b){let w=x[b];v.assert(w<=A-1&&w>=0,()=>`GatherV2: the index value ${w} is not in [0, ${A-1}]`)}}let u=C.segment_util.collectGatherOpShapeInfo(r,a,l,i),c=v.sizeFromShape(a.shape),p=[],d=be({inputs:{x:r},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=be({inputs:{x:a},backend:n,attrs:{shape:[u.batchSize,c/u.batchSize]}});p.push(d),p.push(h);let f=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([r,a])||r.dtype==="string"){let x=n.bufferSync(h),A=n.bufferSync(d),b=fte(A,x,f);return p.forEach(w=>n.disposeIntermediateTensorInfo(w)),n.makeTensorInfo(u.outputShape,b.dtype,b.values)}let m=new aoe(d.shape,f),g=n.runWebGLProgram(m,[d,h],d.dtype);p.push(g);let y=be({inputs:{x:g},backend:n,attrs:{shape:u.outputShape}});return p.forEach(x=>n.disposeIntermediateTensorInfo(x)),y}var ioe={kernelName:gl,backendName:"webgl",kernelFunc:N9},loe="return float(a > b);",uoe=`
  return vec4(greaterThan(a, b));
`,coe=Rn({opSnippet:loe,packedOpSnippet:uoe,cpuKernelImpl:mte,dtype:"bool"}),doe={kernelName:Al,backendName:"webgl",kernelFunc:coe},poe="return float(a >= b);",hoe=`
  return vec4(greaterThanEqual(a, b));
`,foe=Rn({opSnippet:poe,packedOpSnippet:hoe,dtype:"bool",cpuKernelImpl:gte}),moe={kernelName:Eo,backendName:"webgl",kernelFunc:foe};function goe(e){let{inputs:t,backend:n}=e,{input:s}=t;return T9(s,!0,n)}var yoe={kernelName:n0,backendName:"webgl",kernelFunc:goe},Aoe="return float(!isnan(x) && !isinf(x));",xoe=ct({opSnippet:Aoe,dtype:"bool"}),boe={kernelName:kc,backendName:"webgl",kernelFunc:xoe},voe="return float(isinf(x));",woe=ct({opSnippet:voe,dtype:"bool"}),koe={kernelName:Ic,backendName:"webgl",kernelFunc:woe},Ioe="return float(isnan(x));",Soe=ct({opSnippet:Ioe,dtype:"bool"}),Coe={kernelName:Sc,backendName:"webgl",kernelFunc:Soe},Toe="return float(a < b);",Noe=`
  return vec4(lessThan(a, b));
`,Eoe=Rn({opSnippet:Toe,packedOpSnippet:Noe,cpuKernelImpl:yte,dtype:"bool"}),Roe={kernelName:xl,backendName:"webgl",kernelFunc:Eoe},_oe="return float(a <= b);",Doe=`
  return vec4(lessThanEqual(a, b));
`,$oe=Rn({opSnippet:_oe,packedOpSnippet:Doe,cpuKernelImpl:Ate,dtype:"bool"}),Poe={kernelName:bl,backendName:"webgl",kernelFunc:$oe};function Foe(e){let{backend:t,attrs:n}=e,{start:s,stop:r,num:a}=n,o=xte(s,r,a);return t.makeTensorInfo([o.length],"float32",o)}var Ooe={kernelName:s0,backendName:"webgl",kernelFunc:Foe},Moe=id+`
  return x < 0.0 ? 0./0. : log(x);
`,zoe=`
  vec4 result = log(x);
  bvec4 isNaN = isnan(x);
  result.r = isNaN.r ? x.r : (x.r < 0.0 ? 0./0. : result.r);
  result.g = isNaN.g ? x.g : (x.g < 0.0 ? 0./0. : result.g);
  result.b = isNaN.b ? x.b : (x.b < 0.0 ? 0./0. : result.b);
  result.a = isNaN.a ? x.a : (x.a < 0.0 ? 0./0. : result.a);
  return result;
`,Loe=ct({opSnippet:Moe,packedOpSnippet:zoe,cpuKernelImpl:bte}),Boe={kernelName:Do,backendName:"webgl",kernelFunc:Loe},Woe=id+`
  return log(1.0 + x);
`,Voe=ct({opSnippet:Woe}),Uoe={kernelName:Cc,backendName:"webgl",kernelFunc:Voe},Goe="return float(a >= 1.0 && b >= 1.0);",Hoe=`
  return vec4(
    vec4(greaterThanEqual(a, vec4(1.0))) *
    vec4(greaterThanEqual(b, vec4(1.0))));
`,joe=Rn({opSnippet:Goe,packedOpSnippet:Hoe,dtype:"bool"}),qoe={kernelName:vl,backendName:"webgl",kernelFunc:joe},Xoe="return float(!(x >= 1.0));",Koe=ct({opSnippet:Xoe}),Zoe={kernelName:wl,backendName:"webgl",kernelFunc:Koe},Yoe="return float(a >= 1.0 || b >= 1.0);",Joe=`
  return min(
    vec4(greaterThanEqual(a, vec4(1.0))) +
    vec4(greaterThanEqual(b, vec4(1.0))),
    vec4(1.0));
`,Qoe=Rn({opSnippet:Yoe,packedOpSnippet:Joe,dtype:"bool"}),eie={kernelName:Tc,backendName:"webgl",kernelFunc:Qoe},tie=class{constructor(e,t,n,s,r){this.variableNames=["x"],this.outputShape=[];let a=t,o=e[3]-1;this.outputShape=e;let i,l=`float(${n}) + float(${s}) * sum`;r===.5?i=`inversesqrt(${l})`:r===1?i=`1.0/(${l})`:i=`exp(log(${l}) * float(-${r}));`,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int r = coords[1];
        int c = coords[2];
        int d = coords[3];
        float x = getX(b, r, c, d);
        float sum = 0.0;
        for (int j = -${a}; j <= ${a}; j++) {
          int idx = d + j;
          if (idx >= 0 && idx <=  ${o}) {
            float z = getX(b, r, c, idx);
            sum += z * z;
          }
        }
        float val = x * ${i};
        setOutput(val);
      }
    `}},nie=class{constructor(e,t,n,s,r){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let a=t,o=e[3]-1;this.outputShape=e;let i,l=`float(${n}) + float(${s}) * sum`;r===.5?i=`inversesqrt(${l})`:r===1?i=`1.0/(${l})`:i=`exp(log(${l}) * float(-${r}));`,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords.x;
        int r = coords.y;
        int c = coords.z;
        int d = coords.w;

        bool hasNextCol = d < ${this.outputShape[3]};
        bool hasNextRow = c < ${this.outputShape[2]};

        vec4 sum = vec4(0.);
        vec4 xFragAtOutputCoords = getX(b, r, c, d);

        vec4 xAtOutputCoords = vec4(
          getChannel(xFragAtOutputCoords, vec2(c, d)),
          hasNextCol ?
            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,
          hasNextRow ?
            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,
          (hasNextRow && hasNextCol) ?
            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0
        );

        int firstChannel = d - ${a};
        vec2 cache = vec2(0.);
        if(firstChannel >= 0){
          vec4 firstChannelFrag = getX(b, r, c, firstChannel);
          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));
            if(hasNextRow){
              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));
            }
        }

        ivec2 depth = ivec2(d, d + 1);
        for (int j = - ${a}; j <= ${a}; j++) {
          ivec2 idx = depth + j;
          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${o}));

          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;
          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;

          if(depthInRange || depthPlusOneInRange){
            vec4 z = vec4(0.);
            vec4 xFragAtCurrentDepth;
            z.xz = cache.xy;
            if(depthPlusOneInRange && hasNextCol){
              xFragAtCurrentDepth = idx.y != d ?
                getX(b, r, c, idx.y) : xFragAtOutputCoords;
              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));
              if(hasNextRow){
                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));
              }
            }
            cache.xy = z.yw;
            sum += z * z;
          }
        }
        vec4 result = xAtOutputCoords * ${i};
        setOutput(result);
      }
    `}},sie=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{depthRadius:a,bias:o,alpha:i,beta:l}=s,u=X().getBool("WEBGL_PACK_NORMALIZATION")?new nie(r.shape,a,o,i,l):new tie(r.shape,a,o,i,l);return n.runWebGLProgram(u,[r],r.dtype)},rie={kernelName:Gp,backendName:"webgl",kernelFunc:sie},aie=class{constructor(e,t,n,s,r){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=s,this.beta=r,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int r = coords[1];
        int c = coords[2];

        float result = 0.0;
        for (int d = 0; d < ${this.depth}; ++d) {
          int depthBegin = int(max(0.0, float(d - ${t})));
          int depthEnd = int(min(float(${this.depth}),
              float(d + ${t} + 1)));

          const int MIN_DEPTH_BEGIN = 0;
          const int MAX_DEPTH_END = ${this.depth};

          float norm = 0.0;
          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {
            if (k < depthBegin){
              continue;
            }
            else if (k >= depthBegin && k < depthEnd) {
              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
            }
            else {
              break;
            }
          }

          norm = float(${s}) * norm + float(${n});

          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
            if (k < depthBegin){
              continue;
            }
            else if (k >= depthBegin && k < depthEnd){
              float dyi = -2.0 * float(${s})
                * float(${r})
                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
                / norm;
              if (k == d) {
                dyi += pow(norm, -1.0 * ${r});
              }
              if (k == coords[3]) {
                dyi *= getDy(b, r, c, d);
                result += dyi;
              }
            }
            else {
              break;
            }
          }
      }
      setOutput(result);
      }
    `}},oie=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r,y:a,dy:o}=t,{depthRadius:i,bias:l,alpha:u,beta:c}=s,p=new aie(r.shape,i,l,u,c);return n.runWebGLProgram(p,[r,a,o],r.dtype)},iie={kernelName:r0,backendName:"webgl",kernelFunc:oie};function lie(e,t,n,s){let r=v.sizeFromShape(t),o=v.sizeFromShape(e.shape)/r,i=be({inputs:{x:e},attrs:{shape:[o,r]},backend:s}),l=ru(i,e.dtype,"max",s),u=be({inputs:{x:l},attrs:{shape:n},backend:s});return s.disposeIntermediateTensorInfo(i),s.disposeIntermediateTensorInfo(l),u}function E9(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reductionIndices:a,keepDims:o}=s,i=r.shape.length,l=v.parseAxisParam(a,r.shape),u=l,c=C.getAxesPermutation(u,i),p=c!=null,d=n.shouldExecuteOnCPU([r]),h=r;if(p){if(d){let A=n.texData.get(h.dataId).values,b=new Array(i);for(let S=0;S<b.length;S++)b[S]=r.shape[c[S]];let w=Zx(A,r.shape,r.dtype,c,b);h=n.makeTensorInfo(b,r.dtype);let k=n.texData.get(h.dataId);k.values=w}else h=w2(r,c,n);u=C.getInnerMostAxes(u.length,i)}C.assertAxesAreInnerMostDims("max",u,i);let[f,m]=C.computeOutAndReduceShapes(h.shape,u),g=f;o&&(g=C.expandShapeToKeepDim(f,l));let y;if(d){let A=n.texData.get(h.dataId).values,b=vte(A,v.sizeFromShape(m),g,r.dtype);y=n.makeTensorInfo(g,r.dtype);let w=n.texData.get(y.dataId);w.values=b}else y=lie(h,m,g,n);return p&&n.disposeIntermediateTensorInfo(h),y}var uie={kernelName:$o,backendName:"webgl",kernelFunc:E9},cie=l9+`
  return max(a, b);
`,die=`
  vec4 result = vec4(max(a, b));
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  `+b2+`
  return result;
`,pie=Rn({opSnippet:cie,packedOpSnippet:die,cpuKernelImpl:wte}),hie={kernelName:Po,backendName:"webgl",kernelFunc:pie};function fie(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;td(r,"maxPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;v.assert(C.eitherStridesOrDilationsAreOne(o,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=C.computePool2DInfo(r.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Ps({inputs:{x:r},backend:n});let p=new Dp(c,"max",!1);return n.runWebGLProgram(p,[r],r.dtype)}var mie={kernelName:Fo,backendName:"webgl",kernelFunc:fie};function gie(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dataFormat:l,dimRoundingMode:u}=s,c=[1,1,1],p=C.computePool3DInfo(r.shape,a,o,c,i,u,l),d=new Jx(p,"max",!1);return n.runWebGLProgram(d,[r],r.dtype)}var yie={kernelName:Hp,backendName:"webgl",kernelFunc:gie},Aie=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,s=e.dilationHeight,r=e.effectiveFilterHeight,a=e.effectiveFilterWidth,o=r-1-e.padInfo.top,i=a-1-e.padInfo.left,l=r*a-1;this.userCode=`
      const ivec2 pads = ivec2(${o}, ${i});

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];

        ivec2 dyRCCorner = coords.yz - pads;
        int dyRCorner = dyRCCorner.x;
        int dyCCorner = dyRCCorner.y;

        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${r};
          wR += ${s}) {
          float dyR = float(dyRCorner + wR) / ${t}.0;

          if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          for (int wC = 0; wC < ${a}; wC++) {
            float dyC = float(dyCCorner + wC) / ${n}.0;

            if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            float dyValue = getDy(b, idyR, idyC, d);
            int maxPosValue = ${l} - int(getMaxPos(b, idyR, idyC, d));

            // Get the current value, check it against the value from the
            // position matrix.
            int curPosValue = wR * ${a} + wC;
            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);

            dotProd += dyValue * mask;
          }
        }
        setOutput(dotProd);
      }
    `}},xie=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,s=e.strideWidth,r=e.dilationDepth,a=e.dilationHeight,o=e.dilationWidth,i=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=i-1-e.padInfo.front,p=l-1-e.padInfo.top,d=u-1-e.padInfo.left,h=i*l*u-1;this.userCode=`
      const ivec3 pads = ivec3(${c}, ${p}, ${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 < ${i};
           wD += ${r}) {
          float dyD = float(dyDCorner + wD) / ${t}.0;

          if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
            continue;
          }
          int idyD = int(dyD);

          for (int wR = 0; wR < ${l};
              wR += ${a}) {
            float dyR = float(dyRCorner + wR) / ${n}.0;

            if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
                fract(dyR) > 0.0) {
              continue;
            }
            int idyR = int(dyR);

            for (int wC = 0; wC < ${u};
                wC += ${o}) {
              float dyC = float(dyCCorner + wC) / ${s}.0;

              if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
                  fract(dyC) > 0.0) {
                continue;
              }
              int idyC = int(dyC);

              float dyValue = getDy(batch, idyD, idyR, idyC, ch);
              int maxPosValue = ${h} -
                  int(getMaxPos(batch, idyD, idyR, idyC, ch));

              // Get the current value, check it against the value from the
              // position matrix.
              int curPosValue =
                  wD * ${l} * ${u} +
                  wR * ${u} + wC;
              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);

              dotProd += dyValue * mask;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function bie(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=s,p=[1,1,1],d=C.computePool3DInfo(o.shape,i,l,p,u,c),h=new Jx(d,"max",!0),f=n.runWebGLProgram(h,[o],o.dtype),m=new xie(d),g=n.runWebGLProgram(m,[r,f],o.dtype);return n.disposeIntermediateTensorInfo(f),g}var vie={kernelName:o0,backendName:"webgl",kernelFunc:bie};function wie(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a,output:o}=t,i=a;td([a,o],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:p}=s,d=C.computePool2DInfo(i.shape,l,u,1,c,p),h=!0,f=new Dp(d,"max",h),m=n.runWebGLProgram(f,[i],i.dtype),g=new Aie(d),y=n.runWebGLProgram(g,[r,m],i.dtype);return n.disposeIntermediateTensorInfo(m),y}var kie={kernelName:a0,backendName:"webgl",kernelFunc:wie};function Iie(e,t,n,s){let r=new Dp(n,"max",!1),a=s.runWebGLProgram(r,[e],"float32");r=new Dp(n,"max",!0,!0,t);let o=s.runWebGLProgram(r,[e],"float32");return[a,o]}var Sie={kernelName:i0,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s}=e,{filterSize:r,strides:a,pad:o,includeBatchInIndex:i}=t,l=n;v.assert(s.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${s.shape.length}.`);let u=[1,1];v.assert(C.eitherStridesOrDilationsAreOne(a,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${u}'`);let c=C.computePool2DInfo(s.shape,r,a,u,o),[p,d]=Iie(s,i,c,l);return[p,d]}};function Cie(e,t,n,s){let r=v.sizeFromShape(t),o=v.sizeFromShape(e.shape)/r,i=be({inputs:{x:e},attrs:{shape:[o,r]},backend:s}),l=ru(i,"float32","mean",s),u=be({inputs:{x:l},attrs:{shape:n},backend:s});return s.disposeIntermediateTensorInfo(i),s.disposeIntermediateTensorInfo(l),u}var Tie={kernelName:Oo,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s}=e,{keepDims:r,axis:a}=t,o=n,i=s.shape.length,l=v.parseAxisParam(a,s.shape),u=l,c=C.getAxesPermutation(u,i),p=c!=null,d=o.shouldExecuteOnCPU([s]),h=[],f=s;if(p){if(d){let b=o.texData.get(f.dataId).values,w=new Array(i);for(let E=0;E<w.length;E++)w[E]=s.shape[c[E]];let k=Zx(b,s.shape,s.dtype,c,w);f=o.makeTensorInfo(w,s.dtype);let S=o.texData.get(f.dataId);S.values=k}else f=w2(s,c,o);h.push(f),u=C.getInnerMostAxes(u.length,i)}C.assertAxesAreInnerMostDims("sum",u,i);let[m,g]=C.computeOutAndReduceShapes(f.shape,u),y=m;r&&(y=C.expandShapeToKeepDim(m,l));let x=Cie(f,g,y,o);for(let A of h)o.disposeIntermediateTensorInfo(A);return x}};function Nie(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=v.parseAxisParam(a,r.shape),u=l,c=C.getAxesPermutation(u,i),p=r;c!=null&&(p=ts({inputs:{x:r},backend:n,attrs:{perm:c}}),u=C.getInnerMostAxes(u.length,r.shape.length)),C.assertAxesAreInnerMostDims("min",u,i);let[d,h]=C.computeOutAndReduceShapes(p.shape,u),f=v.sizeFromShape(h),m=be({inputs:{x:p},backend:n,attrs:{shape:[-1,f]}}),g=ru(m,m.dtype,"min",n),y;if(o){let x=C.expandShapeToKeepDim(d,l);y=be({inputs:{x:g},backend:n,attrs:{shape:x}})}else y=be({inputs:{x:g},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(p),y}var Eie={kernelName:Mo,backendName:"webgl",kernelFunc:Nie},Rie=l9+`
  return min(a, b);
`,_ie=`
  vec4 result = vec4(min(a, b));
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  `+b2+`
  return result;
`,Die=Rn({opSnippet:Rie,packedOpSnippet:_ie,cpuKernelImpl:kte}),$ie={kernelName:zo,backendName:"webgl",kernelFunc:Die},Pie=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let s=e.length,r=wt(s),a=t.map(u=>u[0]).join(","),o=t.map((u,c)=>u[0]+e[c]).join(","),i=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,s),l=n==="reflect"?0:1;if(s===1){this.userCode=`
        int start = ${a};
        int end = ${o};

        void main() {
          int outC = getOutputCoords();
          if (outC < start) {
            outC = start * 2 - outC - ${l};
          } else if(outC >= end) {
            outC = (end - 1) * 2 - outC + ${l};
          }
          setOutput(getX(outC - start));
        }
      `;return}this.userCode=`
      ${r} start = ${r}(${a});
      ${r} end = ${r}(${o});

      void main() {
        ${r} outC = getOutputCoords();
        for (int i = 0; i < ${s}; i++) {
          if (outC[i] < start[i]) {
            outC[i] = start[i] * 2 - outC[i] - ${l};
          } else if(outC[i] >= end[i]) {
            outC[i] = (end[i] - 1) * 2 - outC[i] + ${l};
          }
        }
        ${r} coords = outC - start;
        setOutput(getX(${i}));
      }
    `}},Fie=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((h,f)=>h[0]+e[f]+h[1]);let s=e.length,r=wt(s),a=t.map(h=>h[0]).join(","),o=t.map((h,f)=>h[0]+e[f]).join(","),i=Qn("rc",s),l=Qn("source",s),u=`${i[s-1]} < ${this.outputShape[s-1]}`,c=s===1?"source":`vec2(${l.slice(-2).join()})`,p=n==="reflect"?0:1,d="";if(s===1){let h=`
        ${r} source = rc;
        if (source < start) {
          source = start * 2 - source - ${p};
        } else if (source >= end) {
          source = (end - 1) * 2 - source + ${p};
        }
        source -= start;
      `;d=`
        ${r} rc = outputLoc;
        ${h}
        result[0] = getChannel(getX(${l.join()}), ${c});
        ${i[s-1]} += 1;
        if(${u}) {
          ${h}
          result[1] = getChannel(getX(${l.join()}), ${c});
        }
      `}else{let h=`
        ${r} source = rc;
        ${r} lt = ${r}(lessThan(source, start));
        ${r} gte = ${r}(greaterThanEqual(source, end));
        ${r} orig = 1 - (lt + gte);
        source = orig * source +
                lt * (start * 2 - source - ${p}) +
                gte * ((end - 1) * 2 - source + ${p});
        source -= start;
      `;d=`
        ${r} rc = outputLoc;
        ${h}
        result[0] = getChannel(getX(${l.join()}), ${c});
        ${i[s-1]} += 1;
        if(${u}) {
          ${h}
          result[1] = getChannel(getX(${l.join()}), ${c});
        }
        rc = outputLoc;
        ${i[s-2]} += 1;
        if(${i[s-2]} < ${this.outputShape[s-2]}) {
          ${h}
          result[2] = getChannel(getX(${l.join()}), ${c});
          ${i[s-1]} += 1;
          if(${u}) {
            ${h}
            result[3] = getChannel(getX(${l.join()}), ${c});
          }
        }
      `}this.userCode=`
      const ${r} start = ${r}(${a});
      const ${r} end = ${r}(${o});

      void main() {
        ${r} outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ${d}
        setOutput(result);
      }
    `}},Oie=({inputs:e,backend:t,attrs:n})=>{let{x:s}=e,{paddings:r,mode:a}=n,o=X().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Fie(s.shape,r,a):new Pie(s.shape,r,a);return t.runWebGLProgram(o,[s],s.dtype)},Mie={kernelName:Lo,backendName:"webgl",kernelFunc:Oie},zie=`if (b == 0.0) return NAN;
  return mod(a, b);`,Lie=`
  vec4 result = mod(a, b);
  vec4 isNaN = vec4(equal(b, vec4(0.0)));
  `+b2+`
  return result;
`,Bie=Rn({opSnippet:zie,packedOpSnippet:Lie}),Wie={kernelName:Nc,backendName:"webgl",kernelFunc:Bie},Vie=class{constructor(e,t,n){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[e,n],this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];

        float r = random(seed);
        float cdf = 0.0;

        for (int i = 0; i < ${t-1}; i++) {
          cdf += getProbs(batch, i);

          if (r < cdf) {
            setOutput(float(i));
            return;
          }
        }

        // If no other event happened, last event happened.
        setOutput(float(${t-1}));
      }
    `}},Uie=`
if (a == b) {
  return 1.0;
};
return a / b;`,Gie=`
  // 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;
`,R9=Rn({opSnippet:Uie,packedOpSnippet:Gie,checkOutOfBounds:!0}),Hie={kernelName:ko,backendName:"webgl",kernelFunc:R9},R7="return a - b;",_9=Rn({opSnippet:R7,packedOpSnippet:R7,supportsComplex:!0,cpuKernelImpl:Bte}),jie={kernelName:ni,backendName:"webgl",kernelFunc:_9};function D9(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{dim:a}=s,o=v.parseAxisParam([a],r.shape),i=E9({inputs:{x:r},backend:n,attrs:{reductionIndices:o,keepDims:!1}}),l=C.expandShapeToKeepDim(i.shape,o),u=be({inputs:{x:i},backend:n,attrs:{shape:l}}),c=_9({inputs:{a:r,b:u},backend:n}),p=C9({inputs:{x:c},backend:n}),d=k2({inputs:{x:p},backend:n,attrs:{axis:o,keepDims:!1}}),h=be({inputs:{x:d},backend:n,attrs:{shape:l}}),f=R9({inputs:{a:p,b:h},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),f}var qie={kernelName:ei,backendName:"webgl",kernelFunc:D9};function Xie(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{numSamples:a,seed:o,normalized:i}=s,l=i?r:D9({inputs:{logits:r},backend:n,attrs:{dim:r.shape.length-1}}),u=l.shape[0],c=l.shape[1],p=new Vie(u,c,a),d=[[o]],h=n.runWebGLProgram(p,[l],"int32",d);return i||n.disposeIntermediateTensorInfo(l),h}var Kie={kernelName:l0,backendName:"webgl",kernelFunc:Xie},Zie=hr+`
  return -x;
`,Yie=`
  vec4 result = -x;
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`;function Jie(e){let{inputs:t,backend:n}=e,{x:s}=t;if(n.shouldExecuteOnCPU([s])){let a=n.texData.get(s.dataId),[o,i]=Ste(a.values,s.shape,s.dtype);return n.makeTensorInfo(i,s.dtype,o)}let r;return X().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new Vi(s.shape,Yie):r=new da(s.shape,Zie),n.runWebGLProgram(r,[s],s.dtype)}var Qie={kernelName:kl,backendName:"webgl",kernelFunc:Jie},ele=dr.nonMaxSuppressionV3Impl;function tle(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l}=s,u=n.readSync(r.dataId),c=n.readSync(a.dataId),{selectedIndices:p}=ele(u,c,o,i,l);return n.makeTensorInfo([p.length],"int32",new Int32Array(p))}var nle={kernelName:Sl,backendName:"webgl",kernelFunc:tle},sle=dr.nonMaxSuppressionV4Impl;function rle(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,padToMaxOutputSize:u}=s,c=n.readSync(r.dataId),p=n.readSync(a.dataId),{selectedIndices:d,validOutputs:h}=sle(c,p,o,i,l,u);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([h]))]}var ale={kernelName:Ec,backendName:"webgl",kernelFunc:rle},ole=dr.nonMaxSuppressionV5Impl;function ile(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=s,c=n.readSync(r.dataId),p=n.readSync(a.dataId),d=o,h=i,f=l,m=u,{selectedIndices:g,selectedScores:y}=ole(c,p,d,h,f,m);return[n.makeTensorInfo([g.length],"int32",new Int32Array(g)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var lle={kernelName:Cl,backendName:"webgl",kernelFunc:ile},ule=class{constructor(e,t,n,s){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int index = round(getIndices(coords.x));
        setOutput(mix(float(${s}), float(${n}),
                      float(index == coords.y)));
      }
    `}},cle=e=>{let{inputs:t,backend:n,attrs:s}=e,{indices:r}=t,{depth:a,onValue:o,offValue:i}=s,l=v.sizeFromShape(r.shape),u=new ule(l,a,o,i),c=be({inputs:{x:r},backend:n,attrs:{shape:[l]}}),p=n.runWebGLProgram(u,[c],r.dtype);n.disposeIntermediateTensorInfo(c);let d=[...r.shape,a],h=be({inputs:{x:p},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(p),h},dle={kernelName:Nl,backendName:"webgl",kernelFunc:cle};function Om(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="complex64"){let r=Mh({inputs:{input:s},backend:n}),a=Om({inputs:{x:r},backend:n}),o=I2({inputs:{input:s},backend:n}),i=Om({inputs:{x:o},backend:n}),l=di({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return zh({attrs:{shape:s.shape,dtype:s.dtype,value:s.dtype==="string"?"":0},backend:n})}var ple={kernelName:Gl,backendName:"webgl",kernelFunc:Om};function $9(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(s.dtype==="complex64"){let r=Mh({inputs:{input:s},backend:n}),a=$9({inputs:{x:r},backend:n}),o=I2({inputs:{input:s},backend:n}),i=Om({inputs:{x:o},backend:n}),l=di({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return zh({attrs:{shape:s.shape,dtype:s.dtype,value:1},backend:n})}var hle={kernelName:Tl,backendName:"webgl",kernelFunc:$9};function fle(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return iy({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let p=iy({inputs:{input:c},backend:n,attrs:{dim:r}});return i.push(p),p}),u=x9({inputs:l,backend:n,attrs:{axis:r}});return i.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var mle={kernelName:El,backendName:"webgl",kernelFunc:fle},gle=class{constructor(e,t,n){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let s=e.length,r=wt(s),a=t.map(l=>l[0]).join(","),o=t.map((l,u)=>l[0]+e[u]).join(","),i=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,s);if(s===1){this.userCode=`
        int start = ${a};
        int end = ${o};

        void main() {
          int outC = getOutputCoords();
          if (outC < start || outC >= end) {
            setOutput(value);
          } else {
            setOutput(getX(outC - start));
          }
        }
      `;return}this.userCode=`
      ${r} start = ${r}(${a});
      ${r} end = ${r}(${o});

      void main() {
        ${r} outC = getOutputCoords();
        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
          setOutput(value);
        } else {
          ${r} coords = outC - start;
          setOutput(getX(${i}));
        }
      }
    `}},yle=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let s=e.length,r=wt(s),a=t.map(f=>f[0]).join(","),o=t.map((f,m)=>f[0]+e[m]).join(","),i=Qn("rc",s),l=Qn("source",s),u=`${i[s-1]} < ${this.outputShape[s-1]}`,c=s===1?"source":`vec2(${l.slice(-2).join()})`,p=[`${r} rc = outputLoc;`,`${i[s-1]} += 1;
       if(${u}) {
      `,s===1?"":`}
       rc = outputLoc;
       ${i[s-2]} += 1;
       if(${i[s-2]} < ${this.outputShape[s-2]}) {`,s===1?"":`  ${i[s-1]} += 1;
         if(${u}) {`],d=s===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",h="";for(let f=0,m=s===1?2:4;f<m;f++)h+=`
        ${p[f]}
        if (${d}) {
          result[${f}] = float(value);
        } else {
          ${r} source = rc - start;
          result[${f}] = getChannel(getX(${l.join()}), ${c});
        }
      `;h+=s===1?"} ":"}}",this.userCode=`
      const ${r} start = ${r}(${a});
      const ${r} end = ${r}(${o});

      void main() {
        ${r} outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ${h}
        setOutput(result);
      }
    `}},P9=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{paddings:a,constantValue:o}=s;if(v.sizeFromShape(r.shape)===0){let u=a.map((c,p)=>c[0]+r.shape[p]+c[1]);return zh({backend:n,attrs:{shape:u,value:o,dtype:r.dtype}})}let i=X().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new yle(r.shape,a,o):new gle(r.shape,a,o),l=[[o]];return n.runWebGLProgram(i,[r],r.dtype,l)},Ale={kernelName:Wo,backendName:"webgl",kernelFunc:P9},xle=`
  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);
`,ble=`
  // 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));
  `+b2+`
  return result;
`,vle=Rn({opSnippet:xle,packedOpSnippet:ble}),wle={kernelName:Vo,backendName:"webgl",kernelFunc:vle};function kle(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=[],u=v.parseAxisParam(a,r.shape),c=u,p=C.getAxesPermutation(c,i),d=r;p!=null&&(d=ts({inputs:{x:r},backend:n,attrs:{perm:p}}),c=C.getInnerMostAxes(c.length,i),l.push(d)),C.assertAxesAreInnerMostDims("prod",c,i);let h;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:g,outDtype:y}=Tte(d.shape,d.dtype,f,c);h=n.makeTensorInfo(g,y,m)}else{let[f,m]=C.computeOutAndReduceShapes(d.shape,c),g=v.sizeFromShape(m),y=be({inputs:{x:d},backend:n,attrs:{shape:[-1,g]}}),x=nh(r.dtype),A=ru(y,x,"prod",n);h=be({inputs:{x:A},backend:n,attrs:{shape:f}}),l.push(y),l.push(A)}if(o){l.push(h);let f=C.expandShapeToKeepDim(h.shape,u);h=be({inputs:{x:h},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),h}var Ile={kernelName:Go,backendName:"webgl",kernelFunc:kle},F9=e=>{let{backend:t,attrs:n}=e,{start:s,stop:r,step:a,dtype:o}=n,i=Nte(s,r,a,o);return t.makeTensorInfo([i.length],o,i)},Sle={kernelName:Rc,backendName:"webgl",kernelFunc:F9},Cle="return 1.0 / x;",Tle=ct({opSnippet:Cle}),Nle={kernelName:_c,backendName:"webgl",kernelFunc:Tle},Ele=hr+`
  return (x < 0.0) ? 0.0 : x;
`,Rle=`
  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;
`,_le=ct({opSnippet:Ele,packedOpSnippet:Rle}),Dle={kernelName:Ho,backendName:"webgl",kernelFunc:_le},$le=hr+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,Ple=`
  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;
`,Fle=ct({opSnippet:$le,packedOpSnippet:Ple}),Ole={kernelName:Xo,backendName:"webgl",kernelFunc:Fle},Mle=class{constructor(e,t,n,s,r){this.variableNames=["A"],this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[s&&t>1?o-1:o,s&&n>1?i-1:i],c=[s&&t>1?t-1:t,s&&n>1?n-1:n],p;r?p="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":p="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec2 effectiveInputOverOutputRatioRC = vec2(
          ${u[0]/c[0]},
          ${u[1]/c[1]});
      const vec2 inputShapeRC = vec2(${o}.0, ${i}.0);

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        ivec2 yRC = coords.yz;

        // Fractional source index.
        vec2 sourceFracIndexRC = ${p};

        // 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);
      }
    `}},zle=class{constructor(e,t,n,s,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[s&&t>1?o-1:o,s&&n>1?i-1:i],c=[s&&t>1?t-1:t,s&&n>1?n-1:n],p;r?p="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":p="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec3 effectiveInputOverOutputRatioRC = vec3(
          ${u[0]/c[0]},
          ${u[1]/c[1]},
          ${u[1]/c[1]});
      const vec3 inputShapeRC = vec3(${o}.0, ${i}.0,
                                     ${i}.0);

      float getAValue(int b, int r, int c, int d) {
        return getChannel(getA(b, r, c, d), vec2(c, d));
      }

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        // Calculate values for next column in yRC.z.
        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);

        // Fractional source index.
        vec3 sourceFracIndexRC = ${p};

        // 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 Lle(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,c=X().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new zle(r.shape,l,u,a,o):new Mle(r.shape,l,u,a,o);return n.runWebGLProgram(c,[r],"float32")}var Ble={kernelName:qo,backendName:"webgl",kernelFunc:Lle},Wle=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,s,r]=t,[,a,o]=e,i=[n&&a>1?s-1:s,n&&o>1?r-1:r],l=[n&&a>1?a-1:a,n&&o>1?o-1:o],u=i[0]/l[0],c=i[1]/l[1],p=1/u,d=1/c,h=Math.ceil(p)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        int r = coords[1];
        int c = coords[2];

        float accumulator = 0.0;

        const float heightScale = float(${u});
        const float widthScale = float(${c});

        const float invHeightScale = float(${p});
        const float invWidthScale = float(${d});

        const int winHeight = int(${h});
        const int winWidth = int(${f});

        // Compute bounds for where in dy we will look
        float startRLerp = floor(float(r) * invHeightScale);
        int startDyR = int(startRLerp - float(winHeight / 2));

        float startCLerp = floor(float(c) * invWidthScale);
        int startDyC = int(startCLerp - float(winWidth / 2));

        // Loop over dy
        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
          int dyR = dyROffset + startDyR;

          // Guard against the window exceeding the bounds of dy
          if (dyR < 0 || dyR >= ${a}) {
            continue;
          }

          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
            int dyC = dyCOffset + startDyC;

            // Guard against the window exceeding the bounds of dy
            if (dyC < 0 || dyC >= ${o}) {
              continue;
            }

            float dxR = float(dyR) * heightScale;
            int topDxRIndex = int(floor(dxR));
            int bottomDxRIndex = int(min(ceil(dxR), ${s-1}.0));
            float dxRLerp = dxR - float(topDxRIndex);
            float inverseDxRLerp = 1.0 - dxRLerp;

            float dxC = float(dyC) * widthScale;
            int leftDxCIndex = int(floor(dxC));
            int rightDxCIndex = int(min(ceil(dxC), ${r-1}.0));
            float dxCLerp = dxC - float(leftDxCIndex);
            float inverseDxCLerp = 1.0 - dxCLerp;

            if (r == topDxRIndex && c == leftDxCIndex) {
              // topLeft
              accumulator +=
                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;
            }

            if (r == topDxRIndex && c == rightDxCIndex) {
              // topRight
              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;
            }

            if (r == bottomDxRIndex && c == leftDxCIndex) {
              // bottomLeft
              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;
            }

            if (r == bottomDxRIndex && c == rightDxCIndex) {
              // bottomRight
              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;
            }
          }
        }
        // End loop over dy

        setOutput(accumulator);
      }
    `}};function Vle(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s,i=new Wle(a.shape,r.shape,o);return n.runWebGLProgram(i,[a],a.dtype)}var Ule={kernelName:c0,backendName:"webgl",kernelFunc:Vle},Gle=class{constructor(e,t,n,s,r){this.variableNames=["A"],this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[s&&t>1?o-1:o,s&&n>1?i-1:i],c=[s&&t>1?t-1:t,s&&n>1?n-1:n],p=s?"0.5":"0.0",d;r?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec2 effectiveInputOverOutputRatioRC = vec2(
          ${u[0]/c[0]},
          ${u[1]/c[1]});
      const vec2 inputShapeRC = vec2(${o}.0, ${i}.0);

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        ivec2 yRC = coords.yz;

        // Fractional source index.
        vec2 sourceFracIndexRC = ${d};

        // Compute the coordinators of nearest neighbor point.
        ivec2 sourceNearestRC = ivec2(
          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${p})));
        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);

        setOutput(newValue);
      }
    `}},Hle=class{constructor(e,t,n,s,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[s&&t>1?o-1:o,s&&n>1?i-1:i],c=[s&&t>1?t-1:t,s&&n>1?n-1:n],p=s?"0.5":"0.0",d;r?d="max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":d="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec3 effectiveInputOverOutputRatioRC = vec3(
          ${u[0]/c[0]},
          ${u[1]/c[1]},
          ${u[1]/c[1]});
      const vec3 inputShapeRC = vec3(${o}.0, ${i}.0,
                                     ${i}.0);

      float getAValue(int b, int r, int c, int d) {
        return getChannel(getA(b, r, c, d), vec2(c, d));
      }

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        // Calculate values for next column in yRC.z.
        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);

        // Fractional source index.
        vec3 sourceFracIndexRC = ${d};

        // Compute the coordinators of nearest neighbor point.
        ivec3 sourceNearestRC = ivec3(
          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${p})));

        // Should we calculate next column and row elements in 2x2 packed cell.
        bool hasNextCol = d < ${l-1};
        bool hasNextRow = coords.z < ${n-1};

        vec4 newValue = vec4(
          getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),
          hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);

        setOutput(newValue);
      }
    `}};function jle(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,c=X().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Hle(r.shape,l,u,a,o):new Gle(r.shape,l,u,a,o);return n.runWebGLProgram(c,[r],r.dtype)}var qle={kernelName:jo,backendName:"webgl",kernelFunc:jle},Xle=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,s,r]=t,[,a,o]=e,i=[n&&a>1?s-1:s,n&&o>1?r-1:r],l=[n&&a>1?a-1:a,n&&o>1?o-1:o],u=i[0]/l[0],c=i[1]/l[1],p=1/u,d=1/c,h=Math.ceil(p)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        int r = coords[1];
        int c = coords[2];

        float accumulator = 0.0;

        const float heightScale = float(${u});
        const float widthScale = float(${c});

        const float invHeightScale = float(${p});
        const float invWidthScale = float(${d});

        const int winHeight = int(${h});
        const int winWidth = int(${f});

        // Compute bounds for where in dy we will look
        float startRLerp = floor(float(r) * invHeightScale);
        int startDyR = int(floor(startRLerp - float(winHeight / 2)));

        float startCLerp = floor(float(c) * invWidthScale);
        int startDyC = int(floor(startCLerp - float(winWidth / 2)));

        // Loop over dy
        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
          int dyR = dyROffset + startDyR;

          // Guard against the window exceeding the bounds of dy
          if (dyR < 0 || dyR >= ${a}) {
            continue;
          }

          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
            int dyC = dyCOffset + startDyC;

            // Guard against the window exceeding the bounds of dy
            if (dyC < 0 || dyC >= ${o}) {
              continue;
            }

            float sourceFracRow =
              float(${i[0]}) *
                (float(dyR) / float(${l[0]}));

            float sourceFracCol =
                float(${i[1]}) *
                  (float(dyC) / float(${l[1]}));

            int sourceNearestRow = int(min(
                float(int(${s}) - 1),
                ${n} ? float(round(sourceFracRow)) :
                                  float(floor(sourceFracRow))));

            int sourceNearestCol = int(min(
                float(int(${r}) - 1),
                ${n} ? float(round(sourceFracCol)) :
                                  float(floor(sourceFracCol))));

            if (r == sourceNearestRow && c == sourceNearestCol) {
              accumulator += getDy(b, dyR, dyC, d);
            }
          }
        }
        // End loop over dy

        setOutput(accumulator);
      }
    `}};function Kle(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s,i=new Xle(a.shape,r.shape,o);return n.runWebGLProgram(i,[a],a.dtype)}var Zle={kernelName:u0,backendName:"webgl",kernelFunc:Kle},Yle=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
        void main() {
          int coord = getOutputCoords();
          setOutput(getX(${e[0]} - coord - 1));
        }
      `;return}let s=o=>t.indexOf(o)!==-1&&e[o]!==1?`${e[o]} - coords[${o}] - 1`:`coords[${o}]`,r=e.map((o,i)=>s(i)).join(","),a=wt(n);this.userCode=`
      void main() {
        ${a} coords = getOutputCoords();
        setOutput(getX(${r}));
      }
    `}},Jle=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=e;let s=Qn("rc",n),r=`${s[n-1]} + 1 < ${this.outputShape[n-1]}`,a=`${s[n-2]} + 1 < ${this.outputShape[n-2]}`,o=wt(n);n===1?this.userCode=`
        void main(){
          int rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = getChannel(getX(${e[0]} - rc - 1),
            ${e[0]} - rc - 1);
          if(${r}){
              result.g = getChannel(getX(${e[0]} - (rc  + 1) - 1),
                ${e[0]} - (rc  + 1) - 1);
          }
          setOutput(result);
        }
      `:this.userCode=`
        void main() {
          ${o} rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = ${i(s.slice())};
          if(${r}){
            result.g = ${l(s.slice())};
          }
          if(${a}) {
            result.b = ${u(s.slice())};
            if(${r}) {
              result.a = ${c(s.slice())};
            }
          }
          setOutput(result);
        }
    `;function i(h){return p(h)}function l(h){return h[n-1]="("+h[n-1]+" + 1)",p(h)}function u(h){return h[n-2]="("+h[n-2]+" + 1)",p(h)}function c(h){return h[n-1]="("+h[n-1]+" + 1)",h[n-2]="("+h[n-2]+" + 1)",p(h)}function p(h){let f=e.map((y,x)=>d(x,h)),m=f.join(","),g=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${g}))`}function d(h,f){return t.indexOf(h)!==-1&&e[h]!==1?`${e[h]} - ${f[h]} - 1`:`${f[h]}`}}};function Qle(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dims:a}=s,o=r.shape.length,i=v.parseAxisParam(a,r.shape);if(o===0)return Ps({inputs:{x:r},backend:n});let l=X().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Jle(r.shape,i):new Yle(r.shape,i);return n.runWebGLProgram(l,[r],r.dtype)}var eue={kernelName:_l,backendName:"webgl",kernelFunc:Qle},tue=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let n=e[1],s=e[2];this.outputShape=e;let r="";typeof t=="number"?r=`float outputValue = ${t.toFixed(2)};`:r=`
        vec3 fill = vec3(${t.join(",")});
        float outputValue = fill[coords[3]];`,this.userCode=`
        void main() {
          ivec4 coords = getOutputCoords();
          int x = coords[2];
          int y = coords[1];
          float coordXFloat = (float(x) - params[0]) * params[3] -
            (float(y) - params[1]) * params[2];
          float coordYFloat = (float(x) - params[0]) * params[2] +
            (float(y) - params[1]) * params[3];
          int coordX = int(round(coordXFloat + params[0]));
          int coordY = int(round(coordYFloat + params[1]));
          ${r}
          if(coordX >= 0 && coordX < ${s} && coordY >= 0 && coordY < ${n}) {
            outputValue = getImage(coords[0], coordY, coordX, coords[3]);
          }
          setOutput(outputValue);
        }
    `}},nue={kernelName:Hl,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:s}=e,{radians:r,fillValue:a,center:o}=t,i=n,l=new tue(s.shape,a),[u,c]=C.getImageCenter(o,s.shape[1],s.shape[2]),p=[[u,c,Math.sin(r),Math.cos(r)]];return i.runWebGLProgram(l,[s],s.dtype,p)}},sue=`
  // OpenGL ES does not support round function.
  // The algorithm is based on banker's rounding.
  float base = floor(x);
  if ((x - base) < 0.5) {
    return floor(x);
  } else if ((x - base) > 0.5) {
    return ceil(x);
  } else {
    if (mod(base, 2.0) == 0.0) {
      return base;
    } else {
      return base + 1.0;
    }
  }
`,rue=ct({opSnippet:sue}),aue={kernelName:Dl,backendName:"webgl",kernelFunc:rue},oue="return inversesqrt(x);",iue=ct({opSnippet:oue,cpuKernelImpl:Ete}),lue={kernelName:Ko,backendName:"webgl",kernelFunc:iue},O9=class{constructor(e,t,n,s,r,a,o=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=a;let i=wt(r.length),l=wt(a.length),u="";n===1?u="i":n===2&&(u="i, j");let c=`getIndices(${u})`,p="";s===1?p="i":s===2&&(p="i, coords[1]");let d=`getUpdates(${p})`,h=t>1?"strides[j]":"strides";this.userCode=`
        ${i} strides = ${i}(${r});

        void main() {
          ${l} coords = getOutputCoords();
          float sum = 0.0;
          bool found = false;
          for (int i = 0; i < ${e}; i++) {
            int flattenedIndex = 0;
            for (int j = 0; j < ${t}; j++) {
              int index = round(${c});
              flattenedIndex += index * ${h};
            }
            if (flattenedIndex == coords[0]) {
              sum += ${d};
              found = true;
            }
          }
          setOutput(mix(getDefaultValue(), sum, float(found)));
        }
      `}};function uue(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r,updates:a}=t,{shape:o}=s,{sliceRank:i,numUpdates:l,sliceSize:u,strides:c,outputSize:p}=C.calculateShapes(a,r,o),d=[p/u,u];if(p===0)return n.makeTensorInfo(o,r.dtype);let h=be({inputs:{x:r},backend:n,attrs:{shape:[l,i]}}),f=be({inputs:{x:a},backend:n,attrs:{shape:[l,u]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),g=new O9(l,i,h.shape.length,f.shape.length,c,d),y=n.runWebGLProgram(g,[f,h,m],f.dtype),x=be({inputs:{x:y},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),x}var cue={kernelName:$l,backendName:"webgl",kernelFunc:uue},due=class{constructor(e,t,n,s){this.variableNames=["sortedSequence","values"],this.customUniforms=[{name:"numInputs",type:"int"}],this.outputShape=[e,n];let r="while (left < right) {",a=`for (int i = 0; i < ${Math.ceil(Math.log2(t+1))}; ++i) { if (left >= right) break;`,o=X().getNumber("WEBGL_VERSION")===2?r:a,i=s==="left"?"<":"<=";this.userCode=`
       int findBound(int batch, float value) {
         int left = 0;
         int right = numInputs;
         int mid;
         ${o}
           mid = (left + right) / 2;
           if (getSortedSequence(batch, mid) ${i} value) {
             left = mid + 1;
           } else {
             right = mid;
           }
         }
         return right;
       }

       void main() {
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
         int valueIndex = coords[1];

         float value = getValues(batch, valueIndex);

         setOutput(float(findBound(batch, value)));
       }
     `}};function pue(e){let{inputs:t,backend:n,attrs:s}=e,{sortedSequence:r,values:a}=t,{side:o}=s,i=new due(r.shape[0],r.shape[1],a.shape[1],o),l=[[r.shape[1]]];return n.runWebGLProgram(i,[r,a],"int32",l)}var hue={kernelName:d0,backendName:"webgl",kernelFunc:pue},fue=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let s,r;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)r="resRC",s="resRC";else{let o=["resRC.x","resRC.y","resRC.z","resRC.w"],i=[],l=[];for(let u=0;u<t.length;u++)l.push(`${o[u]}`),u<e&&i.push(`${o[u]}`);s=i.join(),r=l.join()}let a=wt(n);this.userCode=`
      void main() {
        ${a} resRC = getOutputCoords();
        float cVal = getC(${s});
        if (cVal >= 1.0) {
          setOutput(getA(${r}));
        } else {
          setOutput(getB(${r}));
        }
      }
    `}};function mue(e){let{inputs:t,backend:n}=e,{condition:s,t:r,e:a}=t,o=new fue(s.shape.length,r.shape,r.shape.length);return n.runWebGLProgram(o,[s,r,a],On(r.dtype,a.dtype))}var gue={kernelName:Pl,backendName:"webgl",kernelFunc:mue},yue=`
  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
  // see: https://arxiv.org/abs/1706.02515
  float scaleAlpha = ${C.SELU_SCALEALPHA};
  float scale = ${C.SELU_SCALE};
  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,Aue=ct({opSnippet:yue}),xue={kernelName:Dc,backendName:"webgl",kernelFunc:Aue},bue=id+`
  return 1.0 / (1.0 + exp(-1.0 * x));
`,vue=`
  vec4 result = 1.0 / (1.0 + exp(-1.0 * x));
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`,wue=ct({opSnippet:bue,packedOpSnippet:vue,cpuKernelImpl:_te}),kue={kernelName:Yo,backendName:"webgl",kernelFunc:wue},Iue=`
  if (isnan(x)) { return 0.0; }
  return sign(x);
`,Sue=ct({opSnippet:Iue}),Cue={kernelName:$c,backendName:"webgl",kernelFunc:Sue},Tue=id+`
  return sin(x);
`,Nue=ct({opSnippet:Tue}),Eue={kernelName:Zo,backendName:"webgl",kernelFunc:Nue},Rue=`
  float e2x = exp(x);
  return (e2x - 1.0 / e2x) / 2.0;
`,_ue=ct({opSnippet:Rue}),Due={kernelName:Ol,backendName:"webgl",kernelFunc:_ue},$ue=`
  float epsilon = 1.1920928955078125e-7;
  float threshold = log(epsilon) + 2.0;

  bool too_large = x > -threshold;
  bool too_small = x < threshold;

  float result;
  float exp_x = exp(x);

  if (too_large){
    result = x;
  }
  else if (too_small){
    result = exp_x;
  }
  else{
    result = log(exp_x + 1.0);
  }
  return result;
`,Pue=ct({opSnippet:$ue}),Fue={kernelName:Pc,backendName:"webgl",kernelFunc:Pue},Oue=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,paddings:o}=s;v.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let i=a.reduce((y,x)=>y*x),l=[[0,0]];l.push(...o);for(let y=1+a.length;y<r.shape.length;++y)l.push([0,0]);let u=[],c=P9({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),p=C.getReshaped(c.shape,a,i,!1),d=C.getPermuted(p.length,a.length,!1),h=C.getReshapedPermuted(c.shape,a,i,!1),f=be({inputs:{x:c},backend:n,attrs:{shape:p}}),m=ts({inputs:{x:f},backend:n,attrs:{perm:d}}),g=be({inputs:{x:m},backend:n,attrs:{shape:h}});return u.push(c),u.push(f),u.push(m),u.forEach(y=>n.disposeIntermediateTensorInfo(y)),g},Mue={kernelName:Ml,backendName:"webgl",kernelFunc:Oue};function zue(e){let{inputs:t,backend:n}=e,{indices:s,values:r,denseShape:a,defaultValue:o}=t;if(a.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
         ${a.shape}`);if(s.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
         ${s.shape}`);if(r.shape.length!==1)throw new Error(`Values must be a vector, saw:
         ${r.shape}`);if(o.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
        ${o.shape}`);let i=n.readSync(s.dataId),l=n.readSync(r.dataId),u=n.readSync(a.dataId),c=n.readSync(o.dataId)[0],[p,d,h,f,m]=$te(i,s.shape,s.dtype,l,r.dtype,u,c);return[n.makeTensorInfo(d,s.dtype,p),n.makeTensorInfo([d[0]],r.dtype,h),n.makeTensorInfo([f.length],"bool",new Uint8Array(f.map(g=>Number(g)))),n.makeTensorInfo([m.length],s.dtype,new Int32Array(m))]}var Lue={kernelName:qp,backendName:"webgl",kernelFunc:zue};function Bue(e){let{inputs:t,backend:n}=e,{inputIndices:s,inputShape:r,newShape:a}=t;if(s.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape ${s.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape ${r.shape}`);if(a.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${a.shape}`);let o=Array.from(n.readSync(r.dataId)),i=n.readSync(s.dataId),l=Array.from(n.readSync(a.dataId)),[u,c,p]=Pte(i,s.shape,s.dtype,o,l);return[n.makeTensorInfo(c,s.dtype,u),n.makeTensorInfo([p.length],a.dtype,new Int32Array(p))]}var Wue={kernelName:Fc,backendName:"webgl",kernelFunc:Bue};function Vue(e){let{inputs:t,backend:n}=e,{data:s,indices:r,segmentIds:a}=t;if(s.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
              ${r.shape}`);if(a.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
              ${a.shape}`);let o=n.readSync(s.dataId),i=n.readSync(r.dataId),l=n.readSync(a.dataId),[u,c]=r9(o,s.shape,s.dtype,i,l,!0);return n.makeTensorInfo(c,s.dtype,u)}var Uue={kernelName:Xp,backendName:"webgl",kernelFunc:Vue};function Gue(e){let{inputs:t,backend:n}=e,{data:s,indices:r,segmentIds:a}=t;if(s.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
             ${r.shape}`);if(a.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
             ${a.shape}`);let o=n.readSync(s.dataId),i=n.readSync(r.dataId),l=n.readSync(a.dataId),[u,c]=r9(o,s.shape,s.dtype,i,l);return n.makeTensorInfo(c,s.dtype,u)}var Hue={kernelName:Kp,backendName:"webgl",kernelFunc:Gue};function jue(e){let{inputs:t,backend:n,attrs:s}=e,{sparseIndices:r,sparseValues:a,defaultValue:o}=t,{outputShape:i}=s,{sliceRank:l,numUpdates:u,sliceSize:c,strides:p,outputSize:d}=C.calculateShapes(a,r,i),h=!1;if(a.dtype==="string"){let y=n.bufferSync(r),x=n.bufferSync(a),A=v.decodeString(n.readSync(o.dataId)[0]),b=Rte(y,x,i,d,c,u,l,p,A,h);return n.makeTensorInfo(i,b.dtype,b.values)}let f=new O9(u,l,r.shape.length,a.shape.length,p,[d,1],h),m=n.runWebGLProgram(f,[a,r,o],a.dtype),g=be({inputs:{x:m},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(m),g}var que={kernelName:Zp,backendName:"webgl",kernelFunc:jue};function Xue(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{numOrSizeSplits:a,axis:o}=s,i=v.parseAxisParam(o,r.shape)[0],l=C.prepareSplitSize(r,a,i),u=r.shape.length,c=new Array(u).fill(0),p=r.shape.slice();return l.map(d=>{let h=[...p];h[i]=d;let f=ld({inputs:{x:r},backend:n,attrs:{begin:c,size:h}});return c[i]+=d,f})}var Kue={kernelName:zl,backendName:"webgl",kernelFunc:Xue},_7="return sqrt(x);",Zue=ct({opSnippet:_7,packedOpSnippet:_7,cpuKernelImpl:Fte}),Yue={kernelName:Jo,backendName:"webgl",kernelFunc:Zue},Jue="return x * x;",Que=ct({opSnippet:Jue}),ece={kernelName:Oc,backendName:"webgl",kernelFunc:Que},D7="return (a - b) * (a - b);",tce=Rn({opSnippet:D7,packedOpSnippet:D7}),nce={kernelName:ti,backendName:"webgl",kernelFunc:tce};function sce({inputs:e,attrs:t,backend:n}){let{x:s}=e,r=hr+`
    return x > 0.0 ? 1.0 : float(${t.alpha});
  `,a=new da(s.shape,r);return n.runWebGLProgram(a,[s],s.dtype)}var rce={kernelName:ri,backendName:"webgl",kernelFunc:sce},ace=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let s=n.length,r=wt(n.length),a=wt(n.length),o="";if(s===1)o="coords * strides + begin";else{let i=0;o=n.map((l,u)=>(i++,n.length===1?`coords * strides[${u}] + begin[${u}]`:`coords[${i-1}] * strides[${u}] + begin[${u}]`)).join(",")}this.userCode=`
      ${r} begin = ${r}(${e});
      ${r} strides = ${r}(${t});

      void main() {
        ${a} coords = getOutputCoords();
        setOutput(getX(${o}));
      }
    `}};function oce(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,end:o,strides:i,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:p,shrinkAxisMask:d}=s,{finalShapeSparse:h,finalShape:f,isIdentity:m,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Ut.sliceInfo(r.shape,a,o,i,l,u,c,p,d),w;if(m)w=be({inputs:{x:r},backend:n,attrs:{shape:f}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let S=Ut.computeOutShape(x,A,b),E=ld({inputs:{x:r},backend:n,attrs:{begin:x,size:S}});w=be({inputs:{x:E},backend:n,attrs:{shape:f}}),n.disposeIntermediateTensorInfo(E)}else if(n.shouldExecuteOnCPU([r])){let E=n.readSync(r.dataId),R=Le(r.shape,r.dtype,E),P=Ote(h,R,b,x);w=n.makeTensorInfo(f,r.dtype,P.values)}else{let E=new ace(x,b,h);w=n.runWebGLProgram(E,[r],r.dtype)}let k=be({inputs:{x:w},backend:n,attrs:{shape:f}});return n.disposeIntermediateTensorInfo(w),k}var ice={kernelName:Ll,backendName:"webgl",kernelFunc:oce};function lce(e){let{inputs:t,backend:n,attrs:s}=e,{separator:r,nGramWidths:a,leftPad:o,rightPad:i,padWidth:l,preserveShortSequences:u}=s,{data:c,dataSplits:p}=t,d=n.readSync(c.dataId),h=n.readSync(p.dataId),[f,m]=Mte(d,h,r,a,o,i,l,u);return[n.makeTensorInfo([f.length],"string",f),n.makeTensorInfo(p.shape,"int32",m)]}var uce={kernelName:Mc,backendName:"webgl",kernelFunc:lce};function cce(e){let{inputs:t,backend:n,attrs:s}=e,{skipEmpty:r}=s,{input:a,delimiter:o}=t;if(a.dtype!=="string")throw new Error("Input must be of datatype string");if(a.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${a.shape}`);if(o.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${o.shape}`);let i=n.readSync(a.dataId),l=n.readSync(o.dataId)[0],[u,c,p]=zte(i,l,r),d=c.length;return[n.makeTensorInfo([d,2],"int32",u),n.makeTensorInfo([d],"string",c),n.makeTensorInfo([2],"int32",new Int32Array(p))]}var dce={kernelName:Yp,backendName:"webgl",kernelFunc:cce};function pce(e){let{inputs:t,backend:n,attrs:s}=e,{numBuckets:r}=s,{input:a}=t;if(a.dtype!=="string")throw new Error("Input must be of datatype string");if(r<=0)throw new Error("Number of buckets must be at least 1");let o=n.readSync(a.dataId),i=Lte(o,r);return n.makeTensorInfo(a.shape,"int32",i)}var hce={kernelName:Jp,backendName:"webgl",kernelFunc:pce},fce="return tan(x);",mce=ct({opSnippet:fce}),gce={kernelName:Bl,backendName:"webgl",kernelFunc:mce},yce=`
  float e2x = exp(-2.0 * abs(x));
  return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,Ace=ct({opSnippet:yce}),xce={kernelName:si,backendName:"webgl",kernelFunc:Ace},bce=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let a=0;a<n.length;a++)n[a]=e[a]*t[a];this.outputShape=n,this.rank=n.length;let s=wt(this.rank),r=vce(e);this.userCode=`
      void main() {
        ${s} resRC = getOutputCoords();
        setOutput(getA(${r}));
      }
    `}};function vce(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],s=[];for(let r=0;r<e.length;r++)s.push(`imod(${n[r]}, ${e[r]})`);return s.join()}function M9(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reps:a}=s;if(r.dtype==="string"||r.shape.length>5){let l=n.readSync(r.dataId),u=r.dtype==="string"?l.map(d=>v.decodeString(d)):l,c=Le(r.shape,r.dtype,u),p=Wte(c,a);return n.makeTensorInfo(p.shape,p.dtype,p.values)}let o=new bce(r.shape,a);return n.runWebGLProgram(o,[r],r.dtype)}var wce={kernelName:ba,backendName:"webgl",kernelFunc:M9},kce=class{constructor(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"negativeInf",type:"float"},{name:"dir",type:"int"},{name:"inc",type:"int"}],this.outputShape=e,this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
         int elemIdx = coords[1];

         // We compare elements pair-wise within a group of size 2 * inc.
         // The comparing rule for each group alternates between ascending
         // and descending. Within each group, we compare each pair at
         // positions i and i+inc. To decide whether an element at position i
         // is x0 or x1, we mod it by 2 * inc, if the result is smaller than
         // inc, it is in the first half of the group, we denote it as x0,
         // otherwise we denote it as x1.
         // For example, as shown in the Bitonic top K paper referenced above,
         // Figure5(a) shows that element[1] is in the
         // second half of the group when group size is 2, but it is in the
         // first half of the group when group size is 4.

         bool isFirstInPair = imod(elemIdx, 2 * inc) < inc;
         int i = isFirstInPair ? elemIdx : elemIdx - inc;

         int i0 = firstPass == 1 ? i : int(getIndices(batch, i));
         int i1 = firstPass == 1 ? i + inc : int(getIndices(batch, i + inc));
         float x0 = i0 < n ? getX(batch, i0) : negativeInf;
         float x1 = i1 < n ? getX(batch, i1) : negativeInf;

         // Denotes which direction indices are in (ascending or descending).
         bool reverse = imod(elemIdx, 2 * dir) >= dir;
         bool isGreater = x0 > x1 || (x0 == x1 && i1 > i0);
         if (reverse == isGreater) { // Elements in opposite order of direction
           int iTemp = i0;
           i0 = i1;
           i1 = iTemp;
         }
         if (isFirstInPair) {
            setOutput(float(i0));
         } else {
            setOutput(float(i1));
         }
       }
     `}},Ice=class{constructor(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"k",type:"int"}],this.outputShape=e,this.userCode=`
    void main() {
         // Takes max of indices (0, k), (1, k + 1), (2, k + 2) ...
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
         int elemIdx = coords[1];

         // The output size is half of the previous size.
         // If the previous sequence is | | | | _ _ _ _  | | | |  _ _ _ _ (k=4),
         // we only need to output the indices at positions |, the indices at
         // positions _ can be thrown away, see Figure5(b) After Phase 2
         // (Merge phase) in the Bitonic Top K paper referenced above.
         // For example, the paper shows we only need to output the orange bars.
         // The output sequence should look like this | | | | | | | |.
         // Because the sequence is halved, to map the output index back
         // to the previous sequence to find the corresponding value,
         // we need to double the index. When we double the index,
         // we basically interpolate a position, so 2i looks like
         // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k position
         // of each 2k positions by - elemIdx % k. E.g. for output at
         // index 4,5,6,7, we want to get the corresponding element at
         // original index 8,9,10,11, for output at index 8,9,10,11,
         // we want to get the corresponding element at original index
         // 16,17,18,19, so on and so forth.

         int i = elemIdx < k ? elemIdx : (elemIdx * 2 - imod(elemIdx, k));
         int i0 = firstPass == 1 ? i : int(getIndices(batch, i));
         int i1 = firstPass == 1 ? i + k : int(getIndices(batch, i + k));

         float x0 = getX(batch, i0);
         float x1 = i1 < n ? getX(batch, i1) : x0;

         setOutput(x0 >= x1 ? float(i0) : float(i1));
       }
     `}};function Di(e,t){t!==null&&e.disposeIntermediateTensorInfo(t)}function $7(e){let t=1;for(;t<e;)t*=2;return t}function Sce(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{k:a,sorted:o}=s,i=X().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),l=X().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),u=r.shape,c=u[u.length-1];if(n.shouldExecuteOnCPU([r])||c<i||a>l){let P=n.readSync(r.dataId),[_,$]=Vte(P,u,r.dtype,a,o);return[n.makeTensorInfo(_.shape,_.dtype,_.values),n.makeTensorInfo($.shape,$.dtype,$.values)]}if(a===0)return u[u.length-1]=0,[n.makeTensorInfo(u,r.dtype,[]),n.makeTensorInfo(u,"int32",[])];if(c===1)return[r,zh({attrs:{shape:u,dtype:"int32",value:0},backend:n})];let p=n.texData.get(r.dataId),d=p!==null&&p.isPacked,h=d?n.unpackTensor(r):r,m=v.sizeFromShape(u)/c,g=be({inputs:{x:h},attrs:{shape:[m,c]},backend:n});d&&Di(n,h);let y=$7(a),x=$7(c),A=null,b=()=>A===null?[g,g]:[g,A],w=(P,_,$)=>{let T=b(),F=new kce($),q=[[c],[A===null?1:0],[Number.NEGATIVE_INFINITY],[P],[_]],z=A;A=n.runWebGLProgram(F,T,"int32",q),Di(n,z)};for(let P=1;P<y;P*=2){let _=P*2;for(let $=P;$>=1;$/=2)w(_,$,[m,x])}for(let P=x;P>y;P/=2){let _=b(),$=new Ice([m,P/2]),F=[[c],[A===null?1:0],[y]],G=A;A=n.runWebGLProgram($,_,"int32",F),Di(n,G);let q=y/2,z=q*2;for(let Z=q;Z>=1;Z/=2)w(z,Z,A.shape)}let k=A;A=ld({inputs:{x:A},backend:n,attrs:{begin:0,size:[m,a]}}),Di(n,k);let S=N9({inputs:{x:g,indices:A},backend:n,attrs:{axis:1,batchDims:1}});Di(n,g);let E=u.slice(0,-1);E.push(a),k=A,A=be({inputs:{x:A},attrs:{shape:E},backend:n}),Di(n,k);let R=S;return S=be({inputs:{x:S},attrs:{shape:E},backend:n}),Di(n,R),[S,A]}var Cce={kernelName:Wl,backendName:"webgl",kernelFunc:Sce},Tce=class{constructor(e,t,n,s,r,a){this.variableNames=["Image","Transforms"],this.outputShape=a;let o=n==="nearest"?1:2,i;switch(s){case"constant":i=1;break;case"reflect":i=2;break;case"wrap":i=3;break;case"nearest":i=4;break;default:i=1;break}this.userCode=`
            float mapCoord(float outCoord, float len) {
              float inCoord = outCoord;
              if(${i} == 2) {
                if (inCoord < 0.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz2 = 2.0 * len;
                    if (inCoord < sz2) {
                      inCoord = sz2 * float(int(float(-inCoord / sz2))) +
                      inCoord;
                    }
                    inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0;
                  }
                } else if (inCoord > len - 1.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz2 = 2.0 * len;
                    inCoord -= sz2 * float(int(float(inCoord / sz2)));
                    if (inCoord >= len) {
                      inCoord = sz2 - inCoord - 1.0;
                    }
                  }
                }
                return clamp(inCoord, 0.0, len - 1.0);
              } else if (${i} == 3) {
                if (inCoord < 0.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz = len - 1.0;
                    inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);
                  }
                } else if (inCoord > len - 1.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz = len - 1.0;
                    inCoord -= len * float(int(float(inCoord / sz)));
                  }
                }
                return clamp(inCoord, 0.0, len - 1.0);
              } else if (${i} == 4) {
                return clamp(outCoord, 0.0, len - 1.0);
              } else {
                return outCoord;
              }
            }

            float readWithFillValue(int batch, int coordY, int coordX,
              int channel) {
              float outputValue;
              if (0 <= coordY && coordY < ${e} && 0 <= coordX && coordX < ${t}) {
                  outputValue = getImage(batch, coordY, coordX, channel);
              } else {
                outputValue = float(${r});
              }
              return outputValue;
            }

            void main() {
              ivec4 coords = getOutputCoords();
              float outputValue;
              int batch = coords[0];
              int x = coords[2];
              int y = coords[1];
              int channel = coords[3];
              float xf = float(x);
              float yf = float(y);
              float a1 = getTransforms(batch, 0);
              float a2 = getTransforms(batch, 1);
              float a3 = getTransforms(batch, 2);
              float b1 = getTransforms(batch, 3);
              float b2 = getTransforms(batch, 4);
              float b3 = getTransforms(batch, 5);
              float c1 = getTransforms(batch, 6);
              float c2 = getTransforms(batch, 7);
              float projection = c1 * xf + c2 * yf + 1.0;
              if (projection == 0.0) {
                outputValue = float(${r});
              } else {
                float inX = (a1 * xf + a2 * yf + a3) / projection;
                float inY = (b1 * xf + b2 * yf + b3) / projection;
                float mapX = mapCoord(inX, float(${t}));
                float mapY = mapCoord(inY, float(${e}));

                if (${o} == 1) {
                  int coordY = int(round(mapY));
                  int coordX = int(round(mapX));
                  outputValue = readWithFillValue(batch, coordY, coordX,
                    channel);
                } else {
                  float yFloor = floor(mapY);
                  float xFloor = floor(mapX);
                  float yCeil = yFloor + 1.0;
                  float xCeil = xFloor + 1.0;
                  float valueYFloor = (xCeil - mapX) *
                  readWithFillValue(batch, int(yFloor), int(xFloor), channel) +
                  (mapX - xFloor) *
                  readWithFillValue(batch, int(yFloor), int(xCeil), channel);
                  float valueYCeil = (xCeil - mapX) *
                  readWithFillValue(batch, int(yCeil), int(xFloor), channel) +
                  (mapX - xFloor) *
                  readWithFillValue(batch, int(yCeil), int(xCeil), channel);
                  outputValue = (yCeil - mapY) * valueYFloor +
                  (mapY - yFloor) * valueYCeil;
                }
              }
              setOutput(outputValue);
            }
        `}};function Nce(e){let{inputs:t,backend:n,attrs:s}=e,{image:r,transforms:a}=t,{interpolation:o,fillMode:i,fillValue:l,outputShape:u}=s,[c,p,d,h]=r.shape,[f,m]=u!=null?u:[p,d],g=[c,f,m,h],y=new Tce(p,d,o,i,l,g);return n.runWebGLProgram(y,[r,a],"float32")}var Ece={kernelName:Vl,backendName:"webgl",kernelFunc:Nce};function Rce(e){let{inputs:t,attrs:n,backend:s}=e,{axis:r}=n,{x:a}=t;td(a,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let o=s.readSync(a.dataId),{outputValues:i,outputShape:l,indices:u}=Ute(o,r,a.shape,a.dtype);return[s.makeTensorInfo(l,a.dtype,i),s.makeTensorInfo([u.length],"int32",u)]}var _ce={kernelName:p0,backendName:"webgl",kernelFunc:Rce};function Dce(e){let{inputs:t,backend:n,attrs:s}=e,{value:r}=t,{axis:a}=s;a<0&&(a+=r.shape.length);let o=r,i=o.shape.length,l=r.shape[a],u=new Array(i-1),c=0;for(let m=0;m<i;m++)m!==a&&(u[c++]=o.shape[m]);let p=[],d=new Array(i).fill(0),h=o.shape.slice();h[a]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[a]=m;let g=ld({inputs:{x:o},backend:n,attrs:{begin:d,size:h}}),y=be({inputs:{x:g},backend:n,attrs:{shape:u}});f[m]=y,p.push(g)}return p.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var $ce={kernelName:Ul,backendName:"webgl",kernelFunc:Dce},Pce=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,s=e.batchSize,r=e.inSize,a=e.numSegments,o=a*Math.ceil(r/n);this.outputShape=[s,o];let i="0.0",l="sumValue",u=Math.floor(n/4)*4,c=n%4,p=`
        sumValue += dot(values, segFilter);
    `,d="";r%n>0&&(d=`
        if (inIdx < 0 || inIdx >= ${r}) {
          return initializationValue;
        }
      `);let h="";r%n>0&&(h=`
        if (inIdx < 0 || inIdx >= ${r}) {
          return -1.0;
        }
      `),this.userCode=`
      const float initializationValue = ${i};

      float getValue(int batch, int inIdx) {
        ${d}
        return getX(batch, inIdx);
      }

      float getSegmentIdAtIndex(int inIdx) {
        ${h}
        return getSegmentIds(inIdx);
      }

      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = int(floor(float(outIdx) / float(
          ${a})) * float(${n}));
        int currentSeg = int(mod(float(outIdx), float(${a})));

        float sumValue = 0.0;

        for (int i = 0; i < ${u}; i += 4) {
          int inIdx = inOffset + i;
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0
          );

          ${p}
        }

        int inIdx = inOffset + ${u};
        if (${c===1}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            initializationValue,
            initializationValue,
            initializationValue
          );

          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            0,
            0,
            0
          );

          ${p}
        } else if (${c===2}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            initializationValue,
            initializationValue
          );

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
              0,
              0
          );

          ${p}
        } else if (${c===3}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            initializationValue
          );

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
            0
          );

          ${p}
        }
        setOutput(${l});
      }
    `}};function Fce(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,segmentIds:a}=t,{numSegments:o}=s,i=r.shape.length,l=[],u=0,c=C.getAxesPermutation([u],i),p=r;c!=null&&(p=ts({inputs:{x:r},backend:n,attrs:{perm:c}}),l.push(p),u=C.getInnerMostAxes(1,i)[0]);let d=C.segment_util.computeOutShape(p.shape,u,o),h=v.sizeFromShape([p.shape[u]]),f=be({inputs:{x:p},backend:n,attrs:{shape:[-1,h]}});l.push(f);let m=nh(r.dtype),g=(b,w,k,S,E)=>{let R=b.shape[0],P=b.shape[1],_=C.segment_util.segOpComputeOptimalWindowSize(P,E),$={windowSize:_,inSize:P,batchSize:R,numSegments:E},T=new Pce($,w),F=n.compileAndRun(T,[b,k],S);if(l.push(F),F.shape[1]===E)return F;let G=F9({backend:n,attrs:{start:0,stop:E,step:1,dtype:"float32"}}),q=M9({inputs:{x:G},backend:n,attrs:{reps:[P/_]}});return l.push(G),l.push(q),g(F,w,q,S,E)},y=g(f,"unsortedSegmentSum",a,m,o),x=be({inputs:{x:y},backend:n,attrs:{shape:d}}),A=x;if(c!=null){l.push(x);let b=C.getUndoAxesPermutation(c);A=ts({inputs:{x:A},backend:n,attrs:{perm:b}})}return l.forEach(b=>n.disposeIntermediateTensorInfo(b)),A}var Oce={kernelName:Qp,backendName:"webgl",kernelFunc:Fce},Mce=[zne,Bne,Une,jne,Xne,Yne,Qne,tse,ase,ise,cse,hse,gse,bse,kse,Sse,Tse,_se,$se,Fse,Lse,jse,Xse,Zse,nre,rre,lre,xne,dre,gre,bre,Cre,Nre,Rre,Dre,Pre,Mre,Bre,Ure,Hre,qre,Kre,Jre,eae,rae,oae,uae,pae,fae,Aae,wae,Cae,Eae,Dae,$ae,Fae,Mae,Lae,Wae,Uae,qae,Zae,Qae,toe,roe,ioe,doe,moe,Ane,yoe,fre,boe,koe,Coe,vne,Roe,Poe,Ooe,Boe,Uoe,qoe,Zoe,eie,rie,iie,uie,hie,mie,yie,vie,kie,Sie,Tie,Eie,$ie,Mie,Wie,Kie,Cne,Qie,nle,ale,lle,Jse,dle,hle,mle,Ale,wle,kne,Ile,Sle,Qse,Hie,Nle,Dle,Ole,Nne,Ble,Ule,qle,Zle,eue,nue,aue,lue,cue,hue,gue,xue,kue,Cue,Eue,Due,Gse,qie,Fue,Mue,Lue,Wue,Uue,Hue,que,Kue,Yue,ece,nce,rce,ice,uce,dce,hce,jie,Fne,gce,xce,wce,Cce,Ece,One,_ce,$ce,Oce,ple];for(let e of Mce)cr(e);var Ht;(function(e){e[e.float32=0]="float32",e[e.int32=1]="int32",e[e.bool=2]="bool",e[e.string=3]="string",e[e.complex64=4]="complex64"})(Ht||(Ht={}));var Pp;(function(e){e[e.linear=0]="linear",e[e.relu=1]="relu",e[e.relu6=2]="relu6",e[e.prelu=3]="prelu",e[e.leakyrelu=4]="leakyrelu",e[e.sigmoid=5]="sigmoid",e[e.elu=6]="elu"})(Pp||(Pp={}));var z9;function zce(e){z9=e.wasm.cwrap(Ya,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function Lce(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t;if(r.dtype!=="float32"||a.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=s,d=n.dataIdMap.get(r.dataId).id,h=n.dataIdMap.get(a.dataId).id,f=0;if(o!=null){let E=n.dataIdMap.get(o.dataId);if(E.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${E.shape.length}.`);f=E.id}let m=i==null?0:n.dataIdMap.get(i.dataId).id,g=Pp[c];if(g==null)throw new Error(`${c} activation not yet supported for FusedConv2D in the wasm backend.`);let y=l?r.shape[2]:r.shape[1],x=u?a.shape[1]:a.shape[2],A=ql.assertAndGetBroadcastShape(r.shape.slice(0,-2),a.shape.slice(0,-2)),b=n.makeOutput([...A,y,x],r.dtype),w=n.dataIdMap.get(b.dataId).id,k=new Uint8Array(new Int32Array(r.shape).buffer),S=new Uint8Array(new Int32Array(a.shape).buffer);return z9(d,k,r.shape.length,h,S,a.shape.length,l,u,g,f,m,p||0,w),b}var Bce={kernelName:Ya,backendName:"wasm",setupFunc:zce,kernelFunc:Lce};function In(e,t){let n;function s(a){n=a.wasm.cwrap(e,null,["number","number","number"])}function r(a){let{backend:o,inputs:{x:i}}=a,l=o.dataIdMap.get(i.dataId).id,u=o.makeOutput(i.shape,t||i.dtype),c=o.dataIdMap.get(u.dataId).id;return v.sizeFromShape(u.shape)===0||n(l,Ht[i.dtype],c),u}return{kernelName:e,backendName:"wasm",setupFunc:s,kernelFunc:r}}var Wce=In(ol);function _n(e,t,n){let s;function r(o){s=o.wasm.cwrap(e,null,["number","array","number","number","array","number","number","number"])}function a(o){let{backend:i,inputs:l}=o,{a:u,b:c}=l,p=i.dataIdMap.get(u.dataId).id,d=i.dataIdMap.get(c.dataId).id,h=n!=null?n:u.dtype,f=C.assertAndGetBroadcastShape(u.shape,c.shape),m=i.makeOutput(f,h);if(v.sizeFromShape(f)===0)return m;let g=new Uint8Array(new Int32Array(u.shape).buffer),y=new Uint8Array(new Int32Array(c.shape).buffer),x=i.dataIdMap.get(m.dataId).id;return(()=>s(p,g,u.shape.length,d,y,c.shape.length,Ht[u.dtype],x))(),m}return{kernelName:e,backendName:"wasm",setupFunc:r,kernelFunc:a}}var Vce=!0,Uce=_n(Aa,Vce),L9;function Gce(e){L9=e.wasm.cwrap(co,null,["array","number","number","number"])}function Hce(e){let{inputs:t,backend:n}=e,s=n.makeOutput(t[0].shape,t[0].dtype);if(v.sizeFromShape(s.shape)===0)return s;let r=t.map(i=>n.dataIdMap.get(i.dataId).id),a=new Uint8Array(new Int32Array(r).buffer),o=n.dataIdMap.get(s.dataId).id;return L9(a,r.length,Ht[s.dtype],o),s}var jce={kernelName:co,backendName:"wasm",setupFunc:Gce,kernelFunc:Hce};function S2(e){let{inputs:{x:t},backend:n}=e,s=n.makeOutput(t.shape,t.dtype),r=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(s).set(r),s}var qce={kernelName:Ro,backendName:"wasm",kernelFunc:S2},B9;function Xce(e){B9=e.wasm.cwrap(Gr,null,["number","array","number","number","number","array","number"])}function io(e){let{inputs:t,backend:n,attrs:s}=e,[r,a]=Zce(t.x.shape,s.perm),o=!0;for(let f=0;f<a.length;f++)a[f]!==f&&(o=!1);let i=Kce(t.x.shape,s.perm),l={dataId:t.x.dataId,shape:r,dtype:t.x.dtype};if(o){let f=S2({inputs:t,backend:n});return f.shape=i,f}let u=n.makeOutput(i,l.dtype),c=n.dataIdMap.get(l.dataId).id,p=n.dataIdMap.get(u.dataId).id,d=new Uint8Array(new Int32Array(a).buffer),h=new Uint8Array(new Int32Array(l.shape).buffer);return B9(c,h,l.shape.length,Ht[l.dtype],p,d,a.length),u}function Kce(e,t){let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];return n}function Zce(e,t){let n=[],s=[];for(let r=0;r<e.length;++r)e[r]!==1&&n.push(e[r]),e[t[r]]!==1&&s.push(t[r]);for(let r=0;r<s.length;++r){let a=-1;for(let o=0;o<s.length;++o)s[o]>=r&&(a===-1||s[a]>s[o])&&(a=o);s[a]=r}return[n,s]}var Yce={kernelName:Gr,backendName:"wasm",kernelFunc:io,setupFunc:Xce};function pi(e,t,n){let s=e.shape,r=e.shape.length,a=v.parseAxisParam(t,s),o=a,i=C.getAxesPermutation(o,r),l=null,u=!1;if(i!=null){let c=new Array(r);for(let h=0;h<c.length;h++)c[h]=s[i[h]];o=C.getInnerMostAxes(o.length,r),l=io({inputs:{x:e},attrs:{perm:i},backend:n});let p=n.dataIdMap.get(e.dataId).id;n.dataIdMap.get(l.dataId).id!==p&&(u=!0)}return{transposed:l,originalAxes:a,axes:o,inputWasTransposed:u}}var W9;function Jce(e){W9=e.wasm.cwrap(hc,null,["number, number, number"])}function Qce(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,l=t.dataIdMap.get(o.dataId).id,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=pi(o,r,t);if(h){let A=t.dataIdMap.get(c.dataId).id;u=c,l=A}let f=u.shape.length;C.assertAxesAreInnerMostDims("all",p,f);let[m,g]=C.computeOutAndReduceShapes(u.shape,p),y=v.sizeFromShape(g),x=t.makeOutput(m,o.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;W9(l,y,A)}if(h&&t.disposeData(c.dataId),a){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var ede={kernelName:hc,backendName:"wasm",setupFunc:Jce,kernelFunc:Qce},V9;function tde(e){V9=e.wasm.cwrap(fc,null,["number, number, number"])}function nde(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,l=t.dataIdMap.get(o.dataId).id,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=pi(o,r,t);if(h){let A=t.dataIdMap.get(c.dataId).id;u=c,l=A}let f=u.shape.length;C.assertAxesAreInnerMostDims("any",p,f);let[m,g]=C.computeOutAndReduceShapes(u.shape,p),y=v.sizeFromShape(g),x=t.makeOutput(m,o.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;V9(l,y,A)}if(h&&t.disposeData(c.dataId),a){let 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lde(e){let{inputs:t,attrs:n,backend:s}=e,r=t.x,a=s.dataIdMap.get(r.dataId).id,{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=n,c=C.computePool2DInfo(r.shape,o,i,1,l,u),p=c.filterHeight,d=c.filterWidth,h=c.padInfo.top,f=c.padInfo.right,m=c.padInfo.bottom,g=c.padInfo.left,y=c.strideHeight,x=c.strideWidth,A=c.inChannels;if(c.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${c.dataFormat}'. 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transposeB=${i} must match.`);let b=o?[g,c,d]:[g,d,c],w=i?[y,h,p]:[y,p,h],k=hs({inputs:{x:r},backend:n,attrs:{shape:b}}),S=hs({inputs:{x:a},backend:n,attrs:{shape:w}}),E=n.dataIdMap.get(k.dataId).id,R=n.dataIdMap.get(S.dataId).id,P=o?k.shape[2]:k.shape[1],_=i?S.shape[1]:S.shape[2],$=Math.max(g,y),T=n.makeOutput([$,P,_],k.dtype),F=n.dataIdMap.get(T.dataId).id,G=new Uint8Array(new Int32Array(k.shape).buffer),q=new Uint8Array(new Int32Array(S.shape).buffer);return H9(E,G,k.shape.length,R,q,S.shape.length,o,i,F),n.disposeData(k.dataId),n.disposeData(S.dataId),T.shape=A,T}var hde={kernelName:fo,backendName:"wasm",setupFunc:dde,kernelFunc:pde};function rl(e){let{inputs:{x:t},attrs:{begin:n,size:s},backend:r}=e,[a,o]=Ut.parseSliceParams(t,n,s),i=Ut.isSliceContinous(t.shape,a,o),l=r.readSync(t.dataId),u=r.makeOutput(o,t.dtype),c=v.computeStrides(t.shape),p=r.dataIdMap.get(u.dataId);if(i){let f=Ut.computeFlatOffset(a,c);return t.dtype==="string"?p.stringBytes=l.slice(f,f+v.sizeFromShape(o)):r.typedArrayFromHeap(u).set(l.subarray(f,f+v.sizeFromShape(o))),u}if(t.dtype==="string"){let f=Rm(l,a,o,t.shape,t.dtype);return p.stringBytes=f,u}let d=r.typedArrayFromHeap(u),h=t.shape.length;if(h===2)fde(l,c[0],d,a,o);else if(h===3)mde(l,c[0],c[1],d,a,o);else if(h===4)gde(l,c[0],c[1],c[2],d,a,o);else{let f=Rm(l,a,o,t.shape,t.dtype);d.set(f)}return u}function fde(e,t,n,s,r){let a=0,o=s[0],i=s[1],l=o+r[0];for(let u=o;u<l;u++){let c=u*t+i;n.set(e.subarray(c,c+r[1]),a),a+=r[1]}}function mde(e,t,n,s,r,a){let o=0,i=r[0],l=r[1],u=r[2],c=i+a[0],p=l+a[1];for(let d=i;d<c;d++)for(let h=l;h<p;h++){let f=d*t+h*n+u;s.set(e.subarray(f,f+a[2]),o),o+=a[2]}}function gde(e,t,n,s,r,a,o){let i=0,l=a[0],u=a[1],c=a[2],p=l+o[0],d=u+o[1],h=c+o[2],f=a[3];for(let m=l;m<p;m++)for(let g=u;g<d;g++)for(let y=c;y<h;y++){let x=m*t+g*n+y*s+f;r.set(e.subarray(x,x+o[3]),i),i+=o[3]}}var yde={kernelName:Fl,backendName:"wasm",kernelFunc:rl};function Ade(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s,i=a.reduce((y,x)=>y*x),l=C.getReshaped(r.shape,a,i),u=C.getPermuted(l.length,a.length),c=C.getReshapedPermuted(r.shape,a,i),p=C.getSliceBeginCoords(o,a.length),d=C.getSliceSize(c,o,a.length),h=hs({inputs:{x:r},backend:n,attrs:{shape:l}}),f=io({inputs:{x:h},backend:n,attrs:{perm:u}}),m=hs({inputs:{x:f},backend:n,attrs:{shape:c}}),g=rl({inputs:{x:m},backend:n,attrs:{begin:p,size:d}});return n.disposeData(h.dataId),n.disposeData(f.dataId),n.disposeData(h.dataId),g}var xde={kernelName:il,backendName:"wasm",kernelFunc:Ade};function ud(e){let{inputs:{x:t},attrs:{dtype:n},backend:s}=e,r=s.makeOutput(t.shape,n),a=s.typedArrayFromHeap(t);return s.typedArrayFromHeap(r).set(a),r}var bde={kernelName:mo,backendName:"wasm",kernelFunc:ud},vde=In(go),j9;function wde(e){j9=e.wasm.cwrap(xa,null,["number","number","number","number"])}function kde(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{clipValueMin:a,clipValueMax:o}=s,i=n.dataIdMap.get(r.dataId).id,l=n.makeOutput(r.shape,r.dtype),u=n.dataIdMap.get(l.dataId).id;return j9(i,a,o,u),l}var Ide={kernelName:xa,backendName:"wasm",setupFunc:wde,kernelFunc:kde};function q9(e){let{inputs:t,backend:n}=e,s=v.parseAxisParam(e.attrs.axis,t[0].shape)[0],r=C.computeOutShape(t.map(h=>h.shape),s),a=t.filter(h=>v.sizeFromShape(h.shape)>0);if(a.length===1)return S2({inputs:{x:a[0]},backend:n});let o=n.makeOutput(r,t[0].dtype);if(v.sizeFromShape(r)===0)return o;let i=a.map(h=>h.shape);if(C.assertParamsConsistent(i,s),a[0].dtype==="string"){let h=a.map(A=>{let b=v.sizeFromShape(A.shape.slice(s));return hs({inputs:{x:A},backend:n,attrs:{shape:[-1,b]}})}),f=h.map(A=>({vals:n.readSync(A.dataId),shape:A.shape}));r=C.computeOutShape(h.map(A=>A.shape),1);let m=h[0].shape[0]===1,g=Nx(f,r,t[0].dtype,m),y=C.computeOutShape(a.map(A=>A.shape),s);o.shape=y;let x=n.dataIdMap.get(o.dataId);return x.stringBytes=C.fromStringArrayToUint8(g),h.forEach(A=>n.disposeData(A.dataId)),o}let l=v.sizeFromShape(a[0].shape.slice(0,s)),u=0,c=a.map(h=>{let f=v.sizeFromShape(h.shape.slice(s));return u+=f,f}),p=a.map(h=>n.typedArrayFromHeap(h)),d=n.typedArrayFromHeap(o);for(let h=0;h<l;h++){let f=h*u;for(let m=0;m<p.length;m++){let g=c[m],y=h*g,x=p[m].subarray(y,y+g);d.set(x,f),f+=g}}return o}var Sde={kernelName:ll,backendName:"wasm",kernelFunc:q9},X9;function Cde(e){X9=e.wasm.cwrap(yo,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Tde(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a}=t,o=s.dataIdMap.get(r.dataId).id,i=s.dataIdMap.get(a.dataId).id,{strides:l,dilations:u,pad:c,dimRoundingMode:p,dataFormat:d}=n,h=C.convertConv2DDataFormat(d),f=C.computeConv2DInfo(r.shape,a.shape,l,u,c,p,!1,h),m=f.filterHeight,g=f.filterWidth,y=f.padInfo.top,x=f.padInfo.right,A=f.padInfo.bottom,b=f.padInfo.left,w=f.dilationHeight,k=f.dilationWidth,S=f.strideHeight,E=f.strideWidth,R=f.inChannels,P=f.outChannels,_=f.padInfo.type==="SAME"?1:0;if(f.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${f.dataFormat}'. Please use 'channelsLast'.`);let $=s.makeOutput(f.outShape,"float32"),T=s.dataIdMap.get($.dataId).id;return X9(o,r.shape[0],r.shape[1],r.shape[2],i,m,g,y,x,A,b,_,w,k,S,E,R,P,T),$}var Nde={kernelName:yo,backendName:"wasm",setupFunc:Cde,kernelFunc:Tde},K9;function Ede(e){K9=e.wasm.cwrap(Ao,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Rde(e){let{backend:t,inputs:n,attrs:s}=e,{dy:r,filter:a}=n,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,inputShape:c}=s,p=1,d=C.convertConv2DDataFormat(l),h=C.computeConv2DInfo(c,a.shape,o,p,i,u,!1,d),{batchSize:f,filterHeight:m,filterWidth:g,inChannels:y,inHeight:x,inWidth:A,outChannels:b,outHeight:w,outWidth:k,strideHeight:S,strideWidth:E}=h,R=m-1-h.padInfo.top,P=g-1-h.padInfo.left,_=h.dataFormat==="channelsLast",$=v.computeStrides(h.inShape),T=v.computeStrides(r.shape),[F,G,q]=v.computeStrides(a.shape),z=$[0],Z=_?$[1]:$[2],B=_?$[2]:1,ee=_?1:$[1],Q=T[0],oe=_?T[1]:T[2],Y=_?T[2]:1,ae=_?1:T[1],le=t.makeOutput(h.inShape,"float32"),ye=t.dataIdMap.get(le.dataId).id,we=t.dataIdMap.get(r.dataId).id,Re=t.dataIdMap.get(a.dataId).id;return K9(we,Re,f,m,g,x,A,y,w,k,b,S,E,R,P,F,G,q,z,Z,B,ee,Q,oe,Y,ae,ye),le}var _de={kernelName:Ao,backendName:"wasm",setupFunc:Ede,kernelFunc:Rde},Dde=In(xo),$de=In(bo),ly;(function(e){e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest"})(ly||(ly={}));var Z9;function Pde(e){Z9=e.wasm.cwrap(cl,null,["number","number","number","number","array","number","number","number","number","number"])}function Fde(e){let{backend:t,inputs:n,attrs:s}=e,{method:r,extrapolationValue:a,cropSize:o}=s,{image:i,boxes:l,boxInd:u}=n,c=l.shape[0],[p,d]=o,h=[c,p,d,i.shape[3]],f=t.dataIdMap.get(i.dataId),m;i.dtype!=="float32"&&(m=ud({backend:t,inputs:{x:i},attrs:{dtype:"float32"}}),f=t.dataIdMap.get(m.dataId));let g=f.id,y=t.dataIdMap.get(l.dataId).id,x=t.dataIdMap.get(u.dataId).id,A=t.makeOutput(h,"float32"),b=t.dataIdMap.get(A.dataId).id,w=new Uint8Array(new Int32Array(i.shape).buffer);return Z9(g,y,x,c,w,p,d,ly[r],a,b),m!=null&&t.disposeData(m.dataId),A}var Ode={kernelName:cl,backendName:"wasm",setupFunc:Pde,kernelFunc:Fde},Y9;function Mde(e){Y9=e.wasm.cwrap(ul,null,["number","number","number","number","number","number"])}function zde(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s,l=r.shape.length;v.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumprod does not support ${r.dtype} tensors in the WASM backend`);let u=C.getAxesPermutation([a],l),c=r;u!==null&&(c=io({inputs:{x:r},attrs:{perm:u},backend:n}));let p=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumprod",[p],l);let d=n.makeOutput(c.shape,c.dtype),h=c.shape[p],f=n.dataIdMap.get(c.dataId).id,m=n.dataIdMap.get(d.dataId).id;Y9(f,o?1:0,i?1:0,h,m,Ht[r.dtype]);let g=d;if(u!==null){let y=C.getUndoAxesPermutation(u);g=io({inputs:{x:d},attrs:{perm:y},backend:n}),n.disposeData(c.dataId),n.disposeData(d.dataId)}return g}var Lde={kernelName:ul,backendName:"wasm",setupFunc:Mde,kernelFunc:zde},J9;function Bde(e){J9=e.wasm.cwrap(vo,null,["number","number","number","number","number","number"])}function Wde(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s,l=r.shape.length;v.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumsum does not support ${r.dtype} tensors in the WASM backend`);let u=C.getAxesPermutation([a],l),c=r;u!==null&&(c=io({inputs:{x:r},attrs:{perm:u},backend:n}));let p=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumsum",[p],l);let d=n.makeOutput(c.shape,c.dtype),h=c.shape[p],f=n.dataIdMap.get(c.dataId).id,m=n.dataIdMap.get(d.dataId).id;J9(f,o?1:0,i?1:0,h,m,Ht[r.dtype]);let g=d;if(u!==null){let y=C.getUndoAxesPermutation(u);g=io({inputs:{x:d},attrs:{perm:y},backend:n}),n.disposeData(c.dataId),n.disposeData(d.dataId)}return g}var Vde={kernelName:vo,backendName:"wasm",setupFunc:Bde,kernelFunc:Wde},Q9;function Ude(e){Q9=e.wasm.cwrap(dl,null,["number","number","number","array","number","array","array","number","number"])}function Gde(e){let{backend:t,inputs:n,attrs:s}=e,{x:r}=n,{blockSize:a,dataFormat:o}=s,i=r.shape[0],l=o==="NHWC"?r.shape[1]:r.shape[2],u=o==="NHWC"?r.shape[2]:r.shape[3],c=o==="NHWC"?r.shape[3]:r.shape[1],p=l*a,d=u*a,h=c/(a*a),f=o==="NHWC"?[i,p,d,h]:[i,h,p,d],m=t.makeOutput(f,"float32"),y=t.dataIdMap.get(r.dataId).id,x=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),A=new Uint8Array(new Int32Array(f).buffer),b=new Uint8Array(new Int32Array(v.computeStrides(f)).buffer),w=t.dataIdMap.get(m.dataId).id;return Q9(y,a,o==="NHWC"?1:0,x,r.shape.length-1,A,b,f.length,w),m}var Hde={kernelName:dl,backendName:"wasm",setupFunc:Ude,kernelFunc:Gde},eC;function jde(e){eC=e.wasm.cwrap(wo,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function qde(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a}=t,o=s.dataIdMap.get(r.dataId).id,i=s.dataIdMap.get(a.dataId).id,{strides:l,dilations:u,pad:c,dimRoundingMode:p}=n,d=u==null?[1,1]:u,h=C.computeConv2DInfo(r.shape,a.shape,l,d,c,p,!0),f=h.filterHeight,m=h.filterWidth,g=h.padInfo.top,y=h.padInfo.right,x=h.padInfo.bottom,A=h.padInfo.left,b=h.dilationHeight,w=h.dilationWidth,k=h.strideHeight,S=h.strideWidth,E=h.inChannels,R=h.outChannels,P=h.padInfo.type==="SAME"?1:0;if(h.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${h.dataFormat}'. Please use 'channelsLast'.`);let _=s.makeOutput(h.outShape,"float32"),$=s.dataIdMap.get(_.dataId).id;return eC(o,r.shape[0],r.shape[1],r.shape[2],i,f,m,g,y,x,A,P,b,w,k,S,E,R,$),_}var Xde={kernelName:wo,backendName:"wasm",setupFunc:jde,kernelFunc:qde},Kde=In(Io),Zde=!1,Yde=_n(pl,Zde,"bool"),Jde=In(So,"float32");function uy(e){let{inputs:t,attrs:n,backend:s}=e,{input:r}=t,{dim:a}=n,o=r.shape.length,i=r.shape.slice(),l=a;return a<0&&(v.assert(-(o+1)<=a,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+a+1),i.splice(l,0,1),hs({inputs:{x:r},backend:s,attrs:{shape:i}})}var Qde={kernelName:hl,backendName:"wasm",kernelFunc:uy};function tC(e){let{attrs:{shape:t,value:n,dtype:s},backend:r}=e,a=r.makeOutput(t,s);return r.typedArrayFromHeap(a).fill(n),a}var epe={kernelName:wc,backendName:"wasm",kernelFunc:tC},nC;function tpe(e){nC=e.wasm.cwrap(ml,null,["number","number","number","number","number","number"])}function npe(e){let{inputs:t,backend:n}=e,{image:s}=t,r=n.makeOutput(s.shape,s.dtype),a=n.dataIdMap.get(s.dataId).id,o=n.dataIdMap.get(r.dataId).id,[i,l,u,c]=s.shape;return nC(a,i,l,u,c,o),r}var spe={kernelName:ml,backendName:"wasm",kernelFunc:npe,setupFunc:tpe},rpe=In(Co),ape=!1,ope=_n(To,ape),sC;function ipe(e){sC=e.wasm.cwrap(No,null,["number","number","number","number","number","number","number"])}function lpe(e){let{backend:t,inputs:n,attrs:s}=e,{varianceEpsilon:r}=s,{x:a,mean:o,variance:i,offset:l,scale:u}=n,c=t.dataIdMap.get(a.dataId).id,p=t.dataIdMap.get(o.dataId).id,d=t.dataIdMap.get(i.dataId).id,h=l!=null?t.dataIdMap.get(l.dataId).id:0,f=u!=null?t.dataIdMap.get(u.dataId).id:0,m=t.makeOutput(a.shape,a.dtype);if(v.sizeFromShape(a.shape)===0)return m;let g=t.dataIdMap.get(m.dataId).id;return sC(c,p,d,h,f,r,g),m}var upe={kernelName:No,backendName:"wasm",setupFunc:ipe,kernelFunc:lpe},rC;function cpe(e){rC=e.wasm.cwrap(Ja,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function dpe(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dataFormat:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=n,m=C.computeConv2DInfo(r.shape,a.shape,l,c,u,d),g=Pp[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedConv2D in the wasm backend.`);let y=s.dataIdMap.get(r.dataId).id,x=s.dataIdMap.get(a.dataId).id,A=m.outChannels,b=0;if(o!=null){let Y=s.dataIdMap.get(o.dataId);if(Y.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${Y.shape.length}.`);if(Y.shape[0]!==A)throw new Error(`FusedConv2D bias shape (${Y.shape}) does not match the number of output channels (${A})`);b=Y.id}let w=m.filterHeight,k=m.filterWidth,S=m.padInfo.top,E=m.padInfo.right,R=m.padInfo.bottom,P=m.padInfo.left,_=m.dilationHeight,$=m.dilationWidth,T=m.strideHeight,F=m.strideWidth,G=m.inChannels,q=m.padInfo.type==="SAME"?1:0,z=m.batchSize,Z=m.inHeight,B=m.inWidth;if(p!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${p}'. Please use 'NHWC'.`);let ee=s.makeOutput(m.outShape,"float32"),Q=s.dataIdMap.get(ee.dataId).id,oe=i==null?0:s.dataIdMap.get(i.dataId).id;return rC(y,z,Z,B,x,w,k,b,S,E,R,P,q,_,$,T,F,G,A,g,oe,f||0,Q),ee}var ppe={kernelName:Ja,backendName:"wasm",setupFunc:cpe,kernelFunc:dpe},aC;function hpe(e){aC=e.wasm.cwrap(Qa,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function fpe(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dataFormat:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=n,m=C.computeConv2DInfo(r.shape,a.shape,l,c,u,d,!0),g=Pp[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);let y=s.dataIdMap.get(r.dataId).id,x=s.dataIdMap.get(a.dataId).id,A=m.outChannels,b=0;if(o!=null){let Y=s.dataIdMap.get(o.dataId);if(Y.shape.length!==1)throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${Y.shape.length}.`);if(Y.shape[0]!==A)throw new Error(`FusedDepthwiseConv2D bias shape (${Y.shape}) does not match the number of output channels (${A})`);b=Y.id}let w=m.filterHeight,k=m.filterWidth,S=m.padInfo.top,E=m.padInfo.right,R=m.padInfo.bottom,P=m.padInfo.left,_=m.dilationHeight,$=m.dilationWidth,T=m.strideHeight,F=m.strideWidth,G=m.inChannels,q=m.padInfo.type==="SAME"?1:0,z=m.batchSize,Z=m.inHeight,B=m.inWidth;if(p!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${p}'. Please use 'NHWC'.`);let ee=s.makeOutput(m.outShape,"float32"),Q=s.dataIdMap.get(ee.dataId).id,oe=i==null?0:s.dataIdMap.get(i.dataId).id;return aC(y,z,Z,B,x,w,k,b,S,E,R,P,q,_,$,T,F,G,A,g,oe,f||0,Q),ee}var mpe={kernelName:Qa,backendName:"wasm",setupFunc:hpe,kernelFunc:fpe},oC;function gpe(e){oC=e.wasm.cwrap(yl,null,["number","number","number","number","number","number","array","number"])}function ype(e){let{backend:t,inputs:n}=e,{params:s,indices:r}=n,[a,o,i,l]=zy.prepareAndValidate(s,r),u=t.makeOutput(a,s.dtype);if(o===0)return u;let c=r.shape,p=c[c.length-1],h=t.dataIdMap.get(s.dataId).id,m=t.dataIdMap.get(r.dataId).id,g=new Uint8Array(new Int32Array(l).buffer),y=t.dataIdMap.get(u.dataId).id;return oC(h,Ht[s.dtype],m,o,p,i,g,y),u}var Ape={kernelName:yl,backendName:"wasm",setupFunc:gpe,kernelFunc:ype},iC;function xpe(e){iC=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function bpe(e){let{backend:t,inputs:n,attrs:s}=e,{x:r,indices:a}=n,{axis:o,batchDims:i}=s,l=v.parseAxisParam(o,r.shape)[0],u=t.readSync(a.dataId),c=r.shape[l];for(let R=0;R<u.length;++R){let P=u[R];v.assert(P<=c-1&&P>=0,()=>`GatherV2: the index value ${P} is not in [0, ${c-1}]`)}let p=C.segment_util.collectGatherOpShapeInfo(r,a,l,i),d=hs({inputs:{x:r},attrs:{shape:[p.batchSize,p.outerSize,p.dimSize,p.sliceSize]},backend:t}),h=v.sizeFromShape(a.shape),f=hs({inputs:{x:a},attrs:{shape:[p.batchSize,h/p.batchSize]},backend:t}),m=[p.batchSize,p.outerSize,h/p.batchSize,p.sliceSize],g=t.makeOutput(m,r.dtype);if(v.sizeFromShape(r.shape)===0)return g;let y=d.shape.length-1,A=t.dataIdMap.get(d.dataId).id,w=t.dataIdMap.get(f.dataId).id,k=t.dataIdMap.get(g.dataId).id,S=new Uint8Array(new Int32Array(v.computeStrides(d.shape)).buffer),E=new Uint8Array(new Int32Array(v.computeStrides(m)).buffer);return iC(A,Ht[r.dtype],S,y,w,p.batchSize,E,k),t.disposeData(d.dataId),t.disposeData(f.dataId),g.shape=p.outputShape,g}var vpe={kernelName:gl,backendName:"wasm",setupFunc:xpe,kernelFunc:bpe},wpe=!1,kpe=_n(Al,wpe,"bool"),Ipe=!1,Spe=_n(Eo,Ipe,"bool"),lC;function Cpe(e){lC=e.wasm.cwrap(_o,null,["number","number","number","number"])}function Tpe(e){let{inputs:{x:t},attrs:{alpha:n},backend:s}=e,r=s.dataIdMap.get(t.dataId).id,a=s.makeOutput(t.shape,"float32");if(v.sizeFromShape(t.shape)!==0){let o=s.dataIdMap.get(a.dataId).id;lC(r,Ht[t.dtype],n,o)}return a}var Npe={kernelName:_o,backendName:"wasm",setupFunc:Cpe,kernelFunc:Tpe},Epe=!1,Rpe=_n(xl,Epe,"bool"),_pe=!1,Dpe=_n(bl,_pe,"bool"),$pe=In(Do),Ppe=!1,Fpe=_n(vl,Ppe,"bool"),Ope=In(wl),Mpe=!1,zpe=_n(Tc,Mpe,"bool"),Lpe=!1,Bpe=_n(d6,Lpe,"bool"),uC;function Wpe(e){uC=e.wasm.cwrap($o,null,["number","number","number","number"])}function Vpe(e){let{backend:t,inputs:n,attrs:s}=e,{reductionIndices:r,keepDims:a}=s,{x:o}=n,l=t.dataIdMap.get(o.dataId).id,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=pi(o,r,t);if(h){let A=t.dataIdMap.get(c.dataId).id;u=c,l=A}let f=u.shape.length;C.assertAxesAreInnerMostDims("max",p,f);let[m,g]=C.computeOutAndReduceShapes(u.shape,p),y=v.sizeFromShape(g),x=t.makeOutput(m,o.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;uC(l,Ht[o.dtype],y,A)}if(h&&t.disposeData(c.dataId),a){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var Upe={kernelName:$o,backendName:"wasm",setupFunc:Wpe,kernelFunc:Vpe},Gpe=!1,Hpe=_n(Po,Gpe),cC;function jpe(e){cC=e.wasm.cwrap(Fo,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function qpe(e){let{inputs:t,attrs:n,backend:s}=e,r=t.x,a=s.dataIdMap.get(r.dataId).id;v.assert(r.dtype==="float32",()=>`Error in MaxPool: only float32 input is supported. Got ${r.dtype}.`);let{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=n,c=C.computePool2DInfo(r.shape,o,i,1,l,u),p=c.filterHeight,d=c.filterWidth,h=c.padInfo.top,f=c.padInfo.right,m=c.padInfo.bottom,g=c.padInfo.left,y=c.dilationHeight,x=c.dilationWidth,A=c.strideHeight,b=c.strideWidth,w=c.inChannels,k=c.outChannels;if(c.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${c.dataFormat}'. 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  var resultTemp = multiplier * pow(abs(a), b);

  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS
  let isExpZero = b == vec4<f32>(0.0);
  if (isExpZero.r) {
    resultTemp.r = 1.0;
  }
  if (isExpZero.g) {
    resultTemp.g = 1.0;
  }
  if (isExpZero.b) {
    resultTemp.b = 1.0;
  }
  if (isExpZero.a) {
    resultTemp.a = 1.0;
  }
  let isNaN = a < vec4<f32>(0.0) & floor(b) < b;
  ${UC}
  return resultTemp;
  `,Zme="if (a < 0.0) { return b * a; }  return a;",Yme=`
  let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));
  return (aLessThanZero * (b * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);
  `;function z7(e,t){let n=t?UC:Ume;return t?`
    var resultTemp = vec4<f32>(${e}(a, b));
    let isNaN = isnanVec4(a) | isnanVec4(b);
    `+n+`
    return resultTemp;
  `:n+`
    return ${e}(a, b);
  `}function zm(e,t){switch(e){case Ye.MUL:return Nme;case Ye.ADD:return Ime;case Ye.SUB:return Rme;case Ye.DIV:return Tme;case Ye.EQUAL:return t?Dme:_me;case Ye.GREATER:return t?Pme:$me;case Ye.GREATER_EQUAL:return t?Ome:Fme;case Ye.LESS:return t?zme:Mme;case Ye.LESS_EQUAL:return t?Bme:Lme;case Ye.LOGICAL_AND:return t?Vme:Wme;case Ye.NOT_EQUAL:return t?qme:jme;case Ye.SQUARED_DIFFERENCE:return Eme;case Ye.INT_DIV:return t?Hme:Gme;case Ye.PRELU:return t?Yme:Zme;case Ye.MAX:return z7("max",t);case Ye.MIN:return z7("min",t);case Ye.POW:return t?Kme:Xme;case Ye.COMPLEX_MULTIPLY_REAL:return Sme;case Ye.COMPLEX_MULTIPLY_IMAG:return Cme;default:throw new Error(`BinaryType ${e} is not implemented!`)}}var Fe;(function(e){e[e.ABS=0]="ABS",e[e.CEIL=1]="CEIL",e[e.COS=2]="COS",e[e.COSH=3]="COSH",e[e.ELU=4]="ELU",e[e.EXP=5]="EXP",e[e.EXPM1=6]="EXPM1",e[e.FLOOR=7]="FLOOR",e[e.LINEAR=8]="LINEAR",e[e.LOG=9]="LOG",e[e.LOGICAL_NOT=10]="LOGICAL_NOT",e[e.NEG=11]="NEG",e[e.RELU=12]="RELU",e[e.RELU6=13]="RELU6",e[e.LEAKYRELU=14]="LEAKYRELU",e[e.RSQRT=15]="RSQRT",e[e.SIN=16]="SIN",e[e.SINH=17]="SINH",e[e.SIGMOID=18]="SIGMOID",e[e.SQRT=19]="SQRT",e[e.SQUARE=20]="SQUARE",e[e.TANH=21]="TANH",e[e.TO_INT=22]="TO_INT"})(Fe||(Fe={}));var Jme="return abs(a);",Qme="return ceil(a);",e0e="return cos(a);",t0e=`
  let e2x = exp(-a);
  return (e2x + 1.0 / e2x) / 2.0;
`,n0e="return exp(a) - 1.0;",s0e="if (a >= 0.0) { return a; }  return (exp(a) - 1.0);",r0e=`
  var resFloat = exp(a) - vec4<f32>(1.0);
  if (a.r >= 0.0) {
    resFloat.r = a.r;
  }
  if (a.g >= 0.0) {
    resFloat.g = a.g;
  }
  if (a.b >= 0.0) {
    resFloat.b = a.b;
  }
  if (a.a >= 0.0) {
    resFloat.a = a.a;
  }
  return resFloat;
`,a0e="return exp(a);",o0e="return floor(a);",i0e="return a;",l0e=`if (a < 0.0) { return 1.0/0.0; }
  return log(a);`,u0e="return f32(!(a >= 1.0));",c0e="return -a;",d0e="if (a < 0.0) { return uniforms.alpha * a; } return a;",p0e=`
  let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));
  return (aLessThanZero * (uniforms.alpha * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);
`,h0e="return select(a, 0.0, a < 0.0);",f0e="return clamp(a, 0.0, 6.0);",m0e="return clamp(a, vec4<f32>(0.0, 0.0, 0.0, 0.0), vec4<f32>(6.0, 6.0, 6.0, 6.0));",g0e=`
  return select(a, vec4<f32>(0.0), a < vec4<f32>(0.0));
`,y0e="return 1.0/sqrt(a);",A0e="return 1.0 / (1.0 + exp(-1.0 * a));",x0e="return sin(a);",b0e=`
  let e2x = exp(a);
  return (e2x - 1.0 / e2x) / 2.0;
`,v0e="return sqrt(a);",w0e="return a * a;",k0e=`
  let e2x = exp(-2.0 * abs(a));
  return sign(a) * (1.0 - e2x) / (1.0 + e2x);
`,I0e="return f32(i32((a)));";function Fi(e,t){switch(e){case Fe.ABS:return Jme;case Fe.COS:return e0e;case Fe.COSH:return t0e;case Fe.CEIL:return Qme;case Fe.ELU:return t?r0e:s0e;case Fe.EXP:return a0e;case Fe.EXPM1:return n0e;case Fe.FLOOR:return o0e;case Fe.LINEAR:return i0e;case Fe.LOG:return l0e;case Fe.LOGICAL_NOT:return u0e;case Fe.NEG:return c0e;case Fe.LEAKYRELU:return t?p0e:d0e;case Fe.RELU:return t?g0e:h0e;case Fe.RELU6:return t?m0e:f0e;case Fe.RSQRT:return y0e;case Fe.SIGMOID:return A0e;case Fe.SIN:return x0e;case Fe.SINH:return b0e;case Fe.SQRT:return v0e;case Fe.SQUARE:return w0e;case Fe.TANH:return k0e;case Fe.TO_INT:return I0e;default:throw new Error(`BinaryType ${e} is not implemented!`)}}var nn=e=>{switch(e){case 1:return"f32";case 2:return"vec2<f32>";case 3:return"vec3<f32>";case 4:return"vec4<f32>";default:throw new Error(`${e}-component is not supported.`)}};function Sa(e,t=!1,n=!1,s=3){if(e===null)return"";let r="";if(e==="linear")r=Fi(Fe.LINEAR);else if(e==="relu")r=Fi(Fe.RELU,n);else if(e==="elu")r=Fi(Fe.ELU,n);else if(e==="relu6")r=Fi(Fe.RELU6,n);else if(e==="prelu")r=zm(Ye.PRELU,n);else if(e==="sigmoid")r=Fi(Fe.SIGMOID,n);else if(e==="leakyrelu")r=Fi(Fe.LEAKYRELU,n);else throw new Error(`Activation ${e} has not been implemented for the WebGPU backend.`);let o=nn(n?4:1),i="";return t?i=`
      fn activation(a : ${o}, coords : vec${s}<i32>) -> ${o} {
        let b = getPreluActivationWeightsByOutputCoords(coords);
        ${r}
      }`:i=`
      fn activation(a : ${o}, coords : vec${s}<i32>) -> ${o} {
        ${r}
      }`,i}function cd(e,t){return`
      ${e?"value = value + getBiasByOutputCoords(coords);":""}
      ${t?"value = activation(value, coords);":""}
      `}function S0e(e,t){if(Math.max(...e)>3)throw new Error("Cannot symbolically compute strides for rank > 4 tensor.");let n=e.length,s=e.map(a=>`${t}[${a}]`),r=new Array(n-1);r[n-2]=s[n-1];for(let a=n-3;a>=0;--a)r[a]=`(${r[a+1]} * ${s[a+1]})`;return r}var C0e=(e,t,n,s)=>{let r={dtype:s.dtype,shape:s.shape},a=T0e(n,r,t),o=e.createShaderModule({code:a,label:t.constructor.name});return e.createComputePipeline({compute:{module:o,entryPoint:"main"},label:t.constructor.name,layout:"auto"})};function Tn(e){if(e<=1)return"i32";if(e===2)return"vec2<i32>";if(e===3)return"vec3<i32>";if(e===4)return"vec4<i32>";if(e===5)return"vec5";if(e===6)return"vec6";throw Error(`GPU for rank ${e} is not yet supported`)}function Ka(e){if(e===0)return"x";if(e===1)return"y";if(e===2)return"z";if(e===3)return"w";if(e===4)return"u";if(e===5)return"v";throw Error(`Index ${e} is not yet supported`)}function lt(){return`
    ${dd()}
      let index = getGlobalIndex();
`}function dd(){return`
  ${C2()}
  fn main(@builtin(local_invocation_id) LocalId : vec3<u32>,
          @builtin(global_invocation_id) GlobalId : vec3<u32>,
          @builtin(num_workgroups) NumWorkgroups: vec3<u32>) {
    localId = LocalId;
    globalId = GlobalId;
    numWorkgroups = NumWorkgroups;
`}function C2(){return`
  @compute @workgroup_size(workGroupSizeX, workGroupSizeY, workGroupSizeZ)
`}function T0e(e,t,n){let s=[];if(s.push(`
      const workGroupSizeX = ${n.workGroupSize[0]}u;
      const workGroupSizeY = ${n.workGroupSize[1]}u;
      const workGroupSizeZ = ${n.workGroupSize[2]}u;

      var<private> localId: vec3<u32>;
      var<private> globalId: vec3<u32>;
      var<private> numWorkgroups: vec3<u32>;

      // Only used when the y/z dimension of workgroup size is 1.
      fn getGlobalIndex() -> i32 {
        ${GC(n)?"  return i32(globalId.x);":`  let localInvocationIndex = localId.z * workGroupSizeX * workGroupSizeY +
                   localId.y * workGroupSizeX + localId.x;
               let workGroupID = (globalId - localId)/vec3<u32>(
                   workGroupSizeX, workGroupSizeY, workGroupSizeZ);

               return i32((workGroupID.z * numWorkgroups.x * numWorkgroups.y +
                   workGroupID.y * numWorkgroups.x + workGroupID.x) *
                   (workGroupSizeX * workGroupSizeY * workGroupSizeZ) +
                   localInvocationIndex);
        `}
      }
    `),n.isFromPixels)return s.push(`
        struct Uniform {
          size            : i32,
          numChannels     : i32,
          outShapeStrides : vec2<i32>,
        };

        @group(0) @binding(0) var<storage, read_write> result: array<${yp(t.dtype,n.isVec4)}>;
        @group(0) @binding(2) var<uniform> uniforms: Uniform;
      `),[L7,s.join(`
`),B7(t.shape),n.getUserCode()].join(`
`);let r=!1,a=!1,o="struct Uniforms { NAN : f32, ";n.variableNames.forEach((f,m)=>{let g=Tn(e[m].shape.length);(g==="vec5"||g==="vec6")&&(a=!0),(r||a)&&(o+="@align(16) "),r=a,o+=`${f.charAt(0).toLowerCase()+f.slice(1)}Shape : ${g}, `});let i=Tn(t.shape.length);a=i==="vec5"||i==="vec6",(r||a)&&(o+="@align(16) "),r=a,o+=`outShape : ${i}, `;let l=t.shape.length-1,u=Tn(l);a=u==="vec5"||u==="vec6",(r||a)&&(o+="@align(16) "),r=a,o+=`
         outShapeStrides: ${u}, `,n.size&&(r&&(o+="@align(16) "),r=!1,o+="size : i32, "),n.uniforms&&(r&&(o+="@align(16) "),o+=n.uniforms),o+="};",s.push(o),n.atomic?s.push(`
      @group(0) @binding(0) var<storage, read_write> result: array<atomic<i32>>;
    `):s.push(`
      @group(0) @binding(0) var<storage, read_write> result: array<${yp(t.dtype,n.isVec4)}>;
    `),n.variableNames.forEach((f,m)=>{s.push(`
      @group(0) @binding(${1+m}) var<storage, read> ${f}: array<${n.variableTypes?n.variableTypes[m]:yp(e[m].dtype,n.isVec4)}>;
        `)}),o!==""&&s.push(`
      @group(0) @binding(${1+n.variableNames.length}) var<uniform> uniforms: Uniforms;
      `);let c=D0e(t.shape,n.dispatchLayout),p=[L7,s.join(`
`),B7(t.shape),c,$0e(t.shape.length)];n.atomic||p.push(P0e(t.shape,t.dtype,n.isVec4));let d=e.map((f,m)=>_0e(f,t.shape,n.variableTypes?n.variableTypes[m]==="vec4<f32>":n.isVec4,n.dispatchLayout.x.length===t.shape.length)).join(`
`);return p.push(d),p.push(n.getUserCode()),p.join(`
`)}function N0e(e,t,n,s){let r=e.shaderKey;if(e.isFromPixels)return r;let a=n.map(c=>c.dtype).concat(s.dtype),o=n.map(c=>C.getBroadcastDims(c.shape,s.shape)),i=n.map(c=>v.arraysEqual(c.shape,s.shape)).join("_"),l=o.map(c=>c.join("_")).join(";"),u=GC(e)?"flatDispatch":"";return r+="_"+(e.workGroupSize?e.workGroupSize.join(","):"")+t.map(c=>c.length).join(",")+a.join(",")+e.variableNames.join(",")+l+i+u,r}var L7=`
  struct vec5 {x: i32, y: i32, z: i32, w: i32, u: i32};
  struct vec6 {x: i32, y: i32, z: i32, w: i32, u: i32, v: i32};

  // Checks whether coordinates lie within the bounds of the shape.
  fn coordsInBounds2D(coord : vec2<i32>, shape : vec2<i32>) -> bool {
    return all(coord >= vec2<i32>(0)) && all(coord < shape);
  }
  fn coordsInBounds3D(coord : vec3<i32>, shape : vec3<i32>) -> bool {
    return all(coord >= vec3<i32>(0)) && all(coord < shape);
  }
  fn coordsInBounds4D(coord : vec4<i32>, shape : vec4<i32>) -> bool {
    return all(coord >= vec4<i32>(0)) && all(coord < shape);
  }

  fn getIndexFromCoords1D(coord : i32, shape : i32) -> i32 {
    return coord;
  }
  fn getIndexFromCoords2D(coords : vec2<i32>, shape : vec2<i32>) -> i32 {
    return dot(coords, vec2<i32>(shape.y, 1));
  }
  fn getIndexFromCoords3D(coords : vec3<i32>, shape : vec3<i32>) -> i32 {
    return dot(coords, vec3<i32>(shape.y * shape.z, shape.z, 1));
  }
  fn getIndexFromCoords4D(coords : vec4<i32>, shape : vec4<i32>) -> i32 {
    return dot(coords, vec4<i32>(
        shape.y * shape.z * shape.w, shape.z * shape.w, shape.w, 1));
  }
  fn getIndexFromCoords5D(coords : vec5, shape : vec5) -> i32 {
    let shapeStrides: vec5 = vec5(shape.y * shape.z * shape.w * shape.u, shape.z * shape.w * shape.u, shape.w * shape.u, shape.u, 1);
    return coords.x*shapeStrides.x + coords.y*shapeStrides.y + coords.z*shapeStrides.z + coords.w*shapeStrides.w + coords.u*shapeStrides.u;
  }
  fn getIndexFromCoords6D(coords : vec6, shape : vec6) -> i32 {
    let shapeStrides: vec6 = vec6(shape.y * shape.z * shape.w * shape.u * shape.v, shape.z * shape.w * shape.u * shape.v, shape.w * shape.u * shape.v, shape.u * shape.v, shape.v, 1);
    return coords.x*shapeStrides.x + coords.y*shapeStrides.y + coords.z*shapeStrides.z + coords.w*shapeStrides.w + coords.u*shapeStrides.u + coords.v*shapeStrides.v;
  }

  fn idiv(a: i32, b: i32, sign: f32) -> i32 {
    var res: i32 = a / b;
    let mod: i32 = a % b;
    if (sign < 0. && mod != 0) {
      res = res - 1;
    }
    return res;
  }

  // NaN defination in IEEE 754-1985 is :
  //   - sign = either 0 or 1.
  //   - biased exponent = all 1 bits.
  //   - fraction = anything except all 0 bits (since all 0 bits represents infinity).
  // https://en.wikipedia.org/wiki/IEEE_754-1985#Representation_of_non-numbers
  fn isnan(val: f32) -> bool {
    let floatToUint: u32 = bitcast<u32>(val);
    return (floatToUint & 0x7fffffffu) > 0x7f800000u;
  }
  fn isnanVec4(val : vec4<f32>) -> vec4<bool> {
    return vec4<bool>(isnan(val[0]), isnan(val[1]), isnan(val[2]), isnan(val[3]));
  }
`;function B7(e){let t=e.length;if(t<=1)return"fn getCoordsFromIndex(index : i32) -> i32 { return index; }";let n=v.computeStrides(e),s=Tn(t),r=[];for(let o=0;o<t;o++)r.push(`d${o}`);if(n.length===1)return`    fn getCoordsFromIndex(index : i32) -> vec2<i32> {
      let d0 = index / uniforms.outShapeStrides; let d1 = index - d0 * uniforms.outShapeStrides;
      return vec2<i32>(d0, d1);
    }`;let a;return a="var index2 = index;"+n.map((o,i)=>{let l=`let ${r[i]} = index2 / uniforms.outShapeStrides.${Ka(i)}`,u=i===n.length-1?`let ${r[i+1]} = index2 - ${r[i]} * uniforms.outShapeStrides.${Ka(i)}`:`index2 = index2 - ${r[i]} * uniforms.outShapeStrides.${Ka(i)}`;return`${l}; ${u};`}).join(""),`
    fn getCoordsFromIndex(index : i32) -> ${s} {
      ${a}
      return ${s}(${r.join(",")});
    }
  `}function E0e(e,t){let n=e.name,s=e.shape.length,r=Tn(s),a="get"+n.charAt(0).toUpperCase()+n.slice(1),o=["d0","d1","d2","d3","d4","d5"].slice(0,s),i=o.map(c=>`${c} : i32`).join(", ");if(s<1)return t?`
        fn ${a}() -> vec4<f32> {
          return vec4<f32>(${n}[0]);
        }
      `:`
      fn ${a}() ->f32 {
        return f32(${n}[0]);
      }
    `;let l=`uniforms.${n.charAt(0).toLowerCase()+n.slice(1)}Shape`,u=`${s}D`;return s===0&&(u="1D"),t?`
      fn ${a}(${i}) -> vec4<f32> {
        return vec4<f32>(${n}[getIndexFromCoords${u}(${r}(${o.join(",")}),
          ${l}) / 4]);
      }
      `:`
    fn ${a}(${i}) -> f32 {
      return f32(${n}[getIndexFromCoords${u}(${r}(${o.join(",")}),
        ${l})]);
    }
   `}function R0e(e,t,n,s){let r=e.name,a=r.charAt(0).toUpperCase()+r.slice(1),o="get"+a+"ByOutput",i=e.shape.length,l=t.length,u=Tn(l);if(v.arraysEqual(e.shape,t)&&s)return n?`
      fn ${o}Index(globalIndex : i32) -> vec4<f32> {
        return vec4<f32>(${r}[globalIndex]);
      }

      fn ${o}Coords(coords : ${u}) -> vec4<f32> {
        return vec4<f32>(${r}[${l>1?"getOutputIndexFromCoords(coords)":"coords"} / 4]);
      }
      `:`
    fn ${o}Index(globalIndex : i32) -> f32 {
      return f32(${r}[globalIndex]);
    }

    fn ${o}Coords(coords : ${u}) -> f32 {
      return f32(${r}[${l>1?"getOutputIndexFromCoords(coords)":"coords"}]);
    }
    `;let c=C.getBroadcastDims(e.shape,t),p=l-i,d="";if(i===0)return n?`
    fn ${o}Index(globalIndex : i32) -> vec4<f32> {
      return get${a}();
    }

    fn ${o}Coords(coords : ${u}) -> vec4<f32> {
      return get${a}();
    }
  `:`
    fn ${o}Index(globalIndex : i32) -> f32{
      return get${a}();
    }

    fn ${o}Coords(coords : ${u}) -> f32{
      return get${a}();
    }
  `;l<2&&c.length>=1?d="coords = 0;":d=c.map(g=>`coords.${Ka(g+p)} = 0;`).join(`
`);let h="";if(l<2&&i>0)h="coords";else if(l>1){let g=Tn(i),y=e.shape.map((x,A)=>`coords.${Ka(A+p)}`).join(", ");h=`${g}(${y})`}else h="coords";let f=`uniforms.${r.charAt(0).toLowerCase()+r.slice(1)}Shape`,m=`${i}D`;return n?`
    fn ${o}Index(globalIndex : i32) -> vec4<f32> {
      var coords = getCoordsFromIndex(globalIndex);
      ${d}
      return ${r}[getIndexFromCoords${m}(${h}, ${f}) / 4];
    }

    fn ${o}Coords(coordsIn : ${u}) -> vec4<f32> {
      var coords = coordsIn;
      ${d}
      return ${r}[getIndexFromCoords${m}(${h}, ${f}) / 4];
    }
  `:`
  fn ${o}Index(globalIndex : i32) -> f32 {
    var coords = getCoordsFromIndex(globalIndex);
    ${d}
    return f32(${r}[getIndexFromCoords${m}(${h}, ${f})]);
  }

  fn ${o}Coords(coordsIn : ${u}) -> f32 {
    var coords = coordsIn;
    ${d}
    return f32(${r}[getIndexFromCoords${m}(${h}, ${f})]);
  }
`}function _0e(e,t,n,s){let r=E0e(e,n);return e.shape.length<=t.length&&(r+=R0e(e,t,n,s)),r}function D0e(e,t){let{x:n,y:s=[],z:r=[]}=t,a=e.length;if(n.length===a)return`fn getOutputCoords() -> ${Tn(a)}{
    let globalIndex = getGlobalIndex();
    return getCoordsFromIndex(globalIndex);
  }
  `;let o="",i=[n,s,r],l=0;for(let d=0;d<i.length;d++){let h=i[d];if(h.length!==0)if(l+=h.length,h.length===1)o+=`let d${h[0]} = i32(globalId[${d}]);`;else{let f=S0e(h,"uniforms.outShape");o+=`var index${d} = i32(globalId[${d}]);`;for(let m=0;m<f.length;m++)o+=`let d${h[m]} = index${d} / ${f[m]};`,m===f.length-1?o+=`let d${h[m+1]} = index${d} - d${h[m]} * ${f[m]};`:o+=`index${d} = index${d} - d${h[m]} * ${f[m]};`}}let u=[];for(let d=0;d<l;d++)u.push(`d${d}`);let c=Tn(l),p=`fn getOutputCoords() -> ${c} {
  ${o}
`;return u.length===0?p+=`return ${c}(0); }`:p+=`return ${c}(${u.join(",")}); }`,p}function $0e(e){let t="";switch(e){case 0:case 1:t+=`
        fn getOutputIndexFromCoords(coords : i32) -> i32 {
          return coords;
        }
        `;break;case 2:t+=`
        fn getOutputIndexFromCoords(coords : vec2<i32>) -> i32 {
          return dot(coords, vec2<i32>(uniforms.outShapeStrides, 1));
        }
        `;break;case 3:t+=`
        fn getOutputIndexFromCoords(coords : vec3<i32>) -> i32 {
          return dot(coords, vec3<i32>(uniforms.outShapeStrides.x, uniforms.outShapeStrides.y, 1));
        }
        `;break;case 4:t+=`
        fn getOutputIndexFromCoords(coords : vec4<i32>) -> i32 {
          return dot(coords, vec4<i32>(
            uniforms.outShapeStrides.x, uniforms.outShapeStrides.y, uniforms.outShapeStrides.z, 1));
        }
        `;break;case 5:t+=`
        fn getOutputIndexFromCoords(coords : vec5) -> i32 {
          return coords.x * uniforms.outShapeStrides.x +
              coords.y * uniforms.outShapeStrides.y +
              coords.z * uniforms.outShapeStrides.z +
              coords.w * uniforms.outShapeStrides.w +
              coords.u;
        }
        `;break;case 6:t+=`
        fn getOutputIndexFromCoords(coords : vec6) -> i32 {
          return coords.x * uniforms.outShapeStrides.x +
              coords.y * uniforms.outShapeStrides.y +
              coords.z * uniforms.outShapeStrides.z +
              coords.w * uniforms.outShapeStrides.w +
              coords.u * uniforms.outShapeStrides.u +
              coords.v;
        }
        `;break;default:v.assert(!1,()=>`Unsupported ${e}D shape`);break}return t}function GC(e){return e.dispatch[1]===1&&e.dispatch[2]===1}function yp(e,t){return e==="float32"?t?"vec4<f32>":"f32":e==="int32"||e==="bool"?t?"vec4<i32>":"i32":e}function P0e(e,t,n){let s=e.length,r=yp(t,n),a;if(n?a=`fn setOutputAtIndex(flatIndex : i32, value : vec4<f32>) {
      result[flatIndex] = ${r}(value);
    }
    fn setOutputAtIndexI32(flatIndex : i32, value : vec4<i32>) {
      result[flatIndex] = ${r}(value);
    }`:a=`fn setOutputAtIndex(flatIndex : i32, value : f32) {
      result[flatIndex] = ${r}(value);
    }
    fn setOutputAtIndexI32(flatIndex : i32, value : i32) {
      result[flatIndex] = ${r}(value);
    }`,s>=2){let o=["d0","d1","d2","d3","d4","d5"].slice(0,s),i=Tn(s);n?a+=`
      fn setOutputAtCoords(${o.map(l=>`${l} : i32`).join(", ")}, value : vec4<f32>) {
        let flatIndex = getOutputIndexFromCoords(${i}(${o.join(", ")}));
        setOutputAtIndex(flatIndex / 4, value);
      }
      fn setOutputAtCoordsI32(${o.map(l=>`${l} : i32`).join(", ")}, value : vec4<i32>) {
        let flatIndex = getOutputIndexFromCoords(${i}(${o.join(", ")}));
        setOutputAtIndexI32(flatIndex / 4, value);
      }
    `:a+=`
      fn setOutputAtCoords(${o.map(l=>`${l} : i32`).join(", ")}, value : f32) {
        let flatIndex = getOutputIndexFromCoords(${i}(${o.join(", ")}));
        setOutputAtIndex(flatIndex, value);
      }
      fn setOutputAtCoordsI32(${o.map(l=>`${l} : i32`).join(", ")}, value : i32) {
        let flatIndex = getOutputIndexFromCoords(${i}(${o.join(", ")}));
        setOutputAtIndexI32(flatIndex, value);
      }
    `}return a}var HC={};Ve(HC,{ArrayBufferToTypedArray:()=>XC,GPUBytesPerElement:()=>qC,MatMulProgramType:()=>Hs,computeDispatch:()=>We,computeWorkGroupSizeForConv2d:()=>nb,computeWorkGroupSizeForMatMul:()=>jC,computeWorkPerThreadForConv2d:()=>sb,flatDispatchLayout:()=>at,isWebGPUSupported:()=>rb,tilesFitEvenlyIntoShape:()=>F0e});var ji=e=>{let t=1;for(let n=0;n<e.length;n++)t*=e[n];return t};function F0e(e,t){if(e.length!==t.length)throw new Error(`Cannot compute whether rank ${e.length} tiles fit evenly into rank ${t.length} shape - ranks must match.`);return t.every((n,s)=>n%e[s]===0)}function We(e,t,n=[1,1,1],s=[1,1,1]){let[r,a,o]=[Math.ceil(ji(e.x.map(i=>t[i]))/(n[0]*s[0])),e.y?Math.ceil(ji(e.y.map(i=>t[i]))/(n[1]*s[1])):1,e.z?Math.ceil(ji(e.z.map(i=>t[i]))/(n[2]*s[2])):1];return[r,a,o]}function nb(e,t,n=!1){if(n)return[8,8,1];let s=ji(e.x.map(a=>t[a])),r=ji(e.y.map(a=>t[a]));return s<=4?[4,16,1]:r<=4?[16,4,1]:[16,16,1]}function jC(e,t,n){return e===1?[32,1,1]:n===1?[1,32,1]:[8,8,1]}function sb(e,t,n=!1){if(n)return[4,4,1];let s=ji(e.x.map(a=>t[a])),r=ji(e.y.map(a=>t[a]));return s<=4?[1,2,1]:r<=4?[2,1,1]:[2,2,1]}function at(e){return{x:e.map((t,n)=>n)}}function qC(e){if(e==="float32"||e==="int32"||e==="bool"||e==="string")return 4;if(e==="complex64")return 8;throw new Error(`Unknown dtype ${e}`)}function XC(e,t){if(t==="float32")return new Float32Array(e);if(t==="int32")return new Int32Array(e);if(t==="bool"||t==="string")return Uint8Array.from(new Int32Array(e));throw new Error(`Unknown dtype ${t}`)}function rb(){return(typeof window!="undefined"||typeof WorkerGlobalScope!="undefined")&&!!navigator.gpu}var Hs;(function(e){e[e.MatMulPackedVec4Program=0]="MatMulPackedVec4Program",e[e.MatMulReduceProgram=1]="MatMulReduceProgram",e[e.MatMulSplitKProgram=2]="MatMulSplitKProgram",e[e.MatMulSmallOutputSizeProgram=3]="MatMulSmallOutputSizeProgram",e[e.MatMulPackedProgram=4]="MatMulPackedProgram",e[e.MatMulMax=5]="MatMulMax"})(Hs||(Hs={}));function KC(e,t,n,s,r=!1,a=!1,o=!1,i=1){v.assert(n&&i===1||!n,()=>`transposeA ${n} is not compatible with component size ${i}`);let l=`
      let batch = ${e?"0":"batchIn"};
      let batchASize = uniforms.aShape[1] * uniforms.aShape[2];
      ${n?`value = A[(batch * batchASize + col * uniforms.aShape[2] + row) / ${i}];`:`value = A[(batch * batchASize + row * uniforms.aShape[2] + col) / ${i}];`}

    `,u;return s===!1?u=`value = B[(batch * batchBSize + row * uniforms.bShape[2] + col) / ${i}];`:u=`value = B[(batch * batchBSize + col * uniforms.bShape[2] + row) / ${i}];`,`
  fn mm_readA(batchIn: i32, row: i32, colIn: i32) -> ${nn(i)} {
    var value = ${nn(i)}(0.0);
    let col = colIn * ${i};
    ${r&&o?l:`
    ${n?"if(row < uniforms.dimAOuter && col < uniforms.dimInner)":"if(row < uniforms.aShape[1] && col < uniforms.aShape[2])"}
    {
      ${l}
    }
    `}
    return value;
  }

  fn mm_readB(batchIn: i32, row: i32, colIn: i32) -> ${nn(i)} {
    let col = colIn * ${i};
    let batch = ${t?"0":"batchIn"};
    let batchBSize = uniforms.bShape[1] * uniforms.bShape[2];
    var value = ${nn(i)}(0.0);
    ${u}
    return value;
  }
  `}function T2(e,t,n,s,r,a,o=!1,i=!1,l=!1,u=1){return`
  ${KC(n,s,r,a,o,i,l,u)}
  fn mm_write(batch: i32, row: i32, colIn: i32, valueIn: ${nn(u)}) {
    let col = colIn * ${u};
    ${o&&i?"":"if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)"}
    {
      var value = valueIn;
      let coords = vec3<i32>(batch, row, col);
      ${cd(e,t)}
      setOutputAtCoords(coords[0], coords[1], coords[2], value);
    }
  }
  `}var O0e=e=>e?`
        mm_Asub[inputRow][inputCol] = mm_readA(batch,
          t * TileInner + inputRow,
          globalRowStart + inputCol);
        `:`
        mm_Asub[inputRow][inputCol] = mm_readA(batch,
          globalRowStart + inputRow,
          t * TileInner + inputCol);
        `,M0e=e=>e?"let ACached = mm_Asub[k][tileRow + innerRow];":"let ACached = mm_Asub[tileRow + innerRow][k];";function ab(e,t,n=!1,s=32){let r=e[1]*t[1],a=e[0]*t[0],o=n?r:s,i=n?s:r;v.assert(i%t[1]===0&&o%t[0]===0&&s%t[1]===0,()=>`tileAHight ${i} must be divisible by workGroupSize[1]${t[1]}, tileAWidth ${o} must be divisible by workGroupSize[0]${t[0]}, tileInner ${s} must be divisible by workGroupSize[1]${t[1]}`);let l=i/t[1],u=o/t[0],c=s/t[1];return`
    var<workgroup> mm_Asub : array<array<f32, ${o}>, ${i}>;
    var<workgroup> mm_Bsub : array<array<f32, ${a}>, ${s}>;
    const RowPerThread = ${e[1]};
    const ColPerThread = ${e[0]};
    const TileInner = ${s};

    @compute @workgroup_size(workGroupSizeX, workGroupSizeY, workGroupSizeZ)
    fn main(@builtin(local_invocation_id) LocalId : vec3<u32>,
            @builtin(global_invocation_id) GlobalId : vec3<u32>,
            @builtin(num_workgroups) NumWorkgroups: vec3<u32>,
            @builtin(workgroup_id) workgroupId: vec3<u32>) {
      localId = LocalId;
      globalId = GlobalId;
      numWorkgroups = NumWorkgroups;

      let tileRow = i32(localId.y) * RowPerThread;
      let tileCol = i32(localId.x) * ColPerThread;

      let globalRow = i32(globalId.y) * RowPerThread;
      let globalCol = i32(globalId.x) * ColPerThread;
      let batch = i32(globalId.z);
      let globalRowStart = i32(workgroupId.y) * ${r};

      let numTiles = (uniforms.dimInner - 1) / TileInner + 1;

      var acc : array<array<f32, ColPerThread>, RowPerThread>;

      // Without this initialization strange values show up in acc.
      for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {
        for (var innerCol = 0; innerCol < ColPerThread; innerCol = innerCol + 1) {
          acc[innerRow][innerCol] = 0.0;
        }
      }

      let tileRowA = i32(localId.y) * ${l};
      let tileColA = i32(localId.x) * ${u};
      let tileRowB = i32(localId.y) * ${c};
      // Loop over shared dimension.
      for (var t = 0; t < numTiles; t = t + 1) {
        // Load one tile of A into local memory.
        for (var innerRow = 0; innerRow < ${l}; innerRow = innerRow + 1) {
          for (var innerCol = 0; innerCol < ${u}; innerCol = innerCol + 1) {
            let inputRow = tileRowA + innerRow;
            let inputCol = tileColA + innerCol;
            ${O0e(n)}
          }
        }

        // Load one tile of B into local memory.
        for (var innerRow = 0; innerRow < ${c}; innerRow = innerRow + 1) {
          for (var innerCol = 0; innerCol < ColPerThread; innerCol = innerCol + 1) {
            let inputRow = tileRowB + innerRow;
            let inputCol = tileCol + innerCol;
            mm_Bsub[inputRow][inputCol] = mm_readB(batch,
              t * TileInner + inputRow,
              globalCol + innerCol);
          }
        }

        workgroupBarrier();

        // Compute acc values for a single thread.
        var BCached : array<f32, ColPerThread>;
        for (var k = 0; k < TileInner; k = k + 1) {
          for (var inner = 0; inner < ColPerThread; inner = inner + 1) {
            BCached[inner] = mm_Bsub[k][tileCol + inner];
          }

          for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {
            ${M0e(n)}
            for (var innerCol = 0; innerCol < ColPerThread; innerCol = innerCol + 1) {
              acc[innerRow][innerCol] = acc[innerRow][innerCol] + ACached * BCached[innerCol];
            }
          }
        }

        workgroupBarrier();
      }

      for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {
        for (var innerCol = 0; innerCol < ColPerThread; innerCol = innerCol + 1) {
          mm_write(batch, globalRow + innerRow, globalCol + innerCol,
              acc[innerRow][innerCol]);
        }
      }
    }
  `}var z0e=e=>e?`
      mm_readA(batch, colA, globalRow),
      mm_readA(batch, colA + 1, globalRow),
      mm_readA(batch, colA + 2, globalRow),
      mm_readA(batch, colA + 3, globalRow)
  `:`
      mm_readA(batch, globalRow, colA),
      mm_readA(batch, globalRow, colA + 1),
      mm_readA(batch, globalRow, colA + 2),
      mm_readA(batch, globalRow, colA + 3)
  `;function L0e(e,t=!1){return v.assert(e[1]===1&&e[2]===1,()=>`A linear work group size is required. But got ${e}.`),`
    const TileSize = ${e[0]*4};
    var<workgroup> mm_Asub : array<vec4<f32>, ${e[0]}>;

    ${dd()}
      let tileCol = i32(localId.x);
      let globalCol = i32(globalId.x);
      let globalRow = i32(globalId.y);

      let numTiles = (uniforms.dimInner - 1) / TileSize + 1;
      let batch = i32(globalId.z);
      // Without this initialization strange values show up in acc.
      var acc = 0.0;

      // Loop over shared dimension.
      for (var t = 0; t < numTiles; t = t + 1) {
        // Load one tile of A into local memory.
        let colA = t * TileSize + tileCol * 4;
        mm_Asub[tileCol] = vec4<f32>(${z0e(t)});
        workgroupBarrier();

        // Compute acc values for a single thread.
        for (var k = 0; k < TileSize / 4; k = k + 1) {
          let rowB = t * TileSize + k * 4;
          let BCached = vec4<f32>(mm_readB(batch, rowB, globalCol),
                              mm_readB(batch, rowB + 1, globalCol),
                              mm_readB(batch, rowB + 2, globalCol),
                              mm_readB(batch, rowB + 3, globalCol));

          let ACached = mm_Asub[k];
          acc = acc + dot(ACached, BCached);
        }

        workgroupBarrier();
      }

      mm_write(batch, globalRow, globalCol, acc);
    }
  `}var B0e=class{constructor(e,t,n,s,r,a=!1,o=!1,i=null,l=null,u=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workGroupSize=[16,16,1],this.outputShape=t,this.dispatchLayout={x:[2],y:[1],z:[0]};let c=a?e[1]:e[2];this.workGroupSize=jC(t[1],c,t[2]),(t[1]===1||t[2]===1)&&(n=1),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[n,n,1]),v.arraysEqual(this.dispatch,[1,1,1])&&(n=1,this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[n,n,1]));let p=i!=null,d=u!=null;p&&this.variableNames.push("bias"),d&&this.variableNames.push("preluActivationWeights"),this.workPerThread=n,this.transposeA=a,this.transposeB=o,this.addBias=p,this.activation=l,this.hasPreluActivationWeights=d,this.batchAEqualOne=s,this.batchBEqualOne=r,[this.fitAOuter,this.fitBOuter,this.fitInner]=this.getShapeFit(t[1],t[2],c),this.shaderKey=`matMulPacked_${this.workPerThread}_${a}_${o}_${this.activation}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.outputShape[1]>1}_${this.batchAEqualOne}_${this.batchBEqualOne}`}getShapeFit(e,t,n){let s=this.workGroupSize[1]*this.workPerThread,r=this.workGroupSize[0]*this.workPerThread;this.tileInner=32,this.outputShape[1]===1&&(this.tileInner=this.workGroupSize[0]*4);let a=e%s===0,o=t%r===0,i=n%this.tileInner===0;return[a,o,i]}getUserCode(){return`
      ${Sa(this.activation,this.hasPreluActivationWeights)}
      ${T2(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,!1,this.transposeB,this.fitAOuter,this.fitBOuter,this.fitInner)}
      ${this.outputShape[1]>1?ab([this.workPerThread,this.workPerThread,1],this.workGroupSize,this.transposeA,this.tileInner):L0e(this.workGroupSize,this.transposeA)}
    `}},W0e=(e,t)=>e?`
        mm_Asub[inputRow][inputCol] = mm_readA(batch,
          t * TileInner + inputRow,
          globalRowStart / ${t} + inputCol);
        `:`
        mm_Asub[inputRow][inputCol] = mm_readA(batch,
          globalRow + innerRow,
          t * TileInner / ${t} + inputCol);
        `,V0e=(e,t)=>e?`
        let ACached0 = mm_Asub[k * InnerElementSize][localRow];
        let ACached1 = mm_Asub[k * InnerElementSize + 1][localRow];
        let ACached2 = mm_Asub[k * InnerElementSize + 2][localRow];
        ${t===3?"":"let ACached3 = mm_Asub[k * InnerElementSize + 3][localRow];"}
        for (var i = 0; i < RowPerThread; i = i + 1) {
          acc[i] = BCached[0] * ACached0[i] + acc[i];
          acc[i] = BCached[1] * ACached1[i] + acc[i];
          acc[i] = BCached[2] * ACached2[i] + acc[i];
          ${t===3?"":"acc[i] = BCached[3] * ACached3[i] + acc[i];"}
        }`:`
        for (var i = 0; i < RowPerThread; i = i + 1) {
          let ACached = mm_Asub[tileRow + i][k];
          acc[i] = BCached[0] * ACached.x + acc[i];
          acc[i] = BCached[1] * ACached.y + acc[i];
          acc[i] = BCached[2] * ACached.z + acc[i];
          ${t===3?"":"acc[i] = BCached[3] * ACached.w + acc[i];"}
        }`;function ob(e,t,n,s,r=4,a=!1){let o=a?t:s,i=a?s:t,l=a?e[1]:r;return v.assert((a&&t===n||s%4===0||s%3===0)&&e[0]===4&&(r===3||r===4),()=>`tileInner ${s} must be divisible by 4|3. ColPerThread ${e[0]} must be 4.
           innerElementSize ${r} must be 3|4.`),`
  var<workgroup> mm_Asub : array<array<vec${l}<f32>, ${o/l}>, ${i}>;
  var<workgroup> mm_Bsub : array<array<vec4<f32>, ${n/e[0]}>, ${s}>;

  const RowPerThread = ${e[1]};
  const ColPerThread = ${e[0]};
  const InnerElementSize = ${r};
  const TileInner = ${s};

  @compute @workgroup_size(workGroupSizeX, workGroupSizeY, workGroupSizeZ)
  fn main(@builtin(local_invocation_id) LocalId : vec3<u32>,
          @builtin(global_invocation_id) GlobalId : vec3<u32>,
          @builtin(num_workgroups) NumWorkgroups: vec3<u32>,
          @builtin(workgroup_id) workgroupId: vec3<u32>) {
    localId = LocalId;
    globalId = GlobalId;
    numWorkgroups = NumWorkgroups;

    let localRow = i32(localId.y);
    let tileRow = ${t===1?"0":"localRow * RowPerThread"};
    let tileCol = i32(localId.x);

    let globalRow = ${t===1?"0":"i32(globalId.y) * RowPerThread"};
    let globalCol = i32(globalId.x);
    let batch = i32(globalId.z);
    let globalRowStart = i32(workgroupId.y) * ${t};

    let numTiles = (uniforms.dimInner - 1) / TileInner + 1;

    var acc: array<vec4<f32>, RowPerThread>;
    var BCached : array<vec4<f32>, 4>;

    // Loop over shared dimension.
    let RowPerThreadB = TileInner / i32(workGroupSizeY);
    let tileRowB = localRow * RowPerThreadB;
    for (var t = 0; t < numTiles; t = t + 1) {
        // Load one tile of A into local memory.
        for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {
            let inputRow = tileRow + innerRow;
            let inputCol = tileCol;
            ${W0e(a,l)}
        }

        // Load one tile of B into local memory.
        for (var innerRow = 0; innerRow < RowPerThreadB; innerRow = innerRow + 1) {
            let inputRow = tileRowB + innerRow;
            let inputCol = tileCol;
            mm_Bsub[inputRow][inputCol] = mm_readB(batch, t * TileInner + inputRow, globalCol);
        }

        workgroupBarrier();

        // Compute acc values for a single thread.
        for (var k = 0; k < TileInner / InnerElementSize; k = k + 1) {
            BCached[0] = mm_Bsub[k * InnerElementSize][tileCol];
            BCached[1] = mm_Bsub[k * InnerElementSize + 1][tileCol];
            BCached[2] = mm_Bsub[k * InnerElementSize + 2][tileCol];
            ${r===3?"":"BCached[3] = mm_Bsub[k * InnerElementSize + 3][tileCol];"}

            ${V0e(a,r)}
        }

        workgroupBarrier();
    }

    for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {
        mm_write(batch, globalRow + innerRow, globalCol, acc[innerRow]);
    }
  }`}var U0e=class{constructor(e,t,n,s,r=!1,a=null,o=null,i=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workGroupSize=[8,8,1],this.isVec4=!0,this.outputShape=t,this.dispatchLayout={x:[2],y:[1],z:[0]},t[1]===1&&!r?this.elementsPerThread=[4,1,1]:this.elementsPerThread=[4,4,1],this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,this.elementsPerThread);let l=a!=null,u=i!=null;l&&this.variableNames.push("bias"),u&&this.variableNames.push("preluActivationWeights"),this.tileAOuter=t[1]===1&&!r?1:this.workGroupSize[1]*this.elementsPerThread[1],this.tileBOuter=this.workGroupSize[0]*this.elementsPerThread[0],this.tileInner=this.tileBOuter,this.aShape=e,this.addBias=l,this.activation=o,this.hasPreluActivationWeights=u,this.batchAEqualOne=n,this.batchBEqualOne=s,this.transposeA=r;let c=r?e[1]:e[2];this.fitAOuter=t[1]%this.tileAOuter===0,this.fitBOuter=t[2]%this.tileBOuter===0,this.fitInner=c%this.tileInner===0,this.shaderKey=`matMulPackedVec4_${this.activation}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.elementsPerThread}_${this.batchAEqualOne}_${this.batchBEqualOne}_${this.transposeA}`}getUserCode(){return`
      ${Sa(this.activation,this.hasPreluActivationWeights,!0)}
      ${T2(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,!1,!1,this.fitAOuter,this.fitBOuter,this.fitInner,4)}
      ${ob(this.elementsPerThread,this.tileAOuter,this.tileBOuter,this.tileInner,4,this.transposeA)}
    `}};function G0e(){return`
    var<workgroup> sumValues : array<f32, workGroupSizeX>;
    ${dd()}
      let coords = getOutputCoords();
      let batch = coords[0];
      let row = coords[1];
      let col = coords[2];
      var sum = 0.0;
      let Length = uniforms.dimInner;
      for (var k = i32(localId.x); k < Length; k = k + i32(workGroupSizeX)) {
        let dataA = mm_readA(batch, row, k);
        let dataB = mm_readB(batch, k, col);
        sum = sum + dataA * dataB;
      }
      sumValues[localId.x] = sum;
      workgroupBarrier();

      for(var currentSize = workGroupSizeX / 2u; currentSize > 1u;
          currentSize = currentSize / 2u) {
        if (localId.x < currentSize)
        {
          sumValues[localId.x] = sumValues[localId.x] + sumValues[localId.x + currentSize];
        }
        workgroupBarrier();
      }

      if (localId.x == 0u) {
        sum = sumValues[0] + sumValues[1];
        mm_write(batch, row, col, sum);
      }
    }
  `}var H0e=class{constructor(e,t,n,s=!1,r=!1,a=null,o=null,i=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workGroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout={x:[],y:[1,2],z:[0]},this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize);let l=a!=null,u=i!=null;l&&this.variableNames.push("bias"),u&&this.variableNames.push("preluActivationWeights"),this.transposeA=s,this.transposeB=r,this.addBias=l,this.activation=o,this.hasPreluActivationWeights=u,this.batchAEqualOne=t,this.batchBEqualOne=n,this.shaderKey=`matMulReduce_${this.activation}_${s}_${r}_${this.batchAEqualOne}_${this.batchBEqualOne}`}getUserCode(){return`
      ${Sa(this.activation,this.hasPreluActivationWeights)}
      ${T2(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,this.transposeA,this.transposeB)}
      ${G0e()}
    `}};function j0e(e){let t=e[1],n=e[0],s=t>n?t:n;return`
  var<workgroup> mm_Asub : array<array<f32, ${s}>, ${t}>;
  var<workgroup> mm_Bsub : array<array<f32, ${n}>, ${s}>;

  // If the output size is small for matrix multiplication, avoid to use vec4
  // and handle some elements per thread to optimally utilize the ALU.
  // Read data from global memory to registers firstly, then store them into
  // shared memory, so it is instruction-Level parallelism for arithmetic
  // operations and others handle IO operations between barrier api, makes ALU
  // and load/store units work simultaneously, could improves the performance.
  ${dd()}
    let tileRow = i32(localId.y);
    let tileCol = i32(localId.x);
    let globalRow = i32(globalId.y);
    let globalCol = i32(globalId.x);
    let batch = i32(globalId.z);

    // uniforms.dimInner should be greater than 0.
    let numTiles = (uniforms.dimInner - 1) / ${s} + 1;
    var acc = 0.0;

    var globalColA = tileCol;
    var globalRowB = 0;
    var regA = mm_readA(batch, globalRow, globalColA);
    var regB0 = mm_readB(batch, globalRowB + 2 * tileRow, globalCol);
    var regB1 = mm_readB(batch, globalRowB + 2 * tileRow + 1, globalCol);
    globalColA = globalColA + ${s};
    globalRowB = globalRowB + ${s};

    for (var t = 0; t < numTiles; t = t + 1) {
      mm_Asub[tileRow][tileCol] = regA;
      mm_Bsub[2 * tileRow][tileCol] = regB0;
      mm_Bsub[2 * tileRow + 1][tileCol] = regB1;

      workgroupBarrier();

      regA = mm_readA(batch, globalRow, globalColA);
      regB0 = mm_readB(batch, globalRowB + 2 * tileRow, globalCol);
      regB1 = mm_readB(batch, globalRowB + 2 * tileRow + 1, globalCol);
      globalColA = globalColA + ${s};
      globalRowB = globalRowB + ${s};

      for (var k = 0; k < ${s}; k = k + 1) {
        acc = acc + mm_Asub[tileRow][k] * mm_Bsub[k][tileCol];
      }
      workgroupBarrier();
    }

    mm_write(batch, globalRow, globalCol, acc);
  }
  `}var q0e=class{constructor(e,t,n,s=!1,r=!1,a=null,o=null,i=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workGroupSize=[16,8,1],this.outputShape=n,this.dispatchLayout={x:[2],y:[1],z:[0]},this.dispatch=[Math.ceil(n[2]/this.workGroupSize[0]),Math.ceil(n[1]/this.workGroupSize[1]),n[0]];let l=a!=null;l&&this.variableNames.push("bias");let u=i!=null;u&&this.variableNames.push("preluActivationWeights"),this.transposeA=s,this.transposeB=r,this.addBias=l,this.activation=o,this.hasPreluActivationWeights=u,this.batchAEqualOne=e[0]===1,this.batchBEqualOne=t[0]===1,this.shaderKey=`matMulSmallOutputSize_${this.activation}_${s}_${r}_${this.batchAEqualOne}_${this.batchBEqualOne}`}getUserCode(){return`
      ${Sa(this.activation,this.hasPreluActivationWeights)}
      ${T2(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,this.transposeA,this.transposeB)}
      ${j0e(this.workGroupSize)}
    `}},X0e=class{constructor(e,t,n,s,r=!1,a=!1){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workGroupSize=[8,8,1],this.atomic=!0,this.tileInner=32,v.assert(e[0]===1,()=>"MatMulSplitKProgram only supports batch = 1."),this.outputShape=e,this.dispatchLayout={x:[2],y:[1],z:[0,3]},this.elementsPerThread=[4,4,this.tileInner],this.outputShape[1]<16&&(this.elementsPerThread[1]=1),this.outputShape[2]<16&&(this.elementsPerThread[0]=1),this.dispatch=We(this.dispatchLayout,[this.outputShape[0],this.outputShape[1],this.outputShape[2],t],this.workGroupSize,this.elementsPerThread),this.transposeA=r,this.transposeB=a,this.batchAEqualOne=n,this.batchBEqualOne=s,this.shaderKey=`matMulSplitK_${r}_${a}_${n}_${s}_${this.elementsPerThread}`}getUserCode(){let e=`
     var oldValue = atomicLoad(&(result[flatIndex]));
     var exchanged = false;
     for (; !exchanged;) {
       let newValueF32 = bitcast<f32>(oldValue) + value;
       let newValue = bitcast<i32>(newValueF32);
       let res = atomicCompareExchangeWeak(&(result[flatIndex]), oldValue, newValue);
       oldValue = res.old_value;
       exchanged = res.exchanged;
     }
     `;return`
      ${KC(this.batchAEqualOne,this.batchBEqualOne,this.transposeA,this.transposeB)}
      fn mm_write(batch: i32, row : i32, col : i32, valueIn : f32) {
        if (row < uniforms.dimAOuter && col < uniforms.dimBOuter) {
          let coords = vec3<i32>(batch, row, col);
          let flatIndex = getOutputIndexFromCoords(coords);
          var value = valueIn;
          // The problem is that we should initialize output to zero before using.
          // Otherwise, the original value will be added to the result.
          ${e}
        }
      }

      ${this.makeMatMulSplitKSource()}
    `}makeMatMulSplitKSource(){let e=this.workGroupSize[1]*this.elementsPerThread[1],t=this.workGroupSize[0]*this.elementsPerThread[0],n=this.elementsPerThread[1],s=this.elementsPerThread[0],r=this.tileInner/this.workGroupSize[0],a=this.tileInner/this.workGroupSize[1];return v.assert(this.tileInner%this.workGroupSize[0]===0&&this.tileInner%this.workGroupSize[1]===0,()=>`tileInner ${this.tileInner} must be divisible by workGroupSize[0]${this.workGroupSize[0]} and workGroupSize[1]${this.workGroupSize[1]}`),`
      var<workgroup> mm_Asub : array<array<f32, ${this.tileInner}>, ${e}>;
      var<workgroup> mm_Bsub : array<array<f32, ${t}>, ${this.tileInner}>;
      ${dd()}
        let tileRow = i32(localId.y) * ${n};
        let tileCol = i32(localId.x) * ${s};

        let globalRow = i32(globalId.y) * ${n};
        let globalCol = i32(globalId.x) * ${s};
        let batch = 0;
        let kStart = i32(globalId.z) * ${this.tileInner};

        // Load one tile of A into local memory.
        let tileColA = i32(localId.x) * ${r};
        for (var innerRow = 0; innerRow < ${n}; innerRow = innerRow + 1) {
          for (var innerCol = 0; innerCol < ${r}; innerCol = innerCol + 1) {
            let inputRow = tileRow + innerRow;
            let inputCol = tileColA + innerCol;
            mm_Asub[inputRow][inputCol] = mm_readA(${this.batchAEqualOne?0:"batch"},
                globalRow + innerRow,
                kStart + inputCol);
          }
        }
        // Load one tile of B into local memory.
        let tileRowB = i32(localId.y) * ${a};
        for (var innerRow = 0; innerRow < ${a}; innerRow = innerRow + 1) {
          for (var innerCol = 0; innerCol < ${s}; innerCol = innerCol + 1) {
            let inputRow = tileRowB + innerRow;
            let inputCol = tileCol + innerCol;
            mm_Bsub[inputRow][inputCol] = mm_readB(${this.batchBEqualOne?0:"batch"},
                kStart + inputRow,
                globalCol + innerCol);
          }
        }

        workgroupBarrier();

        var acc : array<array<f32, ${s}>, ${n}>;
        // Loop over shared dimension. Compute acc values for a single thread.
        for (var k = 0; k < ${this.tileInner}; k = k + 1) {
          var BCached : array<f32, ${s}>;
          for (var inner = 0; inner < ${s}; inner = inner + 1) {
            BCached[inner] = mm_Bsub[k][tileCol + inner];
          }

          for (var innerRow = 0; innerRow < ${n}; innerRow = innerRow + 1) {
            let ACached = mm_Asub[tileRow + innerRow][k];
            for (var innerCol = 0; innerCol < ${s}; innerCol = innerCol + 1) {
              acc[innerRow][innerCol] = acc[innerRow][innerCol] + ACached * BCached[innerCol];
            }
          }
        }

        for (var innerRow = 0; innerRow < ${n}; innerRow = innerRow + 1) {
          for (var innerCol = 0; innerCol < ${s}; innerCol = innerCol + 1) {
            mm_write(batch, globalRow + innerRow, globalCol + innerCol, acc[innerRow][innerCol]);
          }
        }
      }
    `}},K0e=class{constructor(e,t=null,n=null,s=null){this.uniforms="",this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.addBias=t!=null,this.hasPreluActivationWeights=s!=null,this.activation=n,this.addBias&&this.variableNames.push("bias"),this.hasPreluActivationWeights&&this.variableNames.push("preluActivationWeights"),this.shaderKey=`biasActivation_${n}`}getUserCode(){return`
    ${Sa(this.activation,this.hasPreluActivationWeights)}
    ${lt()}
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        var value = getXByOutputIndex(index);
        ${cd(this.addBias,this.activation)}
        setOutputAtIndex(index, value);
      }
    }
    `}},Z0e=class{constructor(e){this.variableNames=[],this.outputShape=[],this.uniforms="value : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="fill"}getUserCode(){return`
    ${lt()}
      if (index < uniforms.size) {
        setOutputAtIndex(index, uniforms.value);
      }
    }
  `}};function au(e){let{backend:t,attrs:n}=e,{shape:s,value:r}=n,{dtype:a}=n;if(a=a||v.inferDtype(r),a==="string"){let o=v.getArrayFromDType(a,v.sizeFromShape(s));return o.fill(r),t.makeTensorInfo(s,a,o)}else{let o=new Z0e(s),i=[{type:"float32",data:[r]}];return t.runWebGPUProgram(o,[],a,i)}}var Y0e={kernelName:wc,backendName:"webgpu",kernelFunc:au};function Ue(e){let{inputs:t,attrs:n}=e,{x:s}=t,{shape:r}=n,a=v.sizeFromShape(s.shape),o=v.inferFromImplicitShape(r,a),i=v.sizeFromShape(o);return v.assert(a===i,()=>`The new shape (${o}) has ${i} elements and the old shape (${s.shape}) has ${a} elements. The new shape and old shape must have the same number of elements.`),e.backend.incRef(s.dataId),{dataId:s.dataId,shape:o,dtype:s.dtype}}var J0e={kernelName:Rl,backendName:"webgpu",kernelFunc:Ue};function ib({a:e,b:t,transposeA:n,transposeB:s,backend:r,bias:a=null,preluActivationWeights:o=null,leakyreluAlpha:i=0,activation:l=null}){let u=e.shape.length,c=t.shape.length,p=n?e.shape[u-2]:e.shape[u-1],d=s?t.shape[c-1]:t.shape[c-2],h=n?e.shape[u-1]:e.shape[u-2],f=s?t.shape[c-2]:t.shape[c-1],m=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(m),x=v.sizeFromShape(g),b=ql.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,f]);v.assert(p===d,()=>`Error in matMul: inner shapes (${p}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${s} must match.`);let w=n?[y,p,h]:[y,h,p],k=s?[x,f,d]:[x,d,f],S=Ue({inputs:{x:e},backend:r,attrs:{shape:w}}),E=Ue({inputs:{x:t},backend:r,attrs:{shape:k}}),R=[S,E],P=Math.max(y,x),_=y===1,$=x===1,T=(p%4===0&&!n||h%4===0&&n)&&f%4===0&&!s,F=[S,E],G=[{type:"int32",data:[h]},{type:"int32",data:[f]},{type:"int32",data:[p]}],q,z,Z=[P,h,f],B=X().get("WEBGPU_MATMUL_PROGRAM_TYPE");switch(B<0&&(h*f<=128?B=Hs.MatMulReduceProgram:P===1&&h<=128&&f<=48&&d>=2e3?B=Hs.MatMulSplitKProgram:h<=16&&(f<=512||d>=2*f)||f<=16&&(h<=512||p>=2*h)?B=Hs.MatMulSmallOutputSizeProgram:T?B=Hs.MatMulPackedVec4Program:B=Hs.MatMulPackedProgram),B){case Hs.MatMulPackedVec4Program:q=new U0e(w,Z,_,$,n,a,l,o);break;case Hs.MatMulReduceProgram:q=new H0e(Z,_,$,n,s,a,l,o);break;case Hs.MatMulSplitKProgram:{if(z=au({backend:r,attrs:{shape:Z,value:0,dtype:e.dtype}}),q=new X0e(Z,d,_,$,n,s),a||l){z=r.runWebGPUProgram(q,F,e.dtype,G,z);let Q=new K0e(z.shape,a,l,o),oe=null,Y=[z];a&&Y.push(a),o&&Y.push(o),l==="leakyrelu"&&(oe=[{type:"float32",data:[i]}],Q.uniforms+=" alpha : f32,");let ae=r.runWebGPUProgram(Q,Y,z.dtype,oe);R.push(z);let le=Ue({inputs:{x:ae},backend:r,attrs:{shape:b}});R.push(ae);for(let ye of R)r.disposeData(ye.dataId);return le}break}case Hs.MatMulSmallOutputSizeProgram:q=new q0e(w,k,Z,n,s,a,l,o);break;case Hs.MatMulPackedProgram:q=new B0e(w,Z,X().get("WEBGPU_MATMUL_WORK_PER_THREAD"),_,$,n,s,a,l,o);break;default:throw new Error(`Unsupported MatMulProgramType ${B}.`)}a&&F.push(a),o&&F.push(o),l==="leakyrelu"&&(G.push({type:"float32",data:[i]}),q.uniforms+=" alpha : f32,"),z=r.runWebGPUProgram(q,F,e.dtype,G,z);let ee=Ue({inputs:{x:z},backend:r,attrs:{shape:b}});R.push(z);for(let Q of R)r.disposeData(Q.dataId);return ee}function Q0e(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=s;return ib({a:r,b:a,transposeA:l,transposeB:u,backend:n,bias:o,preluActivationWeights:i,leakyreluAlpha:p,activation:c})}var e2e={kernelName:Ya,backendName:"webgpu",kernelFunc:Q0e},W7=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.workGroupSize=[128,1,1],this.size=!0,this.outputShape=C.assertAndGetBroadcastShape(t,n),this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`binaryOpComplex_${e}`,this.op=e}getUserCode(){return`
      fn binaryOpComplex(
          areal : f32, aimag : f32, breal : f32, bimag : f32) -> f32 {
        ${zm(this.op,!1)}
      }

      ${lt()}
        if(index < uniforms.size) {
          let areal = getARealByOutputIndex(index);
          let aimag = getAImagByOutputIndex(index);
          let breal = getBRealByOutputIndex(index);
          let bimag = getBImagByOutputIndex(index);
          setOutputAtIndex(index, binaryOpComplex(areal, aimag, breal, bimag));
        }
      }
    `}},hy=class{constructor(e,t,n){this.size=!0,this.variableNames=["A","B"],this.outputShape=C.assertAndGetBroadcastShape(t,n),this.dispatchLayout=at(this.outputShape),this.op=e,this.useSharedMemoryWithA=t.length===1&&n.length>1&&t[0]<1024,this.useSharedMemoryWithB=n.length===1&&t.length>1&&n[0]<1024,this.useSharedMemoryWithA||this.useSharedMemoryWithB?(this.isVec4=!1,this.lastDimensionSize=this.useSharedMemoryWithB?n[0]:t[0],this.shaderKey=`binary_${this.type}_${e}_${this.lastDimensionSize}_${this.useSharedMemoryWithB}`,this.type="shared",this.workGroupSize=[256,1,1],this.lastDimensionSize<256?this.workPerThread=1:this.lastDimensionSize<512?this.workPerThread=2:this.workPerThread=4):(v.arraysEqual(t,n)&&v.sizeFromShape(t)%4===0?(this.isVec4=!0,this.type="vec4",this.workPerThread=4):(this.isVec4=!1,this.type="plain",this.workPerThread=1),this.shaderKey=`binary_${this.type}_${e}`,this.workGroupSize=[128,1,1]),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1])}getUserCode(){let e;if(this.type==="shared"){let t=this.lastDimensionSize>1?`coords[${this.outputShape.length-1}]`:"0",n=this.useSharedMemoryWithB?`let a = getAByOutputCoords(coords);
          let b = sharedBuf[${t}];`:`let a = sharedBuf[${t}];
          let b = getBByOutputCoords(coords);`;e=`
        fn binaryOperation(a : f32, b : f32) -> f32 {
          ${zm(this.op,this.isVec4)}
        }
        var<workgroup> sharedBuf : array<f32, ${this.lastDimensionSize}>;
        ${lt()}

          // Fill in the shared memory buffer. Here we need a loop to make sure
          // that all data in A|B are uploaded when |sharedMemorySize| is larger
          // than work group size.
          for(var localIndex = i32(localId.x); localIndex < ${this.lastDimensionSize}; localIndex = localIndex + ${this.workGroupSize[0]}) {
            sharedBuf[localIndex] = f32(${this.useSharedMemoryWithB?"B":"A"}[localIndex]);
          }
          workgroupBarrier();

          for(var i = 0; i < ${this.workPerThread}; i = i + 1) {
            let flatIndex = index * ${this.workPerThread} + i;
            if(flatIndex < uniforms.size) {
              let coords = getCoordsFromIndex(flatIndex);

              ${n}
              setOutputAtIndex(flatIndex, binaryOperation(a, b));
            }
          }
        }
        `}else{let t=this.type==="vec4"?"vec4<f32>":"f32",n=zm(this.op,this.isVec4);e=`
       fn binaryOperation(a : ${t}, b : ${t}) -> ${t} {
         ${n}
       }
       ${lt()}
         if (index < uniforms.size) {
           let a = getAByOutputIndex(index);
           let b = getBByOutputIndex(index);
           setOutputAtIndex(index, binaryOperation(a, b));
         }
       }
       `}return e}};function Fs(e){let{inputs:t}=e,{x:n}=t;return e.backend.incRef(n.dataId),{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}var t2e={kernelName:Ro,backendName:"webgpu",kernelFunc:Fs};function pd(e){let{inputs:t,backend:n}=e,{real:s,imag:r}=t,a=n.makeTensorInfo(s.shape,"complex64"),o=n.tensorMap.get(a.dataId),i=Fs({inputs:{x:s},backend:n}),l=Fs({inputs:{x:r},backend:n});return o.complexTensorInfos={real:i,imag:l},a}var n2e={kernelName:zp,backendName:"webgpu",kernelFunc:pd},Lh=class{constructor(e,t){this.variableNames=["A"],this.size=!0;let n=128;this.workGroupSize=[n,1,1],this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.op=t,this.shaderKey=`unary_${t}`}getUserCode(){return`
      fn unaryOperation(a : f32) -> f32 {
        ${Fi(this.op,!1)}
      }
      ${lt()}
        if (index < uniforms.size) {
          let a = getAByOutputIndex(index);
          setOutputAtIndex(index, unaryOperation(a));
        }
      }
      `}};function Dn({opType:e,cpuKernelImpl:t,dtype:n}){return({inputs:s,backend:r})=>{let{x:a}=s,o=r,i=n||a.dtype;if(o.shouldExecuteOnCPU([a])&&t!=null){let u=o.tensorMap.get(a.dataId),c=t(u.values,i);return o.makeTensorInfo(a.shape,i,c)}let l=new Lh(a.shape,e);return o.runWebGPUProgram(l,[a],i)}}function os({opType:e,cpuKernelImpl:t,supportsComplex:n=!1,dtype:s}){return({inputs:r,backend:a})=>{let{a:o,b:i}=r,l=a;if(n&&o.dtype==="complex64"){let p=l.tensorMap.get(o.dataId),d=l.tensorMap.get(i.dataId),h,f;if(e!==Ye.MUL)[h,f]=[[p.complexTensorInfos.real,d.complexTensorInfos.real],[p.complexTensorInfos.imag,d.complexTensorInfos.imag]].map(g=>{let[y,x]=g,A={dataId:y.dataId,dtype:y.dtype,shape:o.shape},b={dataId:x.dataId,dtype:x.dtype,shape:i.shape},w=new hy(e,o.shape,i.shape);return l.runWebGPUProgram(w,[A,b],On(y.dtype,x.dtype))});else{let g=new W7(Ye.COMPLEX_MULTIPLY_REAL,o.shape,i.shape),y=new W7(Ye.COMPLEX_MULTIPLY_IMAG,o.shape,i.shape),x=[{dataId:p.complexTensorInfos.real.dataId,dtype:p.complexTensorInfos.real.dtype,shape:o.shape},{dataId:p.complexTensorInfos.imag.dataId,dtype:p.complexTensorInfos.imag.dtype,shape:o.shape},{dataId:d.complexTensorInfos.real.dataId,dtype:d.complexTensorInfos.real.dtype,shape:i.shape},{dataId:d.complexTensorInfos.imag.dataId,dtype:d.complexTensorInfos.imag.dtype,shape:i.shape}];h=l.runWebGPUProgram(g,x,"float32"),f=l.runWebGPUProgram(y,x,"float32")}let m=pd({inputs:{real:h,imag:f},backend:l});return l.disposeData(h.dataId),l.disposeData(f.dataId),m}let u=s||On(o.dtype,i.dtype);if((o.dtype==="string"||i.dtype==="string"||l.shouldExecuteOnCPU([o,i]))&&t!=null){let p=l.tensorMap.get(o.dataId).values,d=l.tensorMap.get(i.dataId).values,h=o.dtype==="string"?C.fromUint8ToStringArray(p):p,f=o.dtype==="string"?C.fromUint8ToStringArray(d):d,[m,g]=t(o.shape,i.shape,h,f,u);return l.makeTensorInfo(g,u,m)}let c=new hy(e,o.shape,i.shape);return l.runWebGPUProgram(c,[o,i],u)}}var{addImpl:s2e,ceilImpl:r2e,concatImpl:a2e,equalImpl:o2e,expImpl:i2e,expm1Impl:l2e,floorImpl:u2e,gatherNdImpl:c2e,gatherV2Impl:d2e,greaterEqualImpl:p2e,greaterImpl:h2e,lessEqualImpl:f2e,lessImpl:m2e,logImpl:g2e,maxImpl:y2e,maximumImpl:A2e,minimumImpl:x2e,multiplyImpl:b2e,negImpl:v2e,notEqualImpl:w2e,prodImpl:k2e,rangeImpl:I2e,rsqrtImpl:S2e,scatterImpl:C2e,simpleAbsImpl:T2e,sliceImpl:N2e,stridedSliceImpl:E2e,stringNGramsImpl:R2e,subImpl:_2e,tileImpl:D2e,topKImpl:$2e,transposeImpl:P2e,uniqueImpl:Fxe}=Sx,F2e=Dn({opType:Fe.ABS,cpuKernelImpl:T2e}),O2e={kernelName:ol,backendName:"webgpu",kernelFunc:F2e},M2e=os({opType:Ye.ADD,cpuKernelImpl:s2e,supportsComplex:!0}),z2e={kernelName:Aa,backendName:"webgpu",kernelFunc:M2e},L2e=class{constructor(e){this.workPerThread=4,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e[0],this.variableNames=e.map((t,n)=>`T${n}`),this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.shaderKey="addN"}getUserCode(){let e=[];this.variableNames.forEach(s=>{e.push(`let v${s} = get${s}ByOutputCoords(coords);`)});let t=this.variableNames.map(s=>`v${s}`).join(" + ");return`
      ${lt()}
        for (var i = 0; i < ${this.workPerThread}; i = i + 1) {
          let flatIndex = index * ${this.workPerThread} + i;
          if (flatIndex < uniforms.size) {
            let coords = getCoordsFromIndex(flatIndex);
            ${e.join(`
        `)}
            setOutputAtIndex(flatIndex, ${t});
          }
        }
      }
    `}};function B2e(e){let{inputs:t,backend:n}=e,s=t;if(s.length===1)return Fs({inputs:{x:s[0]},backend:n});let r=s.map(i=>i.dtype).reduce((i,l)=>On(i,l)),a=s.map(i=>i.shape),o=new L2e(a);return n.runWebGPUProgram(o,s,r)}var W2e={kernelName:co,backendName:"webgpu",kernelFunc:B2e},ZC=class{constructor(e,t,n){this.workGroupSize=[64,1,1],this.variableNames=["x"],this.uniforms="infinityValue : f32,",this.size=!0;let s=[t];C.assertAxesAreInnerMostDims("arg"+n.charAt(0).toUpperCase()+n.slice(1),s,e.length),this.op=n==="min"?"<":">";let[r]=C.computeOutAndReduceShapes(e,s);this.outputShape=r.length===0?[1]:r,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,[1,1,1]),this.inputShape=e,this.shaderKey=`argMinMax${this.op}`}getUserCode(){let e=`
      var<workgroup> xBestIndices : array<i32, ${this.workGroupSize[0]}>;
      var<workgroup> xBestValues : array<f32, ${this.workGroupSize[0]}>;
    `,t=()=>this.inputShape.length===1?"uniforms.xShape":`uniforms.xShape.${Ka(this.inputShape.length-1)}`,n=()=>{let r="";if(this.outputShape.length===1)this.inputShape.length!==1&&(r+="outputCoords,");else for(let a=0;a<this.outputShape.length;a++)r+=`outputCoords.${Ka(a)},`;return r};return`
      fn DIV_CEIL(a : u32, b : u32) -> u32 {
        return ((a - 1u) / b + 1u);
      }

      ${e}

      ${lt()}
        let outputIndex = index / i32(workGroupSizeX);
        let reduceLength = ${t()};

        var bestIndex = i32(localId.x);
        var bestValue = uniforms.infinityValue;
        let outputCoords = getCoordsFromIndex(outputIndex);
        for (var k = i32(localId.x); k < reduceLength && outputIndex < uniforms.size;
            k = k + i32(workGroupSizeX)) {
          let candidate = getX(${n()} k);
          if (!isnan(candidate) && candidate ${this.op} bestValue) {
            bestValue = candidate;
            bestIndex = k;
          }
        }
        xBestValues[localId.x] = bestValue;
        xBestIndices[localId.x] = bestIndex;
        workgroupBarrier();

        var reduceSize = min(u32(reduceLength), workGroupSizeX);
        for (var currentSize = reduceSize / 2u; reduceSize > 1u;
            currentSize = reduceSize / 2u) {
          let interval = DIV_CEIL(reduceSize, 2u);
          if (localId.x < currentSize) {
            let candidate = xBestValues[localId.x + interval];
            if (candidate ${this.op} bestValue) {
              bestValue = candidate;
              xBestValues[localId.x] = bestValue;
              xBestIndices[localId.x] = xBestIndices[localId.x + interval];
            }
          }
          reduceSize = interval;
          workgroupBarrier();
        }

        if (localId.x == 0u && outputIndex < uniforms.size) {
          setOutputAtIndexI32(outputIndex, xBestIndices[localId.x]);
        }
      }
    `}},V2e=class{constructor(e,t){this.variableNames=["A"],this.workGroupSize=[16,16,1];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.dispatchLayout={x:[0],y:[1]},this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[1,1,1]),this.shaderKey="transposeShared"}getUserCode(){return`
      const TILE_DIM = ${this.workGroupSize[0]};
      var<workgroup> tile : array<array<f32, ${this.workGroupSize[0]+1}>, ${this.workGroupSize[0]}>;
      ${C2()}
      fn main(@builtin(local_invocation_id) localId : vec3<u32>,
              @builtin(workgroup_id) workgroupId : vec3<u32>) {
        var x = i32(workgroupId.x) * TILE_DIM + i32(localId.x);
        var y = i32(workgroupId.y) * TILE_DIM + i32(localId.y);
        let width = uniforms.outShape[0];
        let height = uniforms.outShape[1];
        if (x < width && y < height) {
          tile[localId.y][localId.x] = A[y * width + x];
        }
        workgroupBarrier();

        x = i32(workgroupId.y) * TILE_DIM + i32(localId.x);
        y = i32(workgroupId.x) * TILE_DIM + i32(localId.y);
        if (x < height && y < width) {
          setOutputAtIndex((y * height + x), tile[localId.x]
            [localId.y]);
        }
      }
    `}},U2e=class{constructor(e,t){this.variableNames=["A"],this.workPerThread=4,this.workGroupSize=[64,1,1],this.size=!0;let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.newDim=t,this.shaderKey=`transpose_${t}`}getUserCode(){let e=Tn(this.outputShape.length),t=G2e(this.newDim);return`
      ${lt()}

        for(var i = 0; i < ${this.workPerThread}; i = i + 1) {
          let flatIndex = index * ${this.workPerThread} + i;
          if(flatIndex < uniforms.size) {
            let resRC = getCoordsFromIndex(flatIndex);
            setOutputAtIndex(flatIndex, A[getIndexFromCoords${this.outputShape.length}D(
              ${e}(${t}), uniforms.aShape)]);
          }
        }
      }
    `}};function G2e(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=new Array(t);for(let s=0;s<e.length;s++)n[e[s]]=`resRC.${Ka(s)}`;return n.join()}function ya(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{perm:a}=s,o=n,i=r.shape.length,l=new Array(i);for(let c=0;c<l.length;c++)l[c]=r.shape[a[c]];if(n.shouldExecuteOnCPU([r])){let p=o.tensorMap.get(r.dataId).values,d=P2e(p,r.shape,r.dtype,a,l);return n.makeTensorInfo(l,r.dtype,d)}if(r.shape.length===2&&v.arraysEqual(a,[1,0])){let c=new V2e(r.shape,a);return o.runWebGPUProgram(c,[r],r.dtype)}let u=new U2e(r.shape,a);return o.runWebGPUProgram(u,[r],r.dtype)}var H2e={kernelName:Gr,backendName:"webgpu",kernelFunc:ya};function j2e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=ya({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMax",[o[0]],l.shape.length);let c=new ZC(l.shape,o[0],"max"),p=[{type:"float32",data:[Number.NEGATIVE_INFINITY]}],d=n.runWebGPUProgram(c,[l],"int32",p);return u.forEach(h=>n.disposeData(h.dataId)),d}var q2e={kernelName:po,backendName:"webgpu",kernelFunc:j2e};function X2e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=ya({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMin",[o[0]],l.shape.length);let c=new ZC(l.shape,o[0],"min"),p=[{type:"float32",data:[Number.POSITIVE_INFINITY]}],d=n.runWebGPUProgram(c,[l],"int32",p);return u.forEach(h=>n.disposeData(h.dataId)),d}var K2e={kernelName:mc,backendName:"webgpu",kernelFunc:X2e},YC=class{constructor(e,t){this.variableNames=["x"],this.uniforms="stride : vec2<i32>, pad : vec2<i32>, dilation : vec2<i32>, convDims : vec2<i32>, filterDims : vec2<i32>,",this.workGroupSize=[128,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`pool2D_${t}`,this.poolType=t}getUserCode(){let e="resultValue = max(value, resultValue);";this.poolType==="avg"&&(e="resultValue = resultValue + value; count = count + 1.0;");let t="resultValue";return this.poolType==="avg"&&(t="resultValue / count"),`
      ${lt()}
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
          let batch = coords[0];
          let xRCCorner = vec2<i32>(coords.yz) * uniforms.stride - uniforms.pad;
          let xRCorner = xRCCorner.x;
          let xCCorner = xRCCorner.y;

          var resultValue = ${this.poolType==="avg"?"0.0":"-1.0 / pow(10.0, -20.0)"};
          var count = 0.0;

          for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + uniforms.dilation.x) {
            let xR = xRCorner + wR;

            if (xR < 0 || xR >= uniforms.convDims.x) {
              continue;
            }

            for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + uniforms.dilation.y) {
              let xC = xCCorner + wC;
              if (xC < 0 || xC >= uniforms.convDims.y) {
                continue;
              }

              let value = getX(batch, xR, xC, coords[3]);
              ${e}
            }
          }

          setOutputAtIndex(index, ${t});
        }
      }
    `}},JC=class{constructor(e){this.variableNames=["x"],this.uniforms="stride : vec2<i32>,",this.workGroupSize=[256,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="poolWithFilterSizeEqualsOne"}getUserCode(){return`
      ${lt()}
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let batch = coords[0];
          let d = coords[3];

          let xRCCorner = coords.yz * uniforms.stride;
          let xRCorner = xRCCorner.x;
          let xCCorner = xRCCorner.y;

          let value = getX(batch, xRCorner, xCCorner, d);
          setOutputAtIndex(index, value);
        }
      }
    `}};function Z2e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1,c=C.computePool2DInfo(r.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Fs({inputs:{x:r},backend:n});let p,d=[{type:"int32",data:[c.strideHeight,c.strideWidth]}];return c.filterHeight===1&&c.filterWidth===1?p=new JC(c):(p=new YC(c,"avg"),d.push({type:"int32",data:[c.padInfo.top,c.padInfo.left]},{type:"int32",data:[c.dilationHeight,c.dilationWidth]},{type:"int32",data:[c.inHeight,c.inWidth]},{type:"int32",data:[c.effectiveFilterHeight,c.effectiveFilterWidth]})),n.runWebGPUProgram(p,[r],r.dtype,d)}var Y2e={kernelName:ho,backendName:"webgpu",kernelFunc:Z2e};function J2e(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;return ib({a:r,b:a,transposeA:o,transposeB:i,backend:n})}var Q2e={kernelName:fo,backendName:"webgpu",kernelFunc:J2e},e1e=class{constructor(e,t){this.variableNames=["source"],this.workPerThread=1,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.rank=t.length,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.start=e,this.uniforms=`start : ${Tn(e.length)}, `,this.shaderKey="slice"}getUserCode(){let e=Tn(this.rank),t=t1e(this.rank),n;return this.start.length===1?n=this.outputShape.map((r,a)=>"sourceLoc = uniforms.start + coords;"):n=this.outputShape.map((r,a)=>`sourceLoc.${fy[a]} = uniforms.start[${a}] + coords.${fy[a]};`),`
      ${lt()}
        if (index < uniforms.size) {
          var sourceLoc : ${e};
          let coords = getCoordsFromIndex(index);
          ${n.join(`
`)}
          setOutputAtIndex(index, getSource(${t}));
        }
      }
    `}},fy=["x","y","z","w","u","v"];function t1e(e){if(e===1)return"sourceLoc";if(e<=6)return fy.slice(0,e).map(t=>`sourceLoc.${t}`).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}function hd(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,size:o}=s,[i,l]=Ut.parseSliceParams(r,a,o);if(Ut.assertParamsValid(r,i,l),n.shouldExecuteOnCPU([r])||r.dtype==="string"){let p=n.tensorMap.get(r.dataId),d=N2e(p.values,i,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,d)}if(v.sizeFromShape(l)===0)return n.makeTensorInfo(l,r.dtype,[]);let u=new e1e(i,l),c=[{type:"int32",data:i}];return n.runWebGPUProgram(u,[r],r.dtype,c)}var n1e={kernelName:Fl,backendName:"webgpu",kernelFunc:hd},s1e=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s;v.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGPU backend not implemented yet");let i=a.reduce((x,A)=>x*A),l=C.getReshaped(r.shape,a,i),u=C.getPermuted(l.length,a.length),c=C.getReshapedPermuted(r.shape,a,i),p=C.getSliceBeginCoords(o,a.length),d=C.getSliceSize(c,o,a.length),h=[],f=Ue({inputs:{x:r},backend:n,attrs:{shape:l}}),m=ya({inputs:{x:f},backend:n,attrs:{perm:u}}),g=Ue({inputs:{x:m},backend:n,attrs:{shape:c}}),y=hd({inputs:{x:g},backend:n,attrs:{begin:p,size:d}});return h.push(f),h.push(m),h.push(g),h.forEach(x=>n.disposeData(x.dataId)),y},r1e={kernelName:il,backendName:"webgpu",kernelFunc:s1e},QC=os({opType:Ye.NOT_EQUAL,dtype:"bool",cpuKernelImpl:w2e}),a1e={kernelName:Il,backendName:"webgpu",kernelFunc:QC};function Bh(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.tensorMap.get(s.dataId);return Fs({inputs:{x:r.complexTensorInfos.real},backend:n})}var o1e={kernelName:jp,backendName:"webgpu",kernelFunc:Bh};function i1e(e,t){let n=new Lh(e.shape,Fe.TO_INT),s=t.runWebGPUProgram(n,[e],"int32");return{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}function my(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dtype:a}=s;if(a==="complex64"){if(r.dtype==="complex64")return Fs({inputs:{x:r},backend:n});let o=Wt(r.shape),i=my({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=pd({inputs:{real:i,imag:o},backend:n});return o.dispose(),n.disposeData(i.dataId),l}if(r.dtype==="complex64"){let o=Bh({inputs:{input:r},backend:n}),i=my({inputs:{x:o},backend:n,attrs:{dtype:a}});return n.disposeData(o.dataId),i}if(!v.hasEncodingLoss(r.dtype,a)){let o=Fs({inputs:{x:r},backend:n});return{dataId:o.dataId,shape:o.shape,dtype:a}}if(a==="int32")return i1e(r,n);if(a==="bool"){let o=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),l=QC({inputs:{a:r,b:o},backend:n});return n.disposeData(o.dataId),l}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${a}`)}var l1e={kernelName:mo,backendName:"webgpu",kernelFunc:my},u1e=Dn({opType:Fe.CEIL,cpuKernelImpl:r2e}),c1e={kernelName:go,backendName:"webgpu",kernelFunc:u1e},d1e=class{constructor(e){this.variableNames=["A"],this.uniforms="minVal : f32, maxVal : f32,",this.workPerThread=4,this.workGroupSize=[64,1,1],this.isVec4=!0,this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.shaderKey="clipVec4"}getUserCode(){return`
      ${lt()}
        if(index < uniforms.size) {
          let value = getAByOutputIndex(index);
          var clampedValue : vec4<f32>;
          for (var i = 0; i < 4; i = i + 1) {
            if (isnan(value[i])) {
              clampedValue[i] = value[i];
            } else {
              clampedValue[i] = clamp(value[i], uniforms.minVal, uniforms.maxVal);
            }
          }

          setOutputAtIndex(index, clampedValue);
        }
      }
    `}},p1e=class{constructor(e){this.variableNames=["A"],this.uniforms="minVal : f32, maxVal : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="clip"}getUserCode(){return`
      ${lt()}
        if(index < uniforms.size) {
          let value = getAByOutputIndex(index);
          if (isnan(value)) {
            setOutputAtIndex(index, value);
            return;
          }
          setOutputAtIndex(index, clamp(value, uniforms.minVal, uniforms.maxVal));
        }
      }
    `}};function h1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{clipValueMin:a,clipValueMax:o}=s,i,l=[{type:"float32",data:[a]},{type:"float32",data:[o]}];return v.sizeFromShape(r.shape)%4===0?i=new d1e(r.shape):i=new p1e(r.shape),n.runWebGPUProgram(i,[r],r.dtype,l)}var f1e={kernelName:xa,backendName:"webgpu",kernelFunc:h1e},m1e=class{constructor(e){this.uniforms="",this.workPerThread=4,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=C.computeOutShape(e,1),this.variableNames=e.map((t,n)=>`T${n}`),this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.offsetLength=e.length-1;for(let t=0;t<this.offsetLength;t++)this.uniforms+=`offset${t} : i32,`;this.shaderKey="concat"}getUserCode(){let e=[];if(this.offsetLength>0){e.push("if (yC < uniforms.offset0){ setOutputAtCoords(coords.x, coords.y, getT0(yR, yC)); }");for(let r=1;r<this.offsetLength;r++)e.push(`else if (yC < uniforms.offset${[r]}){ setOutputAtCoords(coords.x, coords.y, getT${r}(yR, yC - uniforms.offset${r-1})); }`);let n=this.offsetLength,s=this.offsetLength-1;e.push(`else { setOutputAtCoords(coords.x, coords.y, getT${n}(yR, yC - uniforms.offset${s})); }`)}else e.push("setOutputAtCoords(coords.x, coords.y, getT0(yR, yC));");return`
      ${lt()}
        for(var i = 0; i < ${this.workPerThread}; i = i + 1) {
          let flatIndex = index * ${this.workPerThread} + i;
          if(flatIndex < uniforms.size) {
            let coords = getCoordsFromIndex(flatIndex);
            let yR = coords.x;
            let yC = coords.y;

            ${e.join(`
        `)}
          }
        }
      }
    `}};function N2(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.tensorMap.get(s.dataId);return Fs({inputs:{x:r.complexTensorInfos.imag},backend:n})}var g1e={kernelName:Up,backendName:"webgpu",kernelFunc:N2};function pp(e,t,n){let s=e[0].dtype;if(s==="complex64"){let f=e.map(A=>Bh({inputs:{input:A},backend:n})),m=e.map(A=>N2({inputs:{input:A},backend:n})),g=pp(f,t,n),y=pp(m,t,n),x=pd({inputs:{real:g,imag:y},backend:n});return f.forEach(A=>n.disposeData(A.dataId)),m.forEach(A=>n.disposeData(A.dataId)),n.disposeData(g.dataId),n.disposeData(y.dataId),x}let r=n.shouldExecuteOnCPU(e);if(s==="string"&&(r=!0),r){let f=e.map(w=>{let k=v.sizeFromShape(w.shape.slice(t));return Ue({inputs:{x:w},backend:n,attrs:{shape:[-1,k]}})}),m=f.map(w=>({vals:n.readSync(w.dataId),shape:w.shape})),g=C.computeOutShape(f.map(w=>w.shape),1),y=f[0].shape[0]===1,x=a2e(m,g,s,y),A=C.computeOutShape(e.map(w=>w.shape),t),b=n.makeTensorInfo(A,s,x);return f.forEach(w=>n.disposeData(w.dataId)),b}let a=n.device.limits.maxStorageBuffersPerShaderStage-1;if(e.length>a){let f=[];for(let g=0;g<e.length;g+=a){let y=e.slice(g,g+a);f.push(pp(y,t,n))}let m=pp(f,t,n);for(let g of f)n.disposeData(g.dataId);return m}let{tensors2D:o,outShape:i}=y1e(e,t,n),l=o.map(f=>f.shape),u=new m1e(l),c=[],p=new Array(l.length-1);if(p.length>0){p[0]=l[0][1],c.push({type:"int32",data:[p[0]]});for(let f=1;f<p.length;f++)p[f]=p[f-1]+l[f][1],c.push({type:"int32",data:[p[f]]})}let d=n.runWebGPUProgram(u,o,o[0].dtype,c);o.forEach(f=>n.disposeData(f.dataId));let h=Ue({inputs:{x:d},backend:n,attrs:{shape:i}});return n.disposeData(d.dataId),h}function y1e(e,t,n){let s=C.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>Ue({inputs:{x:a},backend:n,attrs:{shape:[v.sizeFromShape(a.shape.slice(0,t)),v.sizeFromShape(a.shape.slice(t))]}})),outShape:s}}function eT(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s,a=v.parseAxisParam(r,t[0].shape)[0],o=C.computeOutShape(t.map(u=>u.shape),a);if(v.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let i=t.filter(u=>v.sizeFromShape(u.shape)>0);if(i.length===1)return Fs({inputs:{x:i[0]},backend:n});let l=i.map(u=>u.shape);return C.assertParamsConsistent(l,a),pp(i,a,n)}var A1e={kernelName:ll,backendName:"webgpu",kernelFunc:eT};function x1e(e,t,n,s,r=!1,a=null,o=!1,i=4,l=4,u=4){let c=R=>{switch(R){case 1:return"resData = x[xIndex];";case 3:return"resData = vec3<f32>(x[xIndex], x[xIndex + 1], x[xIndex + 2]);";case 4:return"resData = x[xIndex / 4];";default:throw new Error(`innerElementSize ${R} is not supported.`)}},p=R=>{switch(R){case 1:return"return W[row * uniforms.wShape[3] + colIn];";case 4:return"return W[row * uniforms.wShape[3] / 4 + colIn];";default:throw new Error(`innerElementSize ${R} is not supported.`)}},d=e?`
      let coord = vec4<i32>(batch, xRow, xCol, xCh);
      `:`
      let coord = vec4<i32>(batch, xCh, xRow, xCol);
      `,h=e?`
      let coords = vec4<i32>(
        batch,
        row / outWidth,
        row % outWidth,
        col);
      `:`
      let coords = vec4<i32>(
        batch,
        row,
        col / outWidth,
        col % outWidth);
      `,f=e?"uniforms.xShape[1]":"uniforms.xShape[2]",m=e?"uniforms.xShape[2]":"uniforms.xShape[3]",g=e?"row":"col",y=e?"col":"row",x=`
      let inChannels = uniforms.wShape[2];
      let outWidth = ${e?"uniforms.outShape[2]":"uniforms.outShape[3]"};
      let outRow = ${g} / outWidth;
      let outCol = ${g} % outWidth;

      let WRow = ${y} / (uniforms.filterDims[1] * inChannels);
      let WCol = ${y} / inChannels % uniforms.filterDims[1];
      let xRow = outRow * uniforms.stride[0] + uniforms.dilation[0] * WRow - uniforms.pad[0];
      let xCol = outCol * uniforms.stride[1] + uniforms.dilation[1] * WCol - uniforms.pad[1];
      let xCh = ${y} % inChannels;
      var resData = ${nn(i)}(0.0);
      // The bounds checking is always needed since we use it to pad zero for
      // the 'same' padding type.
      if (xRow >= 0 && xRow < ${f} && xCol >= 0 && xCol < ${m}) {
        ${d}
        let xIndex = getIndexFromCoords4D(coord, uniforms.xShape);
        ${c(i)}
      }
      return resData;`,A=e?t&&s?`
      let col = colIn * ${i};
      ${x}`:`
      let col = colIn * ${i};
      if (row < uniforms.dimAOuter && col < uniforms.dimInner) {
        ${x}
      }
      return ${nn(i)}(0.0);`:s&&n?`
      let col = colIn * ${i};
      ${x}`:`
      let col = colIn * ${i};
      if (row < uniforms.dimInner && col < uniforms.dimBOuter) {
        ${x}
      }
      return ${nn(i)}(0.0);`,b=`${p(l)}`,w=nn(u),k=nn(e?i:l),S=nn(e?l:i);return`
      ${Sa(a,o,u===4,4)}
      fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${k} {
        ${e?A:b}
      }

      fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${S} {
        ${e?b:A}
      }

      fn mm_write(batch: i32, row : i32, colIn : i32, valueIn : ${w}) {
        let col = colIn * ${u};
        if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)
        {
        var value = valueIn;
        let outWidth = ${e?"uniforms.outShape[2]":"uniforms.outShape[3]"};
        ${h}
        ${cd(r,a)}
        setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
        }
      }`}var b1e=class{constructor(e,t,n,s,r=!1,a=null,o=!1){this.variableNames=["x","W"],this.uniforms="filterDims : vec2<i32>, pad : vec2<i32>, stride : vec2<i32>, dilation : vec2<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=e.outShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.isVec4=((e.inChannels%4===0||e.inChannels%3===0)&&this.isChannelsLast||e.outWidth%4===0&&!this.isChannelsLast)&&e.outChannels%4===0,this.dispatchLayout=this.isChannelsLast?{x:[3],y:[1,2],z:[0]}:{x:[2,3],y:[1],z:[0]},this.workGroupSize=nb(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=sb(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,this.elementsPerThread),this.isVec4?(this.isChannelsLast&&e.inChannels%4!==0?(this.innerElementSize=3,this.variableTypes=["f32","vec4<f32>"]):(this.innerElementSize=4,this.variableTypes=["vec4<f32>","vec4<f32>"]),r&&(this.variableNames.push("bias"),this.variableTypes.push("vec4<f32>")),o&&(this.variableNames.push("preluActivationWeights"),this.variableTypes.push("vec4<f32>"))):(this.innerElementSize=this.elementsPerThread[0],r&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights")),this.addBias=r,this.activation=a,this.hasPreluActivationWeights=o,this.tileAOuter=this.workGroupSize[1]*this.elementsPerThread[1],this.tileBOuter=this.workGroupSize[0]*this.elementsPerThread[0],this.tileInner=Math.max(this.workGroupSize[0]*this.innerElementSize,this.workGroupSize[1]),this.fitAOuter=t%this.tileAOuter===0,this.fitBOuter=n%this.tileBOuter===0,this.fitInner=s%this.tileInner===0,this.shaderKey=`conv2DMM_${this.elementsPerThread}_${this.activation}}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.innerElementSize}_${this.isChannelsLast}`}getUserCode(){let e=this.isVec4?ob(this.elementsPerThread,this.tileAOuter,this.tileBOuter,this.tileInner,this.innerElementSize,!this.isChannelsLast):ab(this.elementsPerThread,this.workGroupSize,!this.isChannelsLast,this.tileInner),t=this.isVec4?[this.isChannelsLast?this.innerElementSize:4,4,4]:[1,1,1];return`
    ${x1e(this.isChannelsLast,this.fitAOuter,this.fitBOuter,this.fitInner,this.addBias,this.activation,this.hasPreluActivationWeights,t[0],t[1],t[2])}
    ${e}
  `}};function V7(e,t){let n=e.length;return n>=3?t?[...e.slice(0,-3),e[n-3]*e[n-2],e[n-1]]:[...e.slice(0,-3),e[n-3],e[n-2]*e[n-1]]:!t&&n===1&&e[0]>1?[e[0],1]:null}function v1e({x:e,filter:t,convInfo:n,backend:s,bias:r=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let l=n.dataFormat==="channelsLast",u=!l,c=!1,p=l&&n.filterHeight===n.inHeight&&n.filterWidth===n.inWidth&&n.padInfo.type==="VALID",d=[],h,f;if(p){let y=n.inHeight*n.inWidth*n.inChannels;h=Ue({inputs:{x:e},backend:s,attrs:{shape:[1,n.batchSize,y]}}),f=Ue({inputs:{x:t},backend:s,attrs:{shape:[1,y,n.outChannels]}})}else h=Ue({inputs:{x:e},backend:s,attrs:{shape:l?[n.batchSize,n.inHeight*n.inWidth,n.inChannels]:[n.batchSize,n.inChannels,n.inHeight*n.inWidth]}}),f=Ue({inputs:{x:t},backend:s,attrs:{shape:[1,n.inChannels,n.outChannels]}});if(d.push(h),d.push(f),a!=null){let y=V7(a.shape,l);y!=null&&(a=Ue({inputs:{x:a},backend:s,attrs:{shape:y}}),d.push(a))}if(r!=null){let y=V7(r.shape,l);y!=null&&(r=Ue({inputs:{x:r},backend:s,attrs:{shape:y}}),d.push(r))}let m=ib({a:l?h:f,b:l?f:h,transposeA:u,transposeB:c,backend:s,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o}),g=Ue({inputs:{x:m},backend:s,attrs:{shape:n.outShape}});d.push(m);for(let y of d)s.disposeData(y.dataId);return g}function tT({x:e,filter:t,convInfo:n,backend:s,bias:r=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let l=r!=null,u=a!=null,c=n.dataFormat==="channelsLast";if(c&&n.filterHeight===n.inHeight&&n.filterWidth===n.inWidth&&n.padInfo.type==="VALID"||n.filterHeight===1&&n.filterWidth===1&&n.dilationHeight===1&&n.dilationWidth===1&&n.strideHeight===1&&n.strideWidth===1&&(n.padInfo.type==="SAME"||n.padInfo.type==="VALID"))return v1e({x:e,filter:t,convInfo:n,backend:s,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o});let d=c?n.outHeight*n.outWidth:n.outChannels,h=c?n.outChannels:n.outHeight*n.outWidth,f=n.filterHeight*n.filterWidth*n.inChannels,m=[n.padInfo.top,n.padInfo.left],g=[{type:"int32",data:[n.filterHeight,n.filterWidth]},{type:"int32",data:[...m]},{type:"int32",data:[n.strideHeight,n.strideWidth]},{type:"int32",data:[n.dilationHeight,n.dilationWidth]},{type:"int32",data:[d]},{type:"int32",data:[h]},{type:"int32",data:[f]}],y=new b1e(n,d,h,f,l,i,u),x=[],A=[e,t];l&&(!c&&r.shape.length===1&&(r=Ue({inputs:{x:r},backend:s,attrs:{shape:[r.shape[0],1,1]}}),x.push(r)),A.push(r)),u&&(!c&&a.shape.length===1&&(a=Ue({inputs:{x:a},backend:s,attrs:{shape:[a.shape[0],1,1]}}),x.push(a)),A.push(a)),i==="leakyrelu"&&(g.push({type:"float32",data:[o]}),y.uniforms+=" alpha : f32,");let b=s.runWebGPUProgram(y,A,e.dtype,g);for(let w of x)s.disposeData(w.dataId);return b}function w1e(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=n,p=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,a.shape,o,u,i,c,!1,p);return tT({x:r,filter:a,convInfo:d,backend:s})}var k1e={kernelName:yo,backendName:"webgpu",kernelFunc:w1e};function I1e(e=4){let t=a=>{switch(a){case 1:return"return W[getIndexFromCoords4D(coord, uniforms.wShape)];";case 4:return`
            let coord1 = vec4<i32>(coordX, coordY, col + 1, rowInner);
            let coord2 = vec4<i32>(coordX, coordY, col + 2, rowInner);
            let coord3 = vec4<i32>(coordX, coordY, col + 3, rowInner);
            let v0 = W[getIndexFromCoords4D(coord, uniforms.wShape)];
            let v1 = W[getIndexFromCoords4D(coord1, uniforms.wShape)];
            let v2 = W[getIndexFromCoords4D(coord2, uniforms.wShape)];
            let v3 = W[getIndexFromCoords4D(coord3, uniforms.wShape)];
            return vec4<f32>(v0, v1, v2, v3);
            `;default:throw new Error(`innerElementSize ${a} is not supported.`)}},s=`if (row < uniforms.dimAOuter && col < uniforms.dimInner) {
        ${`
      let outRow = row / uniforms.outShape[2];
      let outCol = row % uniforms.outShape[2];

      let WRow = col / (uniforms.filterDims[1] * uniforms.outBackprop[3]);
      let WCol = col / uniforms.outBackprop[3] % uniforms.filterDims[1];
      let xR = f32(outRow - uniforms.pads[0] + WRow) / f32(uniforms.stride[0]);
      let xC = f32(outCol - uniforms.pads[1] + WCol) / f32(uniforms.stride[1]);
      if (xR < 0.0 || xR >= f32(uniforms.outBackprop[1]) || fract(xR) > 0.0) {
        return ${nn(e)}(0.0);
      }
      if (xC < 0.0 || xC >= f32(uniforms.outBackprop[2]) || fract(xC) > 0.0) {
        return ${nn(e)}(0.0);
      }
      let coord = vec4<i32>(
          batch,
          i32(xR),
          i32(xC),
          col % uniforms.outBackprop[3]);
      return x[getIndexFromCoords4D(coord, uniforms.xShape)/${e}];`}
      }
      return ${nn(e)}(0.0);`;return`
  fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${nn(e)} {
    let col = colIn * ${e};
    ${s}
  }

  fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${nn(e)} {
    let col = colIn * ${e};
    let coordX = uniforms.filterDims.x - 1 -
        row / (uniforms.filterDims[1] * uniforms.outBackprop[3]);
    let coordY = uniforms.filterDims.y - 1 -
        (row / uniforms.outBackprop[3]) % uniforms.filterDims[1];
    if (row < uniforms.dimInner && col < uniforms.dimBOuter &&
        coordX >= 0 && coordY >= 0) {
      let rowInner = row % uniforms.outBackprop[3];
      let coord = vec4<i32>(coordX, coordY, col, rowInner);
      ${t(e)}
    }
    return ${nn(e)}(0.0);
  }

  fn mm_write(batch: i32, row : i32, colIn : i32, valueInput : ${nn(e)}) {
    let col = colIn * ${e};
    if (row < uniforms.dimAOuter && (col + ${e-1}) < uniforms.dimBOuter) {
      var value = valueInput;
      let outCoord = vec4<i32>(
          batch,
          row / uniforms.outShape[2],
          row % uniforms.outShape[2],
          col);
      result[getIndexFromCoords4D(outCoord, uniforms.outShape)/${e}] = value;
    }
  }`}var S1e=class{constructor(e){this.variableNames=["x","W"],this.uniforms="filterDims : vec2<i32>, pads : vec2<i32>, stride : vec2<i32>, outBackprop : vec4<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=e.inShape,v.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),this.isVec4=e.inChannels%4===0&&e.outChannels%4===0,this.dispatchLayout={x:[3],y:[1,2],z:[0]},this.workGroupSize=nb(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=sb(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,this.elementsPerThread),this.isVec4?(this.innerElementSize=4,this.variableTypes=["vec4<f32>","f32"]):this.innerElementSize=this.elementsPerThread[0],this.tileAOuter=this.workGroupSize[1]*this.elementsPerThread[1],this.tileBOuter=this.workGroupSize[0]*this.elementsPerThread[0],this.tileInner=Math.max(this.workGroupSize[0]*this.innerElementSize,this.workGroupSize[1]),this.shaderKey=`conv2DDerInputMM_${this.isVec4}_${this.elementsPerThread}_${this.innerElementSize}`}getUserCode(){let e=this.isVec4?ob(this.elementsPerThread,this.tileAOuter,this.tileBOuter,this.tileInner,this.innerElementSize):ab(this.elementsPerThread,this.workGroupSize);return`
    ${I1e(this.isVec4?4:1)}
    ${e}
    `}},C1e=class{constructor(e){this.variableNames=["dy","W"],this.uniforms="filterDims : vec2<i32>, pads : vec2<i32>, stride : vec2<i32>, outBackprop : vec4<i32>,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",this.shaderKey=`conv2DDerInput_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?1:2,t=this.isChannelsLast?2:3,n=this.isChannelsLast?3:1;return`
    ${lt()} {
      if(index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let batch = coords[0];
        let d1 = coords[${n}];

        let dyCorner = vec2<i32>(coords[${e}]), coords[${t}]) - uniforms.pads;
        let dyRCorner = dyCorner.x;
        let dyCCorner = dyCorner.y;

        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
        // ? = to be determined. : = across all values in that axis.
        var dotProd = 0.0;
        for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + 1) {
          let dyR = (f32(dyRCorner) + f32(wR)) / f32(uniforms.stride.x);
          let wRPerm = uniforms.filterDims.x - 1 - wR;
          if (dyR < 0.0 || dyR >= f32(uniforms.outBackprop[1]) || fract(dyR) > 0.0 ||
              wRPerm < 0) {
            continue;
          }
          let idyR = dyR;

          for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + 1) {
            let dyC = (f32(dyCCorner) + f32(wC)) / f32(uniforms.stride.y);
            let wCPerm = uniforms.filterDims.y - 1 - wC;
            if (dyC < 0.0 || dyC >= f32(uniforms.outBackprop[2]) ||
                fract(dyC) > 0.0 || wCPerm < 0) {
              continue;
            }
            let idyC = dyC;

            for (var d2 = 0; d2 < uniforms.outBackprop[3]; d2 = d2 + 1) {
              if (${this.isChannelsLast}) {
                let xValue = getDy(batch, idyR, idyC, d2);
                let wValue = getW(wRPerm, wCPerm, d1, d2);
                dotProd = dotProd + xValue * wValue;
              } else {
                let xValue = getDy(batch, d2, idyR, idyC);
                let wValue = getW(wRPerm, wCPerm, d1, d2);
                dotProd = dotProd + xValue * wValue;
              }

            }
          }
        }
        setOutputAtIndex(index, dotProd);
      }
    }
  `}};function T1e(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{inputShape:o,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=s,p=C.convertConv2DDataFormat(u),d=C.computeConv2DInfo(o,a.shape,i,1,l,c,!1,p),h=[{type:"int32",data:[d.filterHeight,d.filterWidth]},{type:"int32",data:[d.filterHeight-1-d.padInfo.top,d.filterWidth-1-d.padInfo.left]},{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.batchSize,d.outHeight,d.outWidth,d.outChannels]}],f;if(X().getBool("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE"))f=new C1e(d);else{f=new S1e(d);let m=d.inShape[1]*d.inShape[2],g=d.inShape[3],y=d.filterHeight*d.filterWidth*d.outChannels;h.push({type:"uint32",data:[m]},{type:"uint32",data:[g]},{type:"uint32",data:[y]})}return n.runWebGPUProgram(f,[r,a],"float32",h)}var N1e={kernelName:Ao,backendName:"webgpu",kernelFunc:T1e},E1e=Dn({opType:Fe.COS}),R1e={kernelName:xo,backendName:"webgpu",kernelFunc:E1e},_1e=Dn({opType:Fe.COSH}),D1e={kernelName:bo,backendName:"webgpu",kernelFunc:_1e},$1e=class{constructor(e,t,n,s){this.variableNames=["Image","Boxes","BoxInd"],this.uniforms="extrapolationValue : f32,",this.workGroupSize=[64,1,1],this.size=!0;let[r]=t;this.outputShape=[r,n[0],n[1],e],this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.methodId=s==="bilinear"?1:0,this.cropHeightBiggerThan1=this.outputShape[1]>1,this.cropWidthBiggerThan1=this.outputShape[2]>1,this.shaderKey=`cropAndResize_${this.methodId}_${this.cropHeightBiggerThan1}_${this.cropWidthBiggerThan1}`}getUserCode(){let[e,t]=["f32(uniforms.imageShape[1] - 1)","f32(uniforms.imageShape[2] - 1)"],[n,s,r]=this.cropHeightBiggerThan1?[`(${e} / f32(uniforms.outShape[1] - 1))`,"(y2-y1) * height_ratio",`y1*${e} + f32(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${e}`],[a,o,i]=this.cropWidthBiggerThan1?[`(${t} / f32(uniforms.outShape[2] - 1))`,"(x2-x1) * width_ratio",`x1*${t} + f32(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${t}`];return`
      ${lt()}
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let height_ratio = f32(${n});
        let width_ratio = f32(${a});
        let b = coords[0];
        let y = coords[1];
        let x = coords[2];
        let d = coords[3];
        // get box vals
        let y1 = getBoxes(b, 0);
        let x1 = getBoxes(b, 1);
        let y2 = getBoxes(b, 2);
        let x2 = getBoxes(b, 3);
        // get image in batch index
        let bInd = i32(round(getBoxInd(b)));
        if(bInd < 0 || bInd >= uniforms.outShape[0]) {
          return;
        }
        let height_scale = ${s};
        let width_scale = ${o};
        let in_y = ${r};
        if( in_y < 0.0 || in_y > ${e} ) {
          setOutputAtIndex(index, uniforms.extrapolationValue);
          return;
        }
        let in_x = ${i};
        if( in_x < 0.0 || in_x > ${t} ) {
          setOutputAtIndex(index, uniforms.extrapolationValue);
          return;
        }
        let sourceFracIndexCR = vec2<f32>(in_x,in_y);
        if(${this.methodId} == 1) {
          // Compute the four integer indices.
          let sourceFloorCR = vec2<i32>(sourceFracIndexCR);
          let sourceCeilCR = vec2<i32>(ceil(sourceFracIndexCR));
          let topLeft = getImage(bInd, sourceFloorCR.y, sourceFloorCR.x, d);
          let bottomLeft = getImage(bInd, sourceCeilCR.y, sourceFloorCR.x, d);
          let topRight = getImage(bInd, sourceFloorCR.y, sourceCeilCR.x, d);
          let bottomRight = getImage(bInd, sourceCeilCR.y, sourceCeilCR.x, d);
          let fracCR = sourceFracIndexCR - vec2<f32>(sourceFloorCR);
          let top = topLeft + (topRight - topLeft) * fracCR.x;
          let bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
          let newValue = top + (bottom - top) * fracCR.y;
          setOutputAtIndex(index, newValue);
        } else {
          // Compute the coordinators of nearest neighbor point.
          let sourceNearestCR = vec2<i32>(floor(
            sourceFracIndexCR + vec2<f32>(0.5,0.5)));
          let newValue = getImage(
            bInd, sourceNearestCR.y, sourceNearestCR.x, d);
          setOutputAtIndex(index, newValue);
        }
      }
    }
    `}},P1e=e=>{let{inputs:t,backend:n,attrs:s}=e,{image:r,boxes:a,boxInd:o}=t,{cropSize:i,method:l,extrapolationValue:u}=s,c=new $1e(r.shape[3],a.shape,i,l),p=[{type:"float32",data:[u]}];return n.runWebGPUProgram(c,[r,a,o],"float32",p)},F1e={kernelName:cl,backendName:"webgpu",kernelFunc:P1e},Fp;(function(e){e.Prod="*",e.Sum="+"})(Fp||(Fp={}));var U7=class{constructor(e,t,n,s){this.variableNames=["x"],this.uniforms="index : f32,",this.size=!0;let r=128;this.workGroupSize=[r,1,1],this.outputShape=t,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.exclusive=n,this.reverse=s,this.op=e,this.shaderKey=`cum_${this.op}_${this.exclusive}_${this.reverse}`}getUserCode(){let e=this.outputShape.length,t=this.op===Fp.Prod?"1.0":"0.0",n=this.exclusive?t:`getX(${G7(e,"coords",this.op)})`,s=this.outputShape[this.outputShape.length-1],r="",a="";return this.exclusive?(r=this.reverse?`end != ${s-1}`:"end != 0",a=this.reverse?"end + 1":"end - 1"):(r=this.reverse?`end + pow2 < ${s}`:"end >= pow2",a=this.reverse?"end + pow2":"end - pow2"),`
      ${lt()}
       if (index < uniforms.size) {
         var coords = getCoordsFromIndex(index);

         let end = ${H7(e,"coords",this.op)};
         var val = ${n};
         let pow2 = i32(pow(2.0, uniforms.index));
         if (${r}) {
           let idx = ${a};
           ${H7(e,"coords",this.op)} = idx;
           val ${this.op}= getX(${G7(e,"coords",this.op)});
         }
         setOutputAtIndex(index, val);
       }
      }
    `}};function G7(e,t,n){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 ${n} for rank ${e} is not yet supported`)}function H7(e,t,n){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function nT(e,t,n,s,r,a){let o=t.shape.length,i=C.getAxesPermutation([s],o),l=t;i!=null&&(l=ya({inputs:{x:t},backend:n,attrs:{perm:i}}));let u=C.getInnerMostAxes(1,o)[0];if(u!==o-1)throw new Error(`WebGPU cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${s}`);let c=l.shape[u],p=Fs({inputs:{x:l},backend:n});for(let d=0;d<=Math.ceil(Math.log2(c))-1;d++){let h=new U7(e,l.shape,!1,a),f=p,m=[{type:"float32",data:[d]}];p=n.runWebGPUProgram(h,[p],p.dtype,m),n.disposeData(f.dataId)}if(r){let d=new U7(e,l.shape,r,a),h=p,f=[{type:"float32",data:[0]}];p=n.runWebGPUProgram(d,[p],p.dtype,f),n.disposeData(h.dataId)}if(i!=null){let d=C.getUndoAxesPermutation(i),h=ya({inputs:{x:p},backend:n,attrs:{perm:d}});return n.disposeData(p.dataId),n.disposeData(l.dataId),h}return p}function O1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;return nT(Fp.Prod,r,n,a,o,i)}var M1e={kernelName:ul,backendName:"webgpu",kernelFunc:O1e};function z1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;return nT(Fp.Sum,r,n,a,o,i)}var L1e={kernelName:vo,backendName:"webgpu",kernelFunc:z1e},B1e=class{constructor(e,t){this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.uniforms="blockSize : i32,",this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`depthToSpace_${t}`,this.dataFormat=t}getUserCode(){return`
      ${lt()}
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let b = coords[0];
          let h = ${this.getHeightCoordString()};
          let w = ${this.getWidthCoordString()};
          let d = ${this.getDepthCoordString()};

          let in_h = h / uniforms.blockSize;
          let offset_h = h % uniforms.blockSize;
          let in_w = w / uniforms.blockSize;
          let offset_w = w % uniforms.blockSize;
          let offset_d = (offset_h * uniforms.blockSize + offset_w) *
            ${this.getOutputDepthSize()};
          let in_d = d + offset_d;

          let rlt = ${this.getInputSamplingString()};
          setOutputAtIndex(index, rlt);
        }
      }`}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?"uniforms.outShape[3]":"uniforms.outShape[1]"}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function W1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockSize:a,dataFormat:o}=s,i=r.shape[0],l=o==="NHWC"?r.shape[1]:r.shape[2],u=o==="NHWC"?r.shape[2]:r.shape[3],c=o==="NHWC"?r.shape[3]:r.shape[1],p=l*a,d=u*a,h=c/(a*a),f=o==="NHWC"?[i,p,d,h]:[i,h,p,d],m=[{type:"int32",data:[a]}],g=new B1e(f,o);return n.runWebGPUProgram(g,[r],r.dtype,m)}var V1e={kernelName:dl,backendName:"webgpu",kernelFunc:W1e},U1e=class{constructor(e,t,n,s=!1,r=null,a=!1){this.variableNames=["x","W"],this.uniforms="pad : vec2<i32>, inDims : vec2<i32>,",this.workGroupSize=[16,16,1],this.outputShape=e,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),s&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),this.addBias=s,this.activation=r,this.hasPreluActivation=a,this.filterHeight=t,this.filterWidth=n,this.shaderKey=`depthwiseNCHW_${this.activation}_${this.filterHeight}_${this.filterWidth}`}getUserCode(){let e=this.filterWidth*this.filterHeight,t=this.workGroupSize[0]*this.workGroupSize[1]*this.workGroupSize[2],n=this.workGroupSize[1]+this.filterHeight-1,s=this.workGroupSize[0]+this.filterWidth-1;return`
      ${Sa(this.activation,this.hasPreluActivation,!1,4)}

      var<workgroup> mm_Asub : array<array<f32, ${s}>, ${n}>;
      var<workgroup> mm_Bsub : array<array<f32, ${this.filterWidth}>, ${this.filterHeight}>;
      fn readX(batch : i32, channel : i32, row : i32, col : i32) -> f32 {
        var value = 0.0;
        if (row >=0 && row < uniforms.inDims[0] && col >=0 && col < uniforms.inDims[1])
        {
          value = getX(batch, channel, row, col);
        }
        return value;
      }

      ${C2()}
      fn main(@builtin(local_invocation_id) LocalId : vec3<u32>,
              @builtin(global_invocation_id) GlobalId : vec3<u32>,
              @builtin(local_invocation_index) LocalIndex: u32,
              @builtin(num_workgroups) NumWorkgroups: vec3<u32>) {
        localId = LocalId;
        globalId = GlobalId;
        let localIndex = i32(LocalIndex);
        numWorkgroups = NumWorkgroups;
        let coords = getOutputCoords();
        let batch = coords[0];
        let xRCCorner = vec2<i32>(coords.zw) - uniforms.pad;
        let channelMul = uniforms.wShape[3];
        let d1 = coords[1] / channelMul;
        let q = coords[1] % channelMul;

        let inputRowStart = xRCCorner.x;
        let inputColStart = xRCCorner.y;

        let localRow = i32(localId.y);
        let localCol = i32(localId.x);

        // Load one tile of X into local memory.
        for (var inputRow = localRow; inputRow < ${n}; inputRow = inputRow + ${this.workGroupSize[1]}) {
          for (var inputCol = localCol; inputCol < ${s}; inputCol = inputCol + ${this.workGroupSize[0]}) {
            let rowOffset = inputRow - localRow;
            let colOffset = inputCol - localCol;
            mm_Asub[inputRow][inputCol] = readX(batch, d1, inputRowStart + rowOffset, inputColStart + colOffset);
          }
        }

        // Load one tile of W into local memory.
        var wIndex = localIndex;
        ${e<t?`if (wIndex < ${e})`:`for(; wIndex < ${e}; wIndex = wIndex + ${t})`}

        {
          let wRow = wIndex / ${this.filterWidth};
          let wCol = wIndex % ${this.filterWidth};
          mm_Bsub[wRow][wCol] = getW(wRow, wCol, d1, q);
        }

        workgroupBarrier();

        var value = 0.0;
        for (var wR = 0; wR < ${this.filterHeight}; wR = wR + 1) {
          for (var wC = 0; wC < ${this.filterWidth}; wC = wC + 1) {
            let xVal = mm_Asub[localRow + wR][localCol + wC];
            let wVal = mm_Bsub[wR][wC];
            value = fma(xVal, wVal, value);
          }
        }
        ${cd(this.addBias,this.activation)}
        if (coordsInBounds4D(coords, uniforms.outShape)) {
          setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
        }
      }
    `}},sT=class{constructor(e,t=!1,n=null,s=!1){this.variableNames=["x","W"],this.uniforms="pad : vec2<i32>, inDims : vec2<i32>,",this.workGroupSize=[4,4,4],this.isVec4=!0,this.outputShape=e.outShape,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[4,4,1]),v.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),t&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=n,this.hasPreluActivation=s,this.shaderKey=`depthwiseVec4_${n}_${this.convInfo.filterHeight}_${this.convInfo.filterWidth}`}getUserCode(){let e=4+this.convInfo.filterWidth-1;return`
      ${Sa(this.activation,this.hasPreluActivation,!0,4)}
      fn readX(batch : i32, row : i32, col : i32, channel : i32) -> vec4<f32> {
        var value = vec4<f32>(0.0);
        if (row >=0 && row < uniforms.inDims[0] && col >=0 && col < uniforms.inDims[1])
        {
          value = getX(batch, row, col, channel);
        }
        return value;
      }
      ${C2()}
      fn main(@builtin(global_invocation_id) globalId: vec3<u32>) {
        let batch = i32(globalId.z) / uniforms.outShape[1];
        let r = i32(globalId.z) % uniforms.outShape[1];
        let c = i32(globalId.y) * 4;
        let d1 = i32(globalId.x) * 4;
        let xRCCorner = vec2<i32>(r, c) - uniforms.pad;

        let xRCorner = xRCCorner.x;
        let xCCorner = xRCCorner.y;
        var xVals : array<vec4<f32>, ${e}>;
        var dotProd : array<vec4<f32>, 4>;
        dotProd[0] = vec4<f32>(0.0);
        dotProd[1] = vec4<f32>(0.0);
        dotProd[2] = vec4<f32>(0.0);
        dotProd[3] = vec4<f32>(0.0);

        // Use constant instead of uniform can give better performance.
        for (var wR = 0; wR < ${this.convInfo.filterHeight}; wR = wR + 1) {
          let xR = xRCorner + wR;
          for (var i = 0; i < ${e}; i++)
          {
            xVals[i] = readX(batch, xR, xCCorner + i, d1);
          }
          for (var wC = 0; wC < ${this.convInfo.filterWidth}; wC = wC + 1) {
            let wValue = getW(wR, wC, d1, 0);
            dotProd[0] = dotProd[0] + xVals[0 + wC] * wValue;
            dotProd[1] = dotProd[1] + xVals[1 + wC] * wValue;
            dotProd[2] = dotProd[2] + xVals[2 + wC] * wValue;
            dotProd[3] = dotProd[3] + xVals[3 + wC] * wValue;
          }
        }

        for (var i = 0; i < 4; i = i + 1) {
          let coords = vec4<i32>(batch, r, c + i, d1);
          if (coordsInBounds4D(coords, uniforms.outShape)) {
            var value = dotProd[i];
            ${cd(this.addBias,this.activation)}
            setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
          }
        }
      }
    `}},rT=class{constructor(e,t=!1,n=null,s=!1){this.variableNames=["x","W"],this.uniforms=`pad : vec2<i32>, inDims : vec2<i32>, filterHeight : i32,
      filterWidth : i32, stride : vec2<i32>, dilation : vec2<i32>,`,this.workGroupSize=[256,1,1],this.outputShape=e.outShape,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",t&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=n,this.hasPreluActivation=s,this.shaderKey=`depthwise_${this.activation}_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?"getX(batch, xR, xC, d1);":"getX(batch, d1, xR, xC);";return`
      ${Sa(this.activation,this.hasPreluActivation,!1,4)}

      ${dd()}
        let coords = getOutputCoords();
        let batch = coords[0];
        let xRCCorner = vec2<i32>(coords.${this.isChannelsLast?"yz":"zw"}) * uniforms.stride - uniforms.pad;
        let d2 = coords[${this.isChannelsLast?3:1}];
        let channelMul = uniforms.wShape[3];
        let d1 = d2 / channelMul;
        let q = d2 % channelMul;

        let inputRowStart = xRCCorner.x;
        let inputColStart = xRCCorner.y;
        let inputRowEnd = inputRowStart + uniforms.filterHeight *
            uniforms.dilation[0];
        let inputColEnd = inputColStart + uniforms.filterWidth *
            uniforms.dilation[1];

        // Convolve x(?, ?, d1)|x(d1, ?, ?) with w(:, :, d1, q) to get
        // y(yR, yC, d2)|y(d2, yR, yC). ? = to be determined. : = across all
        // values in that axis. x(?, ?, d1) and y(yR, yC, d2) is for NHWC.
        // x(d1, ?, ?) and y(d2, yR, yC) is for NCHW.
        var value = 0.0;

        // Extract if checking out of for loop for performance.
        if (inputRowStart >= 0 && inputColStart >= 0 &&
          inputRowEnd < uniforms.inDims[0] &&
              inputColEnd < uniforms.inDims[1]) {
            for (var wR = 0; wR < uniforms.filterHeight; wR = wR + 1) {
              let xR = inputRowStart + wR * uniforms.dilation[0];

              for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) {
                let xC = inputColStart + wC * uniforms.dilation[1];

                let xVal = ${e};
                let wVal = getW(wR, wC, d1, q);
                value = value + xVal * wVal;
              }
            }
          } else {
            for (var wR = 0; wR < uniforms.filterHeight; wR = wR + 1) {
              let xR = inputRowStart + wR * uniforms.dilation[0];

              if (xR < 0 || xR >= uniforms.inDims[0]) {
                continue;
              }

              for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) {
                let xC = inputColStart + wC * uniforms.dilation[1];

                if (xC < 0 || xC >= uniforms.inDims[1]) {
                  continue;
                }

                let xVal = ${e};
                let wVal = getW(wR, wC, d1, q);
                value = value + xVal * wVal;
              }
            }
          }
          ${cd(this.addBias,this.activation)}
        if (coordsInBounds4D(coords, uniforms.outShape)) {
          setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
        }
      }
    `}};function G1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=s,p=C.convertConv2DDataFormat(l),d=u;d==null&&(d=[1,1]);let h=C.computeConv2DInfo(r.shape,a.shape,o,d,i,c,!0,p),f=[{type:"int32",data:[h.padInfo.top,h.padInfo.left]},{type:"int32",data:[h.inHeight,h.inWidth]}],m=h.dataFormat==="channelsLast",g;return!m&&h.inHeight>16&&h.inWidth>16&&h.strideHeight===1&&h.strideWidth===1&&h.dilationWidth===1&&h.dilationHeight===1&&h.inChannels===h.outChannels?g=new U1e(h.outShape,h.filterHeight,h.filterWidth):m&&h.inHeight>4&&h.inWidth>4&&h.strideHeight===1&&h.strideWidth===1&&h.inChannels===h.outChannels&&h.dilationHeight===1&&h.dilationWidth===1&&h.inChannels%4===0?g=new sT(h):(g=new rT(h),f.push({type:"int32",data:[h.filterHeight]},{type:"int32",data:[h.filterWidth]},{type:"int32",data:[h.strideHeight,h.strideWidth]},{type:"int32",data:[h.dilationHeight,h.dilationWidth]})),n.runWebGPUProgram(g,[r,a],r.dtype,f)}var H1e={kernelName:wo,backendName:"webgpu",kernelFunc:G1e},aT=os({opType:Ye.MUL,cpuKernelImpl:b2e,supportsComplex:!0}),j1e={kernelName:Bo,backendName:"webgpu",kernelFunc:aT},q1e=class{constructor(e,t){this.workGroupSize=[64,1,1],this.variableNames=["x"],this.uniforms="reduceSize : i32,",this.size=!0,this.inputShape=[e.batchSize,e.inSize];let[n]=C.computeOutAndReduceShapes(this.inputShape,[1]);this.outputShape=n.length===0?[1]:n,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,[1,1,1]),this.reduceType=t,this.shaderKey=`reduce_${t}`}getUserCode(){let e="",t="0.0";this.reduceType==="min"||this.reduceType==="max"?(e=`
         if (isnan(candidate)) {
          bestValue = uniforms.NAN;
         } else if (!isnan(bestValue) && candidate ${this.reduceType==="min"?"<":">"} bestValue)
           {  bestValue = candidate; }`,t="f32(x[offset])"):this.reduceType==="sum"||this.reduceType==="mean"?e=" bestValue = bestValue + candidate; ":this.reduceType==="prod"&&(e=" bestValue = bestValue * candidate; ",t="1.0");let n=this.reduceType==="mean"?"setOutputAtIndex(outputIndex, bestValue / f32(uniforms.reduceSize));":"setOutputAtIndex(outputIndex, bestValue);";return`
       fn DIV_CEIL(a : u32, b : u32) -> u32 {
        return ((a - 1u) / b + 1u);
       }

       ${`
         var<workgroup> xBestValues : array<f32, ${this.workGroupSize[0]}>;
       `}
       fn getOffset(outputIndex : i32) -> i32 {
         let outputCoords = getCoordsFromIndex(outputIndex);
         let offset = ${this.outputShape.length===1?"outputCoords":"outputCoords[0]"} * uniforms.reduceSize;
          return offset;
       }
       ${lt()}
         let outputIndex = index / i32(workGroupSizeX);
         let offset = getOffset(outputIndex);
         var bestValue = ${t};
         let Length = uniforms.reduceSize;
         let WorkPerThread = DIV_CEIL(u32(Length), workGroupSizeX);
         for (var k = i32(localId.x); k < Length && outputIndex < uniforms.size;
             k = k + i32(workGroupSizeX)) {
           let candidate = f32(x[offset + k]);
           ${e}
         }
         xBestValues[localId.x] = bestValue;
         workgroupBarrier();

         var reduceSize = min(u32(Length), workGroupSizeX);
         for (var currentSize = reduceSize / 2u; reduceSize > 1u;
             currentSize = reduceSize / 2u) {
           let interval = DIV_CEIL(reduceSize, 2u);
           if (localId.x < currentSize) {
            let candidate = xBestValues[localId.x + interval];
            ${e}
            xBestValues[localId.x] = bestValue;
           }
           reduceSize = interval;
           workgroupBarrier();
         }

         if (localId.x == 0u && outputIndex < uniforms.size) {
          ${n}
        }
       }
     `}};function Wh(e,t,n,s,r){let a=e.shape.length,o=[],i=v.parseAxisParam(t,e.shape),l=i,u=C.getAxesPermutation(l,a),c=e;u!=null&&(c=ya({inputs:{x:e},attrs:{perm:u},backend:r}),l=C.getInnerMostAxes(l.length,a),o.push(c)),C.assertAxesAreInnerMostDims(s,l,a);let[p,d]=C.computeOutAndReduceShapes(c.shape,l),h=p;n&&(h=C.expandShapeToKeepDim(p,i));let f;if((s==="max"||s==="prod")&&r.shouldExecuteOnCPU([c])){let m=r.tensorMap.get(c.dataId).values;switch(s){case"max":let g=y2e(m,v.sizeFromShape(d),h,e.dtype);f=r.makeTensorInfo(h,e.dtype,g);break;case"prod":let{outVals:y,outShape:x,outDtype:A}=k2e(c.shape,c.dtype,m,l);f=r.makeTensorInfo(x,A,y);break;default:throw new Error(`${s} CPU implementation is not yet supported.`)}}else{let m=v.sizeFromShape(d),y=v.sizeFromShape(c.shape)/m,x={windowSize:m,inSize:m,batchSize:y,outSize:1},A=s==="mean"?"float32":nh(e.dtype),b=[{type:"int32",data:[m]}],w=new q1e(x,s),k=r.runWebGPUProgram(w,[c],A,b);o.push(k),f=Ue({inputs:{x:k},attrs:{shape:h},backend:r})}return o.forEach(m=>r.disposeData(m.dataId)),f}function lb(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return Wh(r,a,o,"sum",n)}var X1e={kernelName:Qo,backendName:"webgpu",kernelFunc:lb};function K1e(e){let{inputs:t,backend:n,attrs:s}=e,{equation:r}=s,a=t,{allDims:o,summedDims:i,idDims:l}=C.decodeEinsumEquation(r,a.length);C.checkEinsumDimSizes(o.length,l,a);let{path:u,steps:c}=C.getEinsumComputePath(i,l),p=c.length,d=null,h=o.length,f=[];for(let m=0;m<p;++m){for(let g of c[m]){let{permutationIndices:y,expandDims:x}=C.getEinsumPermutation(h,l[g]),A;C.isIdentityPermutation(y)?A=a[g]:(A=ya({inputs:{x:a[g]},backend:n,attrs:{perm:y}}),f.push(A));let b=A.shape.slice();for(let w=0;w<x.length;++w)b.splice(x[w],0,1);v.arraysEqual(A.shape,b)||(A=Ue({inputs:{x:A},backend:n,attrs:{shape:b}}),f.push(A)),d===null?d=A:(d=aT({inputs:{a:A,b:d},backend:n}),f.push(d))}m<p-1&&(u[m]>=0&&(d=lb({inputs:{x:d},backend:n,attrs:{axis:u[m]-(o.length-h),keepDims:!1}}),f.push(d)),h--)}for(let m of f)m!==d&&n.disposeData(m.dataId);return d}var Z1e={kernelName:Vp,backendName:"webgpu",kernelFunc:K1e},Y1e=Dn({opType:Fe.ELU}),J1e={kernelName:Io,backendName:"webgpu",kernelFunc:Y1e},Q1e=os({opType:Ye.EQUAL,dtype:"bool",cpuKernelImpl:o2e}),ege={kernelName:pl,backendName:"webgpu",kernelFunc:Q1e},oT=Dn({opType:Fe.EXP,cpuKernelImpl:i2e,dtype:"float32"}),tge={kernelName:So,backendName:"webgpu",kernelFunc:oT};function gy(e){let{inputs:t,attrs:n,backend:s}=e,{dim:r}=n,{input:a}=t,o=a.shape.length,i=a.shape.slice(),l=r;return r<0&&(v.assert(-(o+1)<=r,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+r+1),i.splice(l,0,1),Ue({inputs:{x:a},backend:s,attrs:{shape:i}})}var nge={kernelName:hl,backendName:"webgpu",kernelFunc:gy},sge=Dn({opType:Fe.EXPM1,cpuKernelImpl:l2e}),rge={kernelName:fl,backendName:"webgpu",kernelFunc:sge},age=class{constructor(e){this.outputShape=[],this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="flipLeftRight"}getUserCode(){return`
      ${lt()}
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let coordX = uniforms.xShape[2] - coords[2] - 1;
          let outputValue = getX(coords[0], coords[1], coordX, coords[3]);
          setOutputAtIndex(index, outputValue);
        }
      }
    `}},oge={kernelName:ml,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,s=t,r=new age(n.shape);return s.runWebGPUProgram(r,[n],n.dtype)}},ige=Dn({opType:Fe.FLOOR,cpuKernelImpl:u2e}),lge={kernelName:Co,backendName:"webgpu",kernelFunc:ige},uge=os({opType:Ye.INT_DIV,dtype:"int32"}),cge={kernelName:To,backendName:"webgpu",kernelFunc:uge},dge=class{constructor(e,t,n=!1){this.isFromPixels=!0,this.outputShape=[0],this.variableNames=[],this.workGroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[t,1,1]),this.importVideo=n,this.shaderKey=`fromPixels_${this.importVideo}`}getUserCode(){let e=this.importVideo?"textureLoad(src, vec2<i32>(coords.yx));":"textureLoad(src, vec2<i32>(coords.yx), 0)";return`
      @binding(1) @group(0) var src: ${this.importVideo?"texture_external":"texture_2d<f32>"};
      ${lt()}
        let flatIndex = index * uniforms.numChannels;
        if (flatIndex < uniforms.size) {
          let coords = getCoordsFromIndex(flatIndex);
          let values = ${e};
          for (var i = 0; i < uniforms.numChannels; i = i + 1) {
            result[flatIndex + i] = i32(floor(255.0 * values[i]));
          }
        }
      }
  `}},pge={kernelName:xp,backendName:"webgpu",kernelFunc:hge},Fu,Yf=new Map;function hge(e){let{inputs:t,backend:n,attrs:s}=e,{pixels:r}=t,{numChannels:a}=s;if(r==null)throw new Error("pixels passed to tf.browser.fromPixels() can not be null");let o=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,i=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,l=typeof HTMLCanvasElement!="undefined"&&r instanceof HTMLCanvasElement||typeof OffscreenCanvas!="undefined"&&r instanceof OffscreenCanvas,u=typeof ImageBitmap!="undefined"&&r instanceof ImageBitmap,[c,p]=o?[r.videoWidth,r.videoHeight]:[r.width,r.height],d=[p,c,a],h=X().getBool("WEBGPU_IMPORT_EXTERNAL_TEXTURE")&&o,f=o||i;if(u||l||f){let x;if(h){let P=r;if(!Yf.has(P)||Yf.get(P).expired){let _={source:P};Yf.set(P,n.device.importExternalTexture(_))}x={width:c,height:p,format:null,usage:null,texture:Yf.get(P)}}else{f&&(Fu==null&&(Fu=document.createElement("canvas").getContext("2d")),Fu.canvas.width=c,Fu.canvas.height=p,Fu.drawImage(r,0,0,c,p),r=Fu.canvas);let P=GPUTextureUsage.COPY_DST|GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING,_="rgba8unorm",$=n.textureManager.acquireTexture(d[1],d[0],_,P);n.queue.copyExternalImageToTexture({source:r},{texture:$},[d[1],d[0]]),x={width:c,height:p,format:_,usage:P,texture:$}}let A=v.sizeFromShape(d),b=v.computeStrides(d),w=new dge(d,a,h),k=[{type:"uint32",data:[A]},{type:"uint32",data:[a]},{type:"uint32",data:[...b]}],S=n.makeTensorInfo([p,c],"int32"),E=n.tensorMap.get(S.dataId);E.resourceInfo=x;let R=n.runWebGPUProgram(w,[S],"int32",k);return n.disposeData(S.dataId),R}let m=r.data,g=m;if(a!=null&&a!==4){g=new Uint8Array(r.width*r.height*a);let x=m.length,A=0;for(let b=0;b<x;b++)b%4<a&&(g[A++]=m[b])}let y=n.makeTensorInfo(d,"int32",new Int32Array(g));return n.uploadToGPU(y.dataId),y}var fge=class{constructor(e,t,n,s,r){this.uniforms="varianceEpsilon : f32,",this.workGroupSize=[128,1,1],this.size=!0,this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,n),this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),s!=null&&(C.assertAndGetBroadcastShape(e,s),this.variableNames.push("offset")),r!=null&&(C.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale")),this.offsetShape=s,this.scaleShape=r,this.shaderKey="batchNorm"}getUserCode(){let e="0.0";this.offsetShape!=null&&(e="getOffsetByOutputIndex(index)");let t="1.0";return this.scaleShape!=null&&(t="getScaleByOutputIndex(index)"),`
      ${lt()}
        if (index < uniforms.size)
        {
          let xValue = getXByOutputIndex(index);
          let meanValue = getMeanByOutputIndex(index);
          let varianValue = getVarianceByOutputIndex(index);
          let offsetValue = ${e};
          let scaleValue = ${t};
          let inv = scaleValue * inverseSqrt(varianValue + f32(uniforms.varianceEpsilon));
          setOutputAtIndex(index,dot(vec3<f32>(xValue, -meanValue, offsetValue), vec3<f32>(inv, inv, 1.0)));
        }
      }
  `}},mge={kernelName:No,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s,scale:r,offset:a,mean:o,variance:i}=e,{varianceEpsilon:l}=t,u=n,c=[s,o,i],p=null;a!=null&&(p=a.shape,c.push(a));let d=null;r!=null&&(d=r.shape,c.push(r));let h=new fge(s.shape,o.shape,i.shape,p,d),f=[{type:"float32",data:[l]}];return u.runWebGPUProgram(h,c,s.dtype,f)}};function gge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=s,m=C.convertConv2DDataFormat(c),g=C.computeConv2DInfo(r.shape,a.shape,l,p,u,d,!1,m);return tT({x:r,filter:a,convInfo:g,backend:n,bias:o,preluActivationWeights:i,leakyreluAlpha:f,activation:h})}var yge={kernelName:Ja,backendName:"webgpu",kernelFunc:gge};function Age(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dimRoundingMode:p,activation:d,leakyreluAlpha:h}=s,f=c;f==null&&(f=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(l,f),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${f}'`);let m=C.computeConv2DInfo(r.shape,a.shape,l,f,u,p,!0),g=[r,a],y=o!=null,x=i!=null;y&&g.push(o),x&&g.push(i);let A=[{type:"int32",data:[m.padInfo.top,m.padInfo.left]},{type:"int32",data:[m.inHeight,m.inWidth]}],b;return m.inHeight>4&&m.inWidth>4&&m.strideHeight===1&&m.strideWidth===1&&m.inChannels===m.outChannels&&m.dilationHeight===1&&m.dilationWidth===1&&m.inChannels%4===0?b=new sT(m,y,d,x):(b=new rT(m,y,d,x),A.push({type:"int32",data:[m.filterHeight]},{type:"int32",data:[m.filterWidth]},{type:"int32",data:[m.strideHeight,m.strideWidth]},{type:"int32",data:[m.dilationHeight,m.dilationWidth]})),d==="leakyrelu"&&(A.push({type:"float32",data:[h]}),b.uniforms+=" alpha : f32,"),n.runWebGPUProgram(b,g,"float32",A)}var xge={kernelName:Qa,backendName:"webgpu",kernelFunc:Age},bge=class{constructor(e,t){this.variableNames=["A","indices"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`gathernd_${e}`,this.sliceDim=e,this.uniforms=`sliceDim : i32, strides : ${Tn(e)},`}getUserCode(){let e;return this.sliceDim>1?e="uniforms.strides[j]":e="uniforms.strides",`
        ${lt()}
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          var flattenIndex = 0;
          for (var j = 0; j < uniforms.sliceDim; j = j + 1) {
            let indexTemp = i32(round(getIndices(coords[0], j)));
            let strideNum = ${e};
            flattenIndex = flattenIndex + indexTemp * strideNum;
          }

          setOutputAtIndex(index, getA(flattenIndex, coords[1]));
        }
      }
      `}};function vge(e){let{inputs:t,backend:n}=e,{params:s,indices:r}=t,a=r.shape,o=a[a.length-1],i=v.sizeFromShape(s.shape),[l,u,c,p]=C.prepareAndValidate(s,r),d=Ue({inputs:{x:r},backend:n,attrs:{shape:[u,o]}}),h=Ue({inputs:{x:s},backend:n,attrs:{shape:[v.sizeFromShape(s.shape)/c,c]}});if(n.shouldExecuteOnCPU([s,r])||s.dtype==="string"){let x=n.readSync(r.dataId),A=n.bufferSync(s),b=c2e(x,A,s.dtype,u,o,c,p,s.shape,i);return n.makeTensorInfo(l,s.dtype,b.values)}let f=new bge(o,[u,c]),m=[{type:"int32",data:[o]},{type:"int32",data:p}],g=n.runWebGPUProgram(f,[h,d],h.dtype,m),y=Ue({inputs:{x:g},backend:n,attrs:{shape:l}});return n.disposeData(d.dataId),n.disposeData(h.dataId),n.disposeData(g.dataId),y}var wge={kernelName:yl,backendName:"webgpu",kernelFunc:vge},kge=class{constructor(e,t){this.variableNames=["A","indices"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e.slice(),this.aShape=e,this.outputShape=t,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="gather"}getUserCode(){let e=Ige(this.aShape);return`
      ${lt()}
        if (index < uniforms.size) {
          let resRC = getCoordsFromIndex(index);
          let indexZ = i32(getIndices(resRC.x, resRC.z));
          let inBounds = select(0.0, 1.0, indexZ >= 0 && indexZ < uniforms.aShape[2]);
          setOutputAtIndex(index, inBounds * getA(${e}));
        }
      }
    `}};function Ige(e){let t=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[];for(let s=0;s<e.length;s++)s===2?n.push("indexZ"):n.push(`${t[s]}`);return n.join()}function iT(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,indices:a}=t,{axis:o,batchDims:i}=s,l=v.parseAxisParam(o,r.shape)[0],u=C.segment_util.collectGatherOpShapeInfo(r,a,l,i),c=v.sizeFromShape(a.shape),p=[],d=Ue({inputs:{x:r},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=Ue({inputs:{x:a},backend:n,attrs:{shape:[u.batchSize,c/u.batchSize]}});p.push(d),p.push(h);let f=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([r,a])){let A=n.tensorMap.get(h.dataId).values,b=Le(h.shape,h.dtype,A),k=n.tensorMap.get(d.dataId).values,S=Le(d.shape,d.dtype,k),E=d2e(S,b,f);return p.forEach(R=>n.disposeData(R.dataId)),n.makeTensorInfo(u.outputShape,E.dtype,E.values)}let m=new kge(d.shape,f),g=n.runWebGPUProgram(m,[d,h],d.dtype);p.push(g);let y=Ue({inputs:{x:g},backend:n,attrs:{shape:u.outputShape}});return p.forEach(x=>n.disposeData(x.dataId)),y}var Sge={kernelName:gl,backendName:"webgpu",kernelFunc:iT},Cge=os({opType:Ye.GREATER,cpuKernelImpl:h2e,dtype:"bool"}),Tge={kernelName:Al,backendName:"webgpu",kernelFunc:Cge},Nge=os({opType:Ye.GREATER_EQUAL,dtype:"bool",cpuKernelImpl:p2e}),Ege={kernelName:Eo,backendName:"webgpu",kernelFunc:Nge};function Rge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{alpha:a}=s,o=[{type:"float32",data:[a]}],i=new Lh(r.shape,Fe.LEAKYRELU);return i.uniforms="alpha : f32,",n.runWebGPUProgram(i,[r],"float32",o)}var _ge={kernelName:_o,backendName:"webgpu",kernelFunc:Rge},Dge=os({opType:Ye.LESS,dtype:"bool",cpuKernelImpl:m2e}),$ge={kernelName:xl,backendName:"webgpu",kernelFunc:Dge},Pge=os({opType:Ye.LESS_EQUAL,dtype:"bool",cpuKernelImpl:f2e}),Fge={kernelName:bl,backendName:"webgpu",kernelFunc:Pge},Oge=Dn({opType:Fe.LOG,cpuKernelImpl:g2e}),Mge={kernelName:Do,backendName:"webgpu",kernelFunc:Oge},zge=os({opType:Ye.LOGICAL_AND,dtype:"bool"}),Lge={kernelName:vl,backendName:"webgpu",kernelFunc:zge},Bge=Dn({opType:Fe.LOGICAL_NOT}),Wge={kernelName:wl,backendName:"webgpu",kernelFunc:Bge};function lT(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reductionIndices:a,keepDims:o}=s;return Wh(r,a,o,"max",n)}var Vge={kernelName:$o,backendName:"webgpu",kernelFunc:lT},Uge=os({opType:Ye.MAX,cpuKernelImpl:A2e}),Gge={kernelName:Po,backendName:"webgpu",kernelFunc:Uge};function Hge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1,c=C.computePool2DInfo(r.shape,a,o,u,i,l),p,d=[];if(c.filterHeight===1&&c.filterWidth===1){if(v.arraysEqual(c.inShape,c.outShape))return Fs({inputs:{x:r},backend:n});p=new JC(c),d.push({type:"int32",data:[c.strideHeight,c.strideWidth]})}else p=new YC(c,"max"),d.push({type:"int32",data:[c.strideHeight,c.strideWidth]},{type:"int32",data:[c.padInfo.top,c.padInfo.left]},{type:"int32",data:[c.dilationHeight,c.dilationWidth]},{type:"int32",data:[c.inHeight,c.inWidth]},{type:"int32",data:[c.effectiveFilterHeight,c.effectiveFilterWidth]});return n.runWebGPUProgram(p,[r],r.dtype,d)}var jge={kernelName:Fo,backendName:"webgpu",kernelFunc:Hge};function qge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{keepDims:a,axis:o}=s;return Wh(r,o,a,"mean",n)}var Xge={kernelName:Oo,backendName:"webgpu",kernelFunc:qge};function Kge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return Wh(r,a,o,"min",n)}var Zge={kernelName:Mo,backendName:"webgpu",kernelFunc:Kge},Yge=os({opType:Ye.MIN,cpuKernelImpl:x2e}),Jge={kernelName:zo,backendName:"webgpu",kernelFunc:Yge},Qge=class{constructor(e,t,n){this.uniforms="",this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((s,r)=>s[0]+e[r]+s[1]),this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.xShape=e,t.map((s,r)=>{this.uniforms+=` pad${r} : vec2<i32>,`}),this.offset=n==="reflect"?0:1,this.shaderKey=`mirrorPad_${n}`}getUserCode(){let e=this.xShape.length,t=this.xShape.map((l,u)=>`uniforms.pad${u}[0]`).join(","),n=this.xShape.map((l,u)=>`uniforms.pad${u}[0] + uniforms.xShape${e>1?`[${u}]`:""}`).join(","),s=e===1?"start":"start[i]",r=e===1?"end":"end[i]",a=e===1?"outC":"outC[i]",o=Tn(e),i=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
      ${lt()}
        if (index < uniforms.size) {
          let start = ${o}(${t});
          let end = ${o}(${n});
          var outC = getCoordsFromIndex(index);
          for (var i = 0; i < ${e}; i = i + 1) {
            if (${a} < ${s}) {
              ${a} = ${s} * 2 - ${a} - ${this.offset};
            } else if(${a} >= ${r}) {
              ${a} = (${r} - 1) * 2 - ${a} + ${this.offset};
            }
          }
          let coords = outC - start;
          setOutputAtIndex(index, getX(${i}));
        }
      }
    `}},e3e={kernelName:Lo,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s}=e,{paddings:r,mode:a}=t,o=n,i=r.map(c=>({type:"int32",data:[c[0],c[1]]})),l=new Qge(s.shape,r,a);return o.runWebGPUProgram(l,[s],s.dtype,i)}};function t3e(e){let{inputs:t,backend:n}=e,{x:s}=t;if(n.shouldExecuteOnCPU([s])){let a=n.tensorMap.get(s.dataId),[o,i]=v2e(a.values,s.shape,s.dtype);return n.makeTensorInfo(i,s.dtype,o)}let r=new Lh(s.shape,Fe.NEG);return n.runWebGPUProgram(r,[s],s.dtype)}var n3e={kernelName:kl,backendName:"webgpu",kernelFunc:t3e};function s3e(e){console.warn("tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l}=s,u=n.readSync(r.dataId),c=n.readSync(a.dataId),{selectedIndices:p}=dr.nonMaxSuppressionV3Impl(u,c,o,i,l);return n.makeTensorInfo([p.length],"int32",new Int32Array(p))}var r3e={kernelName:Sl,backendName:"webgpu",kernelFunc:s3e};function a3e(e){console.warn("tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=s,c=n.readSync(r.dataId),p=n.readSync(a.dataId),d=o,h=i,f=l,m=u,{selectedIndices:g,selectedScores:y}=dr.nonMaxSuppressionV5Impl(c,p,d,h,f,m);return[n.makeTensorInfo([g.length],"int32",new Int32Array(g)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var o3e={kernelName:Cl,backendName:"webgpu",kernelFunc:a3e};function Lm(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="complex64"){let r=Bh({inputs:{input:s},backend:n}),a=Lm({inputs:{x:r},backend:n}),o=N2({inputs:{input:s},backend:n}),i=Lm({inputs:{x:o},backend:n}),l=pd({inputs:{real:a,imag:i},backend:n});return n.disposeData(r.dataId),n.disposeData(a.dataId),n.disposeData(o.dataId),n.disposeData(i.dataId),l}else return au({attrs:{shape:s.shape,dtype:s.dtype,value:s.dtype==="string"?"":0},backend:n})}var i3e={kernelName:Gl,backendName:"webgpu",kernelFunc:Lm};function uT(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(s.dtype==="complex64"){let r=Bh({inputs:{input:s},backend:n}),a=uT({inputs:{x:r},backend:n}),o=N2({inputs:{input:s},backend:n}),i=Lm({inputs:{x:o},backend:n}),l=pd({inputs:{real:a,imag:i},backend:n});return n.disposeData(r.dataId),n.disposeData(a.dataId),n.disposeData(o.dataId),n.disposeData(i.dataId),l}else return au({attrs:{shape:s.shape,dtype:s.dtype,value:1},backend:n})}var l3e={kernelName:Tl,backendName:"webgpu",kernelFunc:uT};function u3e(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return gy({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let p=gy({inputs:{input:c},backend:n,attrs:{dim:r}});return i.push(p),p}),u=eT({inputs:l,backend:n,attrs:{axis:r}});return i.forEach(c=>n.disposeData(c.dataId)),u}var c3e={kernelName:El,backendName:"webgpu",kernelFunc:u3e},d3e=class{constructor(e,t){this.variableNames=["x"],this.uniforms="constantValue : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((n,s)=>n[0]+e[s]+n[1]),this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),t.map((n,s)=>{this.uniforms+=` pad${s} : vec2<i32>,`}),this.xShape=e,this.shaderKey="pad"}getUserCode(){let e=this.xShape.length,t=Tn(e),n=this.xShape.map((c,p)=>`uniforms.pad${p}[0]`).join(","),s=this.xShape.map((c,p)=>`uniforms.pad${p}[0] + uniforms.xShape${e>1?`[${p}]`:""}`).join(","),r=e>1?`${t}(${n})`:`${n}`,a=e>1?`${t}(${s})`:`${s}`,o=e>1?"any(outC < start)":"outC < start",i=e>1?"any(outC >= end)":"outC >= end",l=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
      ${lt()}
        if (index < uniforms.size) {
          let start = ${r};
          let end = ${a};
          let outC = getCoordsFromIndex(index);

          if (${o} || ${i}) {
            setOutputAtIndex(index, uniforms.constantValue);
          } else {
            let coords = outC - start;
            setOutputAtIndex(index, getX(${l}));
          }
        }
      }
    `}},cT=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{paddings:a,constantValue:o}=s;if(a.every(u=>v.arraysEqual(u,[0,0])))return Fs({inputs:{x:r},backend:n});if(v.sizeFromShape(r.shape)===0){let u=a.map((c,p)=>c[0]+r.shape[p]+c[1]);return au({backend:n,attrs:{shape:u,value:o,dtype:r.dtype}})}let i=[{type:"float32",data:[o]}];a.map(u=>i.push({type:"int32",data:[u[0],u[1]]}));let l=new d3e(r.shape,a);return n.runWebGPUProgram(l,[r],r.dtype,i)},p3e={kernelName:Wo,backendName:"webgpu",kernelFunc:cT},h3e=os({opType:Ye.POW}),f3e={kernelName:Vo,backendName:"webgpu",kernelFunc:h3e};function m3e(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t,a=new hy(Ye.PRELU,s.shape,r.shape);return n.runWebGPUProgram(a,[s,r],"float32")}var g3e={kernelName:Uo,backendName:"webgpu",kernelFunc:m3e};function y3e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return Wh(r,a,o,"prod",n)}var A3e={kernelName:Go,backendName:"webgpu",kernelFunc:y3e},x3e=e=>{let{backend:t,attrs:n}=e,{start:s,stop:r,step:a,dtype:o}=n,i=I2e(s,r,a,o);return t.makeTensorInfo([i.length],o,i)},b3e={kernelName:Rc,backendName:"webgpu",kernelFunc:x3e},dT=os({opType:Ye.DIV}),v3e={kernelName:ko,backendName:"webgpu",kernelFunc:dT},w3e=Dn({opType:Fe.RELU}),k3e={kernelName:Ho,backendName:"webgpu",kernelFunc:w3e},I3e=Dn({opType:Fe.RELU6}),S3e={kernelName:Xo,backendName:"webgpu",kernelFunc:I3e},C3e=class{constructor(e,t,n){this.variableNames=["x"],this.uniforms="adjustHeightWidth : vec2<f32>, halfPixelCenters : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=[e[0],t,n,e[3]],this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="resizeBilinear"}getUserCode(){return`
      ${lt()}
        if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
          let b = coords[0];
          let d = coords[3];
          let rc = coords.yz;

          let effectiveInSize = vec2<f32>(
            f32(uniforms.xShape.y) - uniforms.adjustHeightWidth[0],
            f32(uniforms.xShape.z) - uniforms.adjustHeightWidth[1]);

          let effectiveOutSize = vec2<f32>(
            f32(uniforms.outShape.y) - uniforms.adjustHeightWidth[0],
            f32(uniforms.outShape.z) - uniforms.adjustHeightWidth[1]);

          let effectiveInputOverOutputRatioRC =
              effectiveInSize / effectiveOutSize;

          // Fractional source index
          let sourceFracIndexRC =
            (vec2<f32>(rc) + vec2<f32>(uniforms.halfPixelCenters)) *
            effectiveInputOverOutputRatioRC - vec2<f32>(uniforms.halfPixelCenters);

          // Compute the four integer indices.
          let sourceFloorRC = vec2<i32>(sourceFracIndexRC);
          let sourceCeilRC = vec2<i32>(
            min(vec2<f32>(uniforms.xShape.yz) - vec2<f32>(1.0), ceil(sourceFracIndexRC)));

          let topLeft = getX(b, sourceFloorRC.x, sourceFloorRC.y, d);
          let bottomLeft = getX(b, sourceCeilRC.x, sourceFloorRC.y, d);
          let topRight = getX(b, sourceFloorRC.x, sourceCeilRC.y, d);
          let bottomRight = getX(b, sourceCeilRC.x, sourceCeilRC.y, d);

          let fracRC = sourceFracIndexRC - vec2<f32>(sourceFloorRC);

          let top = topLeft + (topRight - topLeft) * fracRC.y;
          let bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;
          let newValue = top + (bottom - top) * fracRC.x;

          setOutputAtIndex(index, newValue);
        }
      }
    `}};function T3e(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,size:o,halfPixelCenters:i}=s,[l,u]=o,c=a&&l>1?1:0,p=a&&u>1?1:0,h=[{type:"float32",data:[c,p]},{type:"float32",data:[i?.5:0]}],f=new C3e(r.shape,l,u);return n.runWebGPUProgram(f,[r],"float32",h)}var N3e={kernelName:qo,backendName:"webgpu",kernelFunc:T3e},E3e=class{constructor(e,t,n,s){this.variableNames=["x"],this.uniforms="adjustHeightWidth : vec2<f32>, roundBase : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=[e[0],t,n,e[3]],this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.halfPixelCenters=s,this.shaderKey=`resizeNearest_${s}`}getUserCode(){let e;return this.halfPixelCenters?e="max((vec2<f32>(rc) + vec2<f32>(0.5)) * effectiveInputOverOutputRatioRC, vec2<f32>(0.0))":e="vec2<f32>(rc) * effectiveInputOverOutputRatioRC",`
      ${lt()}
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let b = coords[0];
          let d = coords[3];
          let rc = coords.yz;

          let effectiveInSize = vec2<f32>(
            f32(uniforms.xShape.y) - uniforms.adjustHeightWidth[0],
            f32(uniforms.xShape.z) - uniforms.adjustHeightWidth[1]);

          let effectiveOutSize = vec2<f32>(
            f32(uniforms.outShape.y) - uniforms.adjustHeightWidth[0],
            f32(uniforms.outShape.z) - uniforms.adjustHeightWidth[1]);

          let effectiveInputOverOutputRatioRC =
              effectiveInSize / effectiveOutSize;

          // Fractional source index
          let sourceFracIndexRC = ${e};

          // Compute the coordinators of nearest neighbor point.
          let inputShapeRC = vec2<f32>(f32(uniforms.xShape.y), f32(uniforms.xShape.z));
          let sourceNearestRC = vec2<i32>(
            min(inputShapeRC - 1.0, floor(sourceFracIndexRC + uniforms.roundBase)));
          let newValue = getX(b, sourceNearestRC.x, sourceNearestRC.y, d);

          setOutputAtIndex(index, newValue);
        }
      }
    `}};function R3e(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,c=a&&l>1?1:0,p=a&&u>1?1:0,h=[{type:"float32",data:[c,p]},{type:"float32",data:[a?.5:0]}],f=new E3e(r.shape,l,u,o);return n.runWebGPUProgram(f,[r],r.dtype,h)}var _3e={kernelName:jo,backendName:"webgpu",kernelFunc:R3e},D3e=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.uniforms=`centerX : f32, centerY : f32, sinRadians : f32,
          cosRadians : f32,`,this.shaderKey="rotate",this.outputShape=e,typeof t=="number"?(this.uniforms+=" fillValue : f32,",this.fillSnippet="var outputValue = uniforms.fillValue;",this.shaderKey+="_float"):(this.uniforms+=" fillValue : vec3<f32>,",this.fillSnippet="var outputValue = uniforms.fillValue[coords[3]];",this.shaderKey+="_vec3")}getUserCode(){return`
        ${lt()}

          if (index < uniforms.size) {
            let coords = getCoordsFromIndex(index);
            let coordXFloat = (f32(coords[2]) - uniforms.centerX) *
                uniforms.cosRadians - (f32(coords[1]) - uniforms.centerY) *
                uniforms.sinRadians;
            let coordYFloat = (f32(coords[2]) - uniforms.centerX) *
                uniforms.sinRadians + (f32(coords[1]) - uniforms.centerY) *
                uniforms.cosRadians;
            let coordX = i32(round(coordXFloat + uniforms.centerX));
            let coordY = i32(round(coordYFloat + uniforms.centerY));
            ${this.fillSnippet}
            if(coordX >= 0 && coordX < uniforms.xShape[2] && coordY >= 0 &&
                coordY < uniforms.xShape[1]) {
              outputValue = getX(coords[0], coordY, coordX, coords[3]);
            }
            setOutputAtIndex(index, outputValue);
          }
        }
      `}},$3e={kernelName:Hl,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:s}=e,{radians:r,fillValue:a,center:o}=t,i=n,l=new D3e(s.shape,a),[u,c]=C.getImageCenter(o,s.shape[1],s.shape[2]),p=[{type:"float32",data:[u]},{type:"float32",data:[c]},{type:"float32",data:[Math.sin(r)]},{type:"float32",data:[Math.cos(r)]}];return typeof a=="number"?p.push({type:"float32",data:[Number.parseFloat(a.toFixed(2))]}):p.push({type:"float32",data:a}),i.runWebGPUProgram(l,[s],s.dtype,p)}},P3e=Dn({opType:Fe.RSQRT,cpuKernelImpl:S2e}),F3e={kernelName:Ko,backendName:"webgpu",kernelFunc:P3e},im=class{constructor(e,t,n,s,r,a,o,i=!0){this.variableNames=["updates","indices"],this.workGroupSize=[64,1,1],this.atomic=!0,this.outputShape=a,this.type=o,this.sumDupeIndices=i,this.dispatchLayout=at(e),this.dispatch=We(this.dispatchLayout,e,this.workGroupSize),this.sliceDimGreaterThanOne=t>1,this.shaderKey=`scatter_${n}_${s}_${this.sliceDimGreaterThanOne}_${o}_${i}`;let l=Tn(r.length);this.uniforms=`sliceDim : i32, strides: ${l}, size: i32,`,this.updatesRank=s,this.indicesRank=n}getUserCode(){let e="";this.indicesRank===1?e="coords[0]":this.indicesRank===2&&(e="coords[0], j");let t=`getIndices(${e})`,n=this.sliceDimGreaterThanOne?"uniforms.strides[j]":"uniforms.strides",s="",r="";this.dispatchLayout.x.length===1?(s="flattenedIndex",r=`
      fn getUpdatesCoordsFromFlatIndex(index : i32) -> i32 {
        return index;
      }
      `):this.dispatchLayout.x.length===2&&(s="vec2<i32>(flattenedIndex, coords[1])",r=`
      fn getUpdatesCoordsFromFlatIndex(index : i32) -> vec2<i32> {
        // N.B. |updates| could be a scalar tensor, conceptually representing a
        // 2D tensor with all values equal to that. By design, its size must be
        // the same as |outShape[1]| in one dimension, and |indicesShape[0]|
        // gives the other.
        let sliceSize = uniforms.outShape[1];
        let d0 = index / sliceSize;
        let d1 = index - d0 * sliceSize;
        return vec2<i32>(d0, d1);
      }
      `);let o=`getUpdates(${Array.from({length:this.updatesRank},(u,c)=>`coords[${c}]`).join(", ")})`,i=(u,c)=>{let p=`atomicAdd(${u}, bitcast<i32>(${c}))`;this.type==="float32"&&(p=`
          {
            var oldBits = 0;
            var newBits = bitcast<i32>(${c});
            loop {
              let info = atomicCompareExchangeWeak(${u}, oldBits, newBits);
              if (info.exchanged) {
                break;
              }
              oldBits = info.old_value;
              let oldValue = bitcast<f32>(oldBits);
              let newValue = oldValue + (${c});
              newBits = bitcast<i32>(newValue);
            }
          }
        `);let d=`atomicStore(${u}, bitcast<i32>(${c}));`;return this.sumDupeIndices?p:d};return`
    ${r}

      ${lt()}

        if (index < uniforms.size) {
          let coords = getUpdatesCoordsFromFlatIndex(index);
          var flattenedIndex = 0;
          for (var j = 0; j < uniforms.sliceDim; j = j + 1) {
            let indexInside = i32(round(${t}));
            flattenedIndex = flattenedIndex + indexInside * ${n};
          }
          let updateValue =
              ${yp(this.type,!1)}(${o});
          let flatIndex = getOutputIndexFromCoords(${s});

          ${i("&result[flatIndex]","updateValue")};
        }
      }`}};function O3e(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r,updates:a}=t,{shape:o}=s,{sliceRank:i,numUpdates:l,sliceSize:u,strides:c,outputSize:p}=C.calculateShapes(a,r,o),d=[p/u,u];if(p===0)return n.makeTensorInfo(o,r.dtype);let h=Ue({inputs:{x:r},backend:n,attrs:{shape:[l,i]}}),f=Ue({inputs:{x:a},backend:n,attrs:{shape:[l,u]}}),m=f.dtype,g=au({backend:n,attrs:{shape:d,value:0,dtype:m}}),y=v.sizeFromShape(f.shape),x=[{type:"int32",data:[i]},{type:"int32",data:c},{type:"int32",data:[y]}],A=new im(f.shape,i,h.shape.length,f.shape.length,c,d,m),b=n.runWebGPUProgram(A,[f,h],m,x,g),w=Ue({inputs:{x:b},backend:n,attrs:{shape:o}});return n.disposeData(h.dataId),n.disposeData(f.dataId),n.disposeData(b.dataId),w}var M3e={kernelName:$l,backendName:"webgpu",kernelFunc:O3e},z3e=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.cRank=e,this.rank=n,this.shaderKey="select"}getUserCode(){let e,t;if(this.rank>4)throw Error(`Where for rank ${this.rank} is not yet supported`);if(this.rank===1)t="resRC",e="resRC";else{let s=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[],a=[];for(let o=0;o<this.outputShape.length;o++)a.push(`${s[o]}`),o<this.cRank&&r.push(`${s[o]}`);e=r.join(),t=a.join()}return`
      ${lt()}
        if (index < uniforms.size) {
          let resRC = getCoordsFromIndex(index);
          let cVal = getC(${e});
          if (cVal >= 1.0) {
            setOutputAtIndex(index, getA(${t}));
          } else {
            setOutputAtIndex(index, getB(${t}));
          }
        }
      }
    `}};function L3e(e){let{inputs:t,backend:n}=e,{condition:s,t:r,e:a}=t,o=new z3e(s.shape.length,r.shape,r.shape.length);return n.runWebGPUProgram(o,[s,r,a],On(r.dtype,a.dtype))}var B3e={kernelName:Pl,backendName:"webgpu",kernelFunc:L3e},W3e=Dn({opType:Fe.SIGMOID}),V3e={kernelName:Yo,backendName:"webgpu",kernelFunc:W3e},U3e=Dn({opType:Fe.SIN}),G3e={kernelName:Zo,backendName:"webgpu",kernelFunc:U3e},H3e=Dn({opType:Fe.SINH}),j3e={kernelName:Ol,backendName:"webgpu",kernelFunc:H3e},pT=os({opType:Ye.SUB,cpuKernelImpl:_2e,supportsComplex:!0}),q3e={kernelName:ni,backendName:"webgpu",kernelFunc:pT};function X3e(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{dim:a}=s,o=v.parseAxisParam([a],r.shape),i=lT({inputs:{x:r},backend:n,attrs:{reductionIndices:o,keepDims:!1}}),l=C.expandShapeToKeepDim(i.shape,o),u=Ue({inputs:{x:i},backend:n,attrs:{shape:l}}),c=pT({inputs:{a:r,b:u},backend:n}),p=oT({inputs:{x:c},backend:n}),d=lb({inputs:{x:p},backend:n,attrs:{axis:o,keepDims:!1}}),h=Ue({inputs:{x:d},backend:n,attrs:{shape:l}}),f=dT({inputs:{a:p,b:h},backend:n});return n.disposeData(i.dataId),n.disposeData(u.dataId),n.disposeData(c.dataId),n.disposeData(p.dataId),n.disposeData(d.dataId),n.disposeData(h.dataId),f}var K3e={kernelName:ei,backendName:"webgpu",kernelFunc:X3e},Z3e=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,paddings:o}=s;v.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGPU backend not implemented yet");let i=a.reduce((y,x)=>y*x),l=[[0,0]];l.push(...o);for(let y=1+a.length;y<r.shape.length;++y)l.push([0,0]);let u=[],c=cT({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),p=C.getReshaped(c.shape,a,i,!1),d=C.getPermuted(p.length,a.length,!1),h=C.getReshapedPermuted(c.shape,a,i,!1),f=Ue({inputs:{x:c},backend:n,attrs:{shape:p}}),m=ya({inputs:{x:f},backend:n,attrs:{perm:d}}),g=Ue({inputs:{x:m},backend:n,attrs:{shape:h}});return u.push(c),u.push(f),u.push(m),u.forEach(y=>n.disposeData(y.dataId)),g},Y3e={kernelName:Ml,backendName:"webgpu",kernelFunc:Z3e},J3e=class{constructor(e,t){this.variableNames=["A"],this.workGroupSize=[64,1,1],this.size=!0;let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[s]*t[s];this.outputShape=n,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.rank=this.outputShape.length,this.shaderKey="tile"}getUserCode(){let e=Q3e(this.rank,"uniforms.");return`
      ${lt()}
        if (index < uniforms.size) {
          let resRC = getCoordsFromIndex(index);
          setOutputAtIndex(index, getA(${e}));
        }
      }
    `}};function Q3e(e,t=""){if(e>=5)throw Error(`Tile for rank ${e} is not yet supported`);if(e===1)return`(resRC % ${t}aShape)`;let n=["resRC.x","resRC.y","resRC.z","resRC.w"],s=[];for(let r=0;r<e;r++)s.push(`(${n[r]} % ${t}aShape[${r}])`);return s.join()}function hT(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reps:a}=s;if(n.shouldExecuteOnCPU([r])||r.dtype==="string"||r.shape.length>=5){let l=n.readSync(r.dataId),u=r.dtype==="string"?l.map(d=>v.decodeString(d)):l,c=Le(r.shape,r.dtype,u),p=D2e(c,a);return n.makeTensorInfo(p.shape,p.dtype,p.values)}let o=new J3e(r.shape,a);return n.runWebGPUProgram(o,[r],r.dtype)}var eye={kernelName:ba,backendName:"webgpu",kernelFunc:hT};function tye(e){let{inputs:t,backend:n,attrs:s}=e,{sparseIndices:r,sparseValues:a,defaultValue:o}=t,{outputShape:i}=s,{sliceRank:l,numUpdates:u,sliceSize:c,strides:p,outputSize:d}=C.calculateShapes(a,r,i),h=!1;if(a.dtype==="string"){let E=n.bufferSync(r),R=n.bufferSync(a),P=v.decodeString(n.readSync(o.dataId)[0]),_=C2e(E,R,i,d,c,u,l,p,P,h);return n.makeTensorInfo(i,_.dtype,_.values)}let f=[d/c,c],m=Ue({inputs:{x:r},backend:n,attrs:{shape:[u,l]}}),g=a.shape.length?Ue({inputs:{x:a},backend:n,attrs:{shape:[u,c]}}):Fs({inputs:{x:a},backend:n}),y=g.dtype,x=n.makeTensorInfo([],y,v.makeZerosTypedArray(1,y)),A=Ue({inputs:{x:o},backend:n,attrs:{shape:Array(f.length).fill(1)}}),b=hT({inputs:{x:A},backend:n,attrs:{reps:f}}),w=v.sizeFromShape([u,c]),k=[{type:"int32",data:[l]},{type:"int32",data:p},{type:"int32",data:[w]}];switch(u){case 0:break;case 1:{let E=new im([u,c],l,m.shape.length,g.shape.length,p,f,y,h);n.runWebGPUProgram(E,[g,m],y,k,b)}break;default:{let E=new im([u,c],l,m.shape.length,x.shape.length,p,f,y,h);n.runWebGPUProgram(E,[x,m],y,k,b)}{let E=new im([u,c],l,m.shape.length,g.shape.length,p,f,y);n.runWebGPUProgram(E,[g,m],y,k,b)}}let S=Ue({inputs:{x:b},backend:n,attrs:{shape:i}});return n.disposeData(m.dataId),n.disposeData(g.dataId),n.disposeData(A.dataId),n.disposeData(x.dataId),n.disposeData(b.dataId),S}var nye={kernelName:Zp,backendName:"webgpu",kernelFunc:tye};function sye(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{numOrSizeSplits:a,axis:o}=s,i=v.parseAxisParam(o,r.shape)[0],l=C.prepareSplitSize(r,a,i),u=r.shape.length,c=new Array(u).fill(0),p=r.shape.slice();return l.map(d=>{let h=[...p];h[i]=d;let f=hd({inputs:{x:r},backend:n,attrs:{begin:c,size:h}});return c[i]+=d,f})}var rye={kernelName:zl,backendName:"webgpu",kernelFunc:sye},aye=Dn({opType:Fe.SQRT}),oye={kernelName:Jo,backendName:"webgpu",kernelFunc:aye},iye={kernelName:Oc,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{x:n}=e,s=t,r=new Lh(n.shape,Fe.SQUARE);return s.runWebGPUProgram(r,[n],n.dtype)}},lye=os({opType:Ye.SQUARED_DIFFERENCE}),uye={kernelName:ti,backendName:"webgpu",kernelFunc:lye},cye=class{constructor(e){this.variableNames=["x"],this.workPerThread=1,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]);let t=Tn(this.outputShape.length);this.uniforms=`begin : ${t},  strides : ${t}, `,this.shaderKey="stridedSlice"}getUserCode(){let e=this.outputShape.length,t="";if(e===1)t="coords * uniforms.strides + uniforms.begin";else{let s=0;t=this.outputShape.map((r,a)=>(s++,this.outputShape.length===1?`coords * uniforms.strides[${a}] + uniforms.begin[${a}]`:`coords[${s-1}] * uniforms.strides[${a}] + uniforms.begin[${a}]`)).join(",")}return`
       ${lt()}
         if (index < uniforms.size) {
           let coords = getCoordsFromIndex(index);
           setOutputAtIndex(index, getX(${t}));
         }
       }
     `}};function dye(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,end:o,strides:i,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:p,shrinkAxisMask:d}=s,{finalShapeSparse:h,finalShape:f,isIdentity:m,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Ut.sliceInfo(r.shape,a,o,i,l,u,c,p,d),w;if(m)w=Ue({inputs:{x:r},backend:n,attrs:{shape:f}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let k=Ut.computeOutShape(x,A,b),S=hd({inputs:{x:r},backend:n,attrs:{begin:x,size:k}});w=Ue({inputs:{x:S},backend:n,attrs:{shape:f}}),n.disposeData(S.dataId)}else if(n.shouldExecuteOnCPU([r])){let S=n.readSync(r.dataId),E=Le(r.shape,r.dtype,S),R=E2e(h,E,b,x);w=n.makeTensorInfo(f,r.dtype,R.values)}else{let S=new cye(h),E=[{type:"int32",data:x},{type:"int32",data:b}],R=n.runWebGPUProgram(S,[r],r.dtype,E);w=Ue({inputs:{x:R},backend:n,attrs:{shape:f}}),n.disposeData(R.dataId)}return w}var pye={kernelName:Ll,backendName:"webgpu",kernelFunc:dye};function hye(e){let{inputs:t,backend:n,attrs:s}=e,{separator:r,nGramWidths:a,leftPad:o,rightPad:i,padWidth:l,preserveShortSequences:u}=s,{data:c,dataSplits:p}=t,d=n.readSync(c.dataId),h=n.readSync(p.dataId),[f,m]=R2e(d,h,r,a,o,i,l,u);return[n.makeTensorInfo([f.length],"string",f),n.makeTensorInfo(p.shape,"int32",m)]}var fye={kernelName:Mc,backendName:"webgpu",kernelFunc:hye},mye=Dn({opType:Fe.TANH}),gye={kernelName:si,backendName:"webgpu",kernelFunc:mye},yye=class{constructor(e){this.variableNames=["x","indices"],this.workGroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.uniforms=`inputSize : i32, firstPass : i32, negativeInf : f32,
        dir : i32, inc : i32,`,this.shaderKey="swap"}getUserCode(){return`
        ${lt()}
          if (index < uniforms.size) {
            let outC = getCoordsFromIndex(index);
            let batch = outC[0];
            let elemIdx = outC[1];
            // We compare elements pair-wise within a group of size 2 * inc.
            // The comparing rule for each group alternates between ascending
            // and descending. Within each group, we compare each pair at
            // positions i and i+inc. To decide whether an element at position i
            // is x0 or x1, we mod it by 2 * inc, if the result is smaller than
            // inc, it is in the first half of the group, we denote it as x0,
            // otherwise we denote it as x1.
            // For example, as shown in the Bitonic top K paper referenced
            // above, Figure5(a) shows that element[1] is in the second half of
            // the group when group size is 2, but it is in the first half of
            // the group when group size is 4.
            let isFirstInPair = elemIdx % (2 * uniforms.inc) < uniforms.inc;
            var i = 0;
            if (isFirstInPair) {
              i = elemIdx;
            } else {
              i = elemIdx - uniforms.inc;
            }

            var i0 = 0;
            if (uniforms.firstPass == 1) {
              i0 = i;
            } else {
              i0 = i32(getIndices(batch, i));
            }

            var i1 = 0;
            if (uniforms.firstPass == 1) {
              i1 = i + uniforms.inc;
            } else {
              i1 = i32(getIndices(batch, i + uniforms.inc));
            }

            var x0 = f32(0.0);
            var x1 = f32(0.0);
            if (i0 < uniforms.inputSize) {
              x0 = getX(batch, i0);
            } else {
              x0 = uniforms.negativeInf;
            }
            if (i1 < uniforms.inputSize) {
              x1 = getX(batch, i1);
            } else {
              x1 = uniforms.negativeInf;
            }

            let reverse = elemIdx % (2 * uniforms.dir) >= uniforms.dir;
            let isGreater = x0 > x1 || (x0 == x1 && i1 > i0);
            if (reverse == isGreater) {
              // Elements in opposite order of direction
              let iTemp = i0;
              i0 = i1;
              i1 = iTemp;
            }
            if (isFirstInPair) {
              setOutputAtIndex(index, f32(i0));
            } else {
              setOutputAtIndex(index, f32(i1));
            }
          }
        }
      `}},Aye=class{constructor(e){this.variableNames=["x","indices"],this.workGroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.uniforms="inputSize : i32, firstPass : i32, k : i32,",this.shaderKey="merge"}getUserCode(){return`
        ${lt()}
          if (index < uniforms.size) {
            let outC = getCoordsFromIndex(index);
            let batch = outC[0];
            let elemIdx = outC[1];
            // The output size is half of the previous size.
            // If the previous sequence is | | | | _ _ _ _  | | | |  _ _ _ _
            // (k=4), we only need to output the indices at positions |, the
            // indices at positions _ can be thrown away, see Figure5(b) After
            // Phase 2 (Merge phase) in the Bitonic Top K paper referenced
            // above.
            // For example, the paper shows we only need to output the orange
            // bars. The output sequence should look like this | | | | | | | |.
            // Because the sequence is halved, to map the output index back to
            // the previous sequence to find the corresponding value, we need
            // to double the index. When we double the index, we basically
            // interpolate a position, so 2i looks like
            // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k
            // position of each 2k positions by - elemIdx % k. E.g. for output
            // at index 4,5,6,7, we want to get the corresponding element at
            // original index 8,9,10,11, for output at index 8,9,10,11,
            // we want to get the corresponding element at original index
            // 16,17,18,19, so on and so forth.

            var i = 0;
            if (elemIdx < uniforms.k) {
              i = elemIdx;
            } else {
              i = elemIdx * 2 - elemIdx % uniforms.k;
            }
            var i0 = 0;
            if (uniforms.firstPass == 1) {
              i0 = i;
            } else {
              i0 = i32(getIndices(batch, i));
            }
            var i1 = 0;
            if (uniforms.firstPass == 1) {
              i1 = i + uniforms.k;
            } else {
              i1 = i32(getIndices(batch, i + uniforms.k));
            }

            let x0 = getX(batch, i0);
            var x1 = f32(0.0);
            if (i1 < uniforms.inputSize) {
              x1 = getX(batch, i1);
            } else {
              x1 = x0;
            }

            if (x0 >= x1) {
              setOutputAtIndex(index, f32(i0));
            } else {
              setOutputAtIndex(index, f32(i1));
            }
          }
        }
      `}};function Ou(e,t){t!==null&&e.disposeData(t.dataId)}function j7(e){let t=1;for(;t<e;)t*=2;return t}function xye(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{k:a,sorted:o}=s,i=r.shape,l=i[i.length-1];if(n.shouldExecuteOnCPU([r])){let w=n.readSync(r.dataId),[k,S]=$2e(w,i,r.dtype,a,o);return[n.makeTensorInfo(k.shape,k.dtype,k.values),n.makeTensorInfo(S.shape,S.dtype,S.values)]}if(a===0)return i[i.length-1]=0,[n.makeTensorInfo(i,r.dtype,[]),n.makeTensorInfo(i,"int32",[])];if(l===1)return[r,au({attrs:{shape:i,dtype:"int32",value:0},backend:n})];let c=v.sizeFromShape(i)/l,p=Ue({inputs:{x:r},attrs:{shape:[c,l]},backend:n}),d=j7(a),h=j7(l),f=null,m=()=>f===null?[p,p]:[p,f],g=(w,k,S)=>{let E=m(),R=new yye(S),_=[{type:"int32",data:[l]},{type:"int32",data:[f===null?1:0]},{type:"float32",data:[Number.NEGATIVE_INFINITY]},{type:"int32",data:[w]},{type:"int32",data:[k]}],$=f;f=n.runWebGPUProgram(R,E,"int32",_),Ou(n,$)};for(let w=1;w<d;w*=2){let k=w*2;for(let S=w;S>=1;S/=2)g(k,S,[c,h])}for(let w=h;w>d;w/=2){let k=m(),S=new Aye([c,w/2]),R=[{type:"int32",data:[l]},{type:"int32",data:[f===null?1:0]},{type:"int32",data:[d]}],P=f;f=n.runWebGPUProgram(S,k,"int32",R),Ou(n,P);let _=d/2,$=_*2;for(let T=_;T>=1;T/=2)g($,T,f.shape)}let y=f;f=hd({inputs:{x:f},backend:n,attrs:{begin:0,size:[c,a]}}),Ou(n,y);let x=iT({inputs:{x:p,indices:f},backend:n,attrs:{axis:1,batchDims:1}});Ou(n,p);let A=i.slice(0,-1);A.push(a),y=f,f=Ue({inputs:{x:f},attrs:{shape:A},backend:n}),Ou(n,y);let b=x;return x=Ue({inputs:{x},attrs:{shape:A},backend:n}),Ou(n,b),[x,f]}var bye={kernelName:Wl,backendName:"webgpu",kernelFunc:xye},vye=class{constructor(e){this.variableNames=["Image","Transforms"],this.uniforms="interpolationModeId : i32, fillModeId : i32, fillValue : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="transform"}getUserCode(){return`
          fn mapCoord(outCoord : f32, len : f32) -> f32{
            var inCoord = outCoord;
            if(uniforms.fillModeId == 2) {
              if (inCoord < 0.0) {
                if (len <= 1.0) {
                  inCoord = 0.0;
                } else {
                  let sz2 = 2.0 * len;
                  if (inCoord < sz2) {
                    inCoord = sz2 * f32(i32(f32(-inCoord / sz2))) +
                    inCoord;
                  }
                  if (inCoord < -len) {
                    inCoord = inCoord + sz2;
                  } else {
                    inCoord = -inCoord - 1.0;
                  }
                }
              } else if (inCoord > len - 1.0) {
                if (len <= 1.0) {
                  inCoord = 0.0;
                } else {
                  let sz2 = 2.0 * len;
                  inCoord = inCoord - sz2 * f32(i32(f32(inCoord / sz2)));
                  if (inCoord >= len) {
                    inCoord = sz2 - inCoord - 1.0;
                  }
                }
              }
              return clamp(inCoord, 0.0, len - 1.0);
            } else if (uniforms.fillModeId == 3) {
              if (inCoord < 0.0) {
                if (len <= 1.0) {
                  inCoord = 0.0;
                } else {
                  let sz = len - 1.0;
                  inCoord = inCoord + len * (f32(i32(f32(-inCoord / sz))) + 1.0);
                }
              } else if (inCoord > len - 1.0) {
                if (len <= 1.0) {
                  inCoord = 0.0;
                } else {
                  let sz = len - 1.0;
                  inCoord = inCoord - len * f32(i32(f32(inCoord / sz)));
                }
              }
              return clamp(inCoord, 0.0, len - 1.0);
            } else if (uniforms.fillModeId == 4) {
              return clamp(outCoord, 0.0, len - 1.0);
            }
            return outCoord;
          }
          fn readWithFillValue(batch : i32, coordY : i32, coordX : i32,
            channel : i32) -> f32 {
            var outputValue : f32;
            if (0 <= coordY && coordY < uniforms.imageShape[1] && 0 <= coordX && coordX < uniforms.imageShape[2]) {
                outputValue = getImage(batch, coordY, coordX, channel);
            } else {
              outputValue = uniforms.fillValue;
            }
            return outputValue;
          }

          ${lt()}
            if (index < uniforms.size) {
              let coords = getCoordsFromIndex(index);
              var outputValue : f32;
              let batch = coords[0];
              let x = coords[2];
              let y = coords[1];
              let channel = coords[3];
              let xf = f32(x);
              let yf = f32(y);
              let a1 = getTransforms(batch, 0);
              let a2 = getTransforms(batch, 1);
              let a3 = getTransforms(batch, 2);
              let b1 = getTransforms(batch, 3);
              let b2 = getTransforms(batch, 4);
              let b3 = getTransforms(batch, 5);
              let c1 = getTransforms(batch, 6);
              let c2 = getTransforms(batch, 7);
              let projection = c1 * xf + c2 * yf + 1.0;
              if (projection == 0.0) {
                outputValue = uniforms.fillValue;
              } else {
                let inX = (a1 * xf + a2 * yf + a3) / projection;
                let inY = (b1 * xf + b2 * yf + b3) / projection;
                let mapX = mapCoord(inX, f32(uniforms.imageShape[2]));
                let mapY = mapCoord(inY, f32(uniforms.imageShape[1]));

                if (uniforms.interpolationModeId == 1) {
                  let coordY = i32(round(mapY));
                  let coordX = i32(round(mapX));
                  outputValue = readWithFillValue(batch, coordY, coordX,
                    channel);
                } else {
                  let yFloor = floor(mapY);
                  let xFloor = floor(mapX);
                  let yCeil = yFloor + 1.0;
                  let xCeil = xFloor + 1.0;
                  let valueYFloor = (xCeil - mapX) *
                  readWithFillValue(batch, i32(yFloor), i32(xFloor), channel) +
                  (mapX - xFloor) *
                  readWithFillValue(batch, i32(yFloor), i32(xCeil), channel);
                  let valueYCeil = (xCeil - mapX) *
                  readWithFillValue(batch, i32(yCeil), i32(xFloor), channel) +
                  (mapX - xFloor) *
                  readWithFillValue(batch, i32(yCeil), i32(xCeil), channel);
                  outputValue = (yCeil - mapY) * valueYFloor +
                  (mapY - yFloor) * valueYCeil;
                }
              }
              setOutputAtIndex(index, outputValue);
            }
          }
        `}};function wye(e){let{inputs:t,backend:n,attrs:s}=e,{image:r,transforms:a}=t,{interpolation:o,fillMode:i,fillValue:l,outputShape:u}=s,[c,p,d,h]=r.shape,[f,m]=u!=null?u:[p,d],g=[c,f,m,h],y=new vye(g),x=o==="nearest"?1:2,A;switch(i){case"constant":A=1;break;case"reflect":A=2;break;case"wrap":A=3;break;case"nearest":A=4;break;default:A=1;break}let b=[{type:"int32",data:[x]},{type:"int32",data:[A]},{type:"float32",data:[l]}];return n.runWebGPUProgram(y,[r,a],"float32",b)}var kye={kernelName:Vl,backendName:"webgpu",kernelFunc:wye};function Iye(e){let{inputs:t,backend:n,attrs:s}=e,{value:r}=t,{axis:a}=s;a<0&&(a+=r.shape.length);let o=r,i=o.shape.length,l=r.shape[a],u=new Array(i-1),c=0;for(let m=0;m<i;m++)m!==a&&(u[c++]=o.shape[m]);let p=[],d=new Array(i).fill(0),h=o.shape.slice();h[a]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[a]=m;let g=hd({inputs:{x:o},backend:n,attrs:{begin:d,size:h}}),y=Ue({inputs:{x:g},backend:n,attrs:{shape:u}});f[m]=y,p.push(g)}return p.forEach(m=>n.disposeData(m.dataId)),f}var Sye={kernelName:Ul,backendName:"webgpu",kernelFunc:Iye},Cye=[e2e,O2e,z2e,W2e,q2e,K2e,Y2e,Q2e,r1e,l1e,c1e,f1e,n2e,A1e,k1e,N1e,R1e,D1e,F1e,M1e,L1e,V1e,H1e,Z1e,J1e,ege,tge,nge,rge,Y0e,oge,pge,lge,cge,mge,yge,xge,wge,Sge,Tge,Ege,t2e,g1e,_ge,$ge,Fge,Mge,Lge,Wge,Vge,Gge,jge,Xge,Zge,Jge,e3e,j1e,n3e,r3e,o3e,a1e,l3e,c3e,p3e,f3e,g3e,A3e,b3e,o1e,v3e,k3e,S3e,J0e,N3e,_3e,$3e,F3e,M3e,B3e,V3e,G3e,j3e,n1e,pye,fye,K3e,Y3e,nye,rye,oye,iye,uye,q3e,X1e,gye,eye,bye,kye,H2e,Sye,i3e];for(let e of Cye)cr(e);var Tye=class{constructor(e){this.device=e,this.numUsedBuffers=0,this.numFreeBuffers=0,this.freeBuffers=new Map,this.usedBuffers=new Map,this.numBytesUsed=0,this.numBytesAllocated=0}acquireUploadBuffer(e,t){return this.acquireBuffer(e,t,!0)}acquireBuffer(e,t,n=!1){let s=q7(e,t);if(this.freeBuffers.has(s)||this.freeBuffers.set(s,[]),this.usedBuffers.has(s)||this.usedBuffers.set(s,[]),this.numBytesUsed+=e,this.numUsedBuffers++,this.freeBuffers.get(s).length>0){this.numFreeBuffers--;let a=this.freeBuffers.get(s).shift();return this.usedBuffers.get(s).push(a),a}this.numBytesAllocated+=e;let r=this.device.createBuffer({size:e,usage:t,mappedAtCreation:n});return this.usedBuffers.get(s).push(r),r}releaseBuffer(e,t,n){if(this.freeBuffers.size===0)return;let s=q7(t,n);this.freeBuffers.has(s)||this.freeBuffers.set(s,[]),this.freeBuffers.get(s).push(e),this.numFreeBuffers++,this.numUsedBuffers--;let r=this.usedBuffers.get(s),a=r.indexOf(e);if(a<0)throw new Error("Cannot release a buffer that was never provided by this buffer manager");r.splice(a,1),this.numBytesUsed-=t}releaseUploadBuffer(e,t,n){e.mapAsync(GPUMapMode.WRITE).then(()=>{this.releaseBuffer(e,t,n)},s=>{})}getNumUsedBuffers(){return this.numUsedBuffers}getNumFreeBuffers(){return this.numFreeBuffers}dispose(){this.freeBuffers.forEach((e,t)=>{e.forEach(n=>{n.destroy()})}),this.usedBuffers.forEach((e,t)=>{e.forEach(n=>{n.destroy()})}),this.freeBuffers=new Map,this.usedBuffers=new Map,this.numUsedBuffers=0,this.numFreeBuffers=0,this.numBytesUsed=0,this.numBytesAllocated=0}};function q7(e,t){return`${e}_${t}`}var Nye=class{constructor(e){this.device=e,this.numUsedTextures=0,this.numFreeTextures=0,this.freeTextures=new Map,this.usedTextures=new Map,this.numBytesUsed=0,this.numBytesAllocated=0}acquireTexture(e,t,n,s){let r=K7(n),a=e*t*r,o=X7(e,t,n,s);if(this.freeTextures.has(o)||this.freeTextures.set(o,[]),this.usedTextures.has(o)||this.usedTextures.set(o,[]),this.numBytesUsed+=a,this.numUsedTextures++,this.freeTextures.get(o).length>0){this.numFreeTextures--;let l=this.freeTextures.get(o).shift();return this.usedTextures.get(o).push(l),l}this.numBytesAllocated+=a;let i=this.device.createTexture({size:[e,t],format:n,usage:s});return this.usedTextures.get(o).push(i),i}releaseTexture(e,t,n,s,r){if(this.freeTextures.size===0)return;let a=X7(t,n,s,r);this.freeTextures.has(a)||this.freeTextures.set(a,[]),this.freeTextures.get(a).push(e),this.numFreeTextures++,this.numUsedTextures--;let o=this.usedTextures.get(a),i=o.indexOf(e);if(i<0)throw new Error("Cannot release a texture that was never provided by this texture manager");o.splice(i,1);let l=K7(s),u=t*n*l;this.numBytesUsed-=u}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){this.freeTextures.forEach((e,t)=>{e.forEach(n=>{n.destroy()})}),this.usedTextures.forEach((e,t)=>{e.forEach(n=>{n.destroy()})}),this.freeTextures=new Map,this.usedTextures=new Map,this.numUsedTextures=0,this.numFreeTextures=0,this.numBytesUsed=0,this.numBytesAllocated=0}};function X7(e,t,n,s){return`${e}_${t}_${n}_${s}`}function K7(e){if(e==="rgba8unorm")return 16;throw new Error(`${e} is not supported!`)}var Eye=X().getNumber("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD"),Rye=(e,t)=>{let n=e.limits.maxComputeWorkgroupsPerDimension,s=t.dispatchLayout,r=t.dispatch;if(r.every(o=>o<=n))return r;v.assert(r[0]>n&&s.y===void 0&&s.z===void 0,()=>"Dispatch size exceeds WebGPU limits in Y or Z dimension.");let a=Math.ceil(Math.sqrt(r[0]));return a>n?(a=Math.ceil(Math.cbrt(r[0])),v.assert(a<=n,()=>"Total dispatch size exceeds WebGPU maximum."),[a,a,a]):[a,a,1]},E2=class extends uc{constructor(e,t=!1){if(super(),this.commandQueueOwnedIds=new WeakSet,this.dispatchNumberInEncoder=0,this.disposed=!1,this.downloadWaitMs=0,this.tensorDataPendingDisposal=[],this.stagingPendingDisposal=[],this.uniformPendingDisposal=[],this.uploadWaitMs=0,!rb())throw new Error("WebGPU is not supported on this device");this.pipelineCache={},this.device=e,this.queue=e.queue,this.currentCommandEncoder=null,this.currentComputePass=null,this.supportTimeQuery=t,this.bufferManager=new Tye(this.device),this.textureManager=new Nye(this.device),this.tensorMap=new Op(this,sn()),this.supportTimeQuery&&(this.querySet=this.device.createQuerySet({type:"timestamp",count:2})),X().getBool("WEBGPU_USE_PROFILE_TOOL")&&(this.dummyCanvas=document.createElement("canvas"),this.dummyCanvas.width=1,this.dummyCanvas.height=1,this.dummyContext=this.dummyCanvas.getContext("webgpu"),this.dummyContext.configure({device:e,format:"bgra8unorm"}),document.body.appendChild(this.dummyCanvas))}nextDataId(){return E2.nextDataId++}floatPrecision(){return 32}defaultGpuBufferUsage(){return GPUBufferUsage.STORAGE|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST}disposeData(e,t=!1){if(this.tensorDataPendingDisposal.indexOf(e)>=0)return!1;if(!this.tensorMap.has(e))return!0;let n=this.tensorMap.get(e);if(this.decRef(e),!t&&n.refCount>0)return!1;if(this.commandQueueOwnedIds.has(e))return this.tensorDataPendingDisposal.push(e),!1;let{complexTensorInfos:s}=this.tensorMap.get(e);return s!=null&&(this.disposeData(s.real.dataId,t),this.disposeData(s.imag.dataId,t)),this.releaseResource(e),this.tensorMap.delete(e),!0}memory(){return{numBytesInGPU:this.bufferManager.numBytesUsed,numBytesAllocatedInGPU:this.bufferManager.numBytesAllocated,unreliable:!1}}releaseResource(e){let t=this.tensorMap.get(e);if(!(!t||!t.resourceInfo)){if("texture"in t.resourceInfo){let n=t.resourceInfo;n.texture instanceof GPUTexture&&this.textureManager.releaseTexture(n.texture,n.width,n.height,n.format,n.usage),n.texture=null}else{let n=t.resourceInfo;this.bufferManager.releaseBuffer(n.buffer,n.size,n.usage),n.buffer=null}t.resourceInfo=null}}refCount(e){return this.tensorMap.has(e)?this.tensorMap.get(e).refCount:0}incRef(e){let t=this.tensorMap.get(e);t.refCount++}decRef(e){if(this.tensorMap.has(e)){let t=this.tensorMap.get(e);t.refCount--}}write(e,t,n){if(n==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let s={id:this.nextDataId()};return this.tensorMap.set(s,{dtype:n,shape:t,values:e,refCount:1}),s}move(e,t,n,s,r){if(s==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.tensorMap.set(e,{dtype:s,shape:n,values:t,refCount:r})}submitQueue(){this.ensureComputePassEnded(),this.queue.submit([this.currentCommandEncoder.finish()]),this.currentCommandEncoder=null,this.dispatchNumberInEncoder=0,this.commandQueueOwnedIds=new WeakSet,this.tensorDataPendingDisposal.forEach(e=>{this.releaseResource(e),this.tensorMap.delete(e)}),this.uniformPendingDisposal.forEach(e=>this.bufferManager.releaseBuffer(e.buffer,e.size,e.usage)),this.stagingPendingDisposal.forEach(e=>this.bufferManager.releaseUploadBuffer(e.buffer,e.size,e.usage)),this.tensorDataPendingDisposal=[],this.uniformPendingDisposal=[],this.stagingPendingDisposal=[]}ensureCommandEncoderReady(){this.currentCommandEncoder||(this.currentCommandEncoder=this.device.createCommandEncoder())}ensureComputePassEnded(){this.currentComputePass&&(this.currentComputePass.end(),this.currentComputePass=null)}getComputePass(){return this.currentComputePass||(this.currentComputePass=this.currentCommandEncoder.beginComputePass()),this.currentComputePass}async getBufferData(e,t){let n=this.bufferManager.acquireBuffer(t,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(e,0,n,0,t),this.submitQueue(),await n.mapAsync(GPUMapMode.READ);let s=n.getMappedRange().slice(0);return n.unmap(),n!=null&&this.bufferManager.releaseBuffer(n,t,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ),X().getBool("WEBGPU_USE_PROFILE_TOOL")&&(v.assert(this.dummyContext!==void 0,()=>"Fail to get context for profiling tool"),this.dummyContext.getCurrentTexture()),s}convertAndCacheOnCPU(e,t){let n=this.tensorMap.get(e);return this.releaseResource(e),n.values=t,n.values}readSync(e){let t=this.tensorMap.get(e),{values:n}=t;if(n==null)throw new Error("WebGPU readSync is only available for CPU-resident tensors.");return n}async read(e){if(!this.tensorMap.has(e))throw new Error(`Tensor ${e} was not registered!`);let t=this.tensorMap.get(e),{values:n}=t;if(n!=null)return this.convertAndCacheOnCPU(e,n);let s;if(t.dtype==="complex64"){let r=await Promise.all([this.read(t.complexTensorInfos.real.dataId),this.read(t.complexTensorInfos.imag.dataId)]),a=r[0],o=r[1];s=C.mergeRealAndImagArrays(a,o)}else{let r=t.resourceInfo,a=await this.getBufferData(r.buffer,r.size);s=XC(a,t.dtype)}return this.convertAndCacheOnCPU(e,s),s}readToGPU(e){let t=this.tensorMap.get(e),{values:n,dtype:s,shape:r,resourceInfo:a}=t;if(s==="complex64")throw new Error("Does not support reading buffer for complex64 dtype.");if(a==null)throw n!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let o=a.size,i=this.bufferManager.acquireBuffer(o,a.usage);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(a.buffer,0,i,0,o),this.submitQueue();let l=this.makeTensorInfo(r,s),u=sn().makeTensorFromTensorInfo(l),c=this.tensorMap.get(l.dataId);return c.resourceInfo={size:o,usage:this.defaultGpuBufferUsage(),buffer:i},{tensorRef:u,buffer:i,bufSize:o}}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let n=t.map(s=>v.decodeString(s));return Le(e.shape,e.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return Le(e.shape,e.dtype,t)}async time(e){let t=this.activeTimers,n=[],s=!1;this.programTimersStack==null?(this.programTimersStack=n,s=!0):this.activeTimers.push(n),this.activeTimers=n,e();let r=v.flatten(this.activeTimers.map(l=>l.query)).filter(l=>l!=null),a=v.flatten(this.activeTimers.map(l=>l.name)).filter(l=>l!=null);this.activeTimers=t,s&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null},i=await Promise.all(r);return o.kernelMs=v.sum(i),o.getExtraProfileInfo=()=>i.map((l,u)=>({name:a[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", "),this.uploadWaitMs=0,this.downloadWaitMs=0,o}makeTensorInfo(e,t,n){return t==="string"&&n!=null&&n.length>0&&v.isString(n[0])&&(n=n.map(r=>v.encodeString(r))),{dataId:this.write(n,e,t),shape:e,dtype:t}}tensorToBinding(e){if(!e)return null;let t=this.tensorMap.get(e.dataId);if("texture"in t.resourceInfo){let s=t.resourceInfo;return s.texture instanceof GPUExternalTexture?s.texture:s.texture.createView()}let n=t.resourceInfo;return{offset:0,size:n.size,buffer:n.buffer}}async getQueryTime(e){return this.supportTimeQuery?this.getTimeFromQuerySet(e):0}uploadToGPU(e){let t=this.tensorMap.get(e);if(t.resourceInfo)return;let n=qC(t.dtype)*v.sizeFromShape(t.shape),s=this.bufferManager.acquireBuffer(n,this.defaultGpuBufferUsage());if(t.resourceInfo={size:n,usage:this.defaultGpuBufferUsage(),buffer:s},t.values){let r=this.bufferManager.acquireUploadBuffer(n,GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC),a=r.getMappedRange();t.dtype==="int32"||t.dtype==="bool"?new Int32Array(a).set(t.values):new Float32Array(a).set(t.values),r.unmap(),this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(r,0,s,0,n);let o={size:n,usage:GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC,buffer:r};this.stagingPendingDisposal.push(o)}}makeUniforms(e){let t=0,n=0,s=[];e.forEach(i=>{i.data.length===0&&(i.data=[1]);let l;switch(i.data.length){case 1:l=4;break;case 2:l=8;break;case 3:l=16;break;case 4:l=16;break;case 5:l=16;break;case 6:l=16;break;default:v.assert(!1,()=>`Unsupported ${i.data.length}D shape`)}(n===5||n===6)&&(l=16),t=Math.ceil(t/l)*l,n=i.data.length,s.push(t),t+=i.data.length*4});let r=new ArrayBuffer(t);e.forEach((i,l)=>{let u=s[l];i.type==="int32"?new Int32Array(r,u,i.data.length).set(i.data):i.type==="uint32"?new Uint32Array(r,u,i.data.length).set(i.data):new Float32Array(r,u,i.data.length).set(i.data)});let a=this.bufferManager.acquireBuffer(t,GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM);this.queue.writeBuffer(a,0,r,0,t);let o={size:t,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM,buffer:a};return this.uniformPendingDisposal.push(o),{offset:0,size:t,buffer:a}}runWebGPUProgram(e,t,n,s,r){if(r||(r=this.makeTensorInfo(e.outputShape,n)),v.sizeFromShape(r.shape)===0)return this.tensorMap.get(r.dataId).values=v.getTypedArrayFromDType(r.dtype,0),r;this.uploadToGPU(r.dataId),e.dispatch=Rye(this.device,e);let a=[],o=[];if(!e.isFromPixels){a.push({type:"float32",data:[NaN]}),o=t.concat(r).map(g=>g.shape);let f="int32";o.map(g=>{a.push({type:f,data:g})});let m=v.computeStrides(r.shape);if(a.push({type:f,data:m}),e.size){let g=v.sizeFromShape(e.outputShape);a.push({type:f,data:[e.isVec4?g/4:g]})}}let i=t.map((f,m)=>{if(f.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");return this.uploadToGPU(f.dataId),{dtype:this.tensorMap.get(f.dataId).dtype,shape:f.shape,name:e.variableNames[m]}}),l=N0e(e,o,i,r),u;l in this.pipelineCache?u=this.pipelineCache[l]:(u=C0e(this.device,e,i,r),this.pipelineCache[l]=u),s&&(a=[...a,...s]);let c=[this.tensorToBinding(r),...t.map(f=>this.tensorToBinding(f)),this.makeUniforms(a)],p=this.device.createBindGroup({layout:u.getBindGroupLayout(0),entries:c.map((f,m)=>({binding:m,resource:f}))});this.ensureCommandEncoderReady();let d=this.getComputePass(),h=this.activeTimers!=null;return h&&this.supportTimeQuery&&d.writeTimestamp(this.querySet,0),d.setPipeline(u),d.setBindGroup(0,p),d.dispatchWorkgroups(e.dispatch[0],e.dispatch[1],e.dispatch[2]),h&&this.supportTimeQuery&&d.writeTimestamp(this.querySet,1),this.dispatchNumberInEncoder++,t.forEach(f=>{this.commandQueueOwnedIds.add(f.dataId)}),this.commandQueueOwnedIds.add(r.dataId),X().get("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE")<=this.dispatchNumberInEncoder&&this.submitQueue(),h&&this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(this.querySet)}),r}async getTimeFromQuerySet(e){let t=this.bufferManager.acquireBuffer(16,GPUBufferUsage.COPY_SRC|GPUBufferUsage.QUERY_RESOLVE),n=this.bufferManager.acquireBuffer(16,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.resolveQuerySet(e,0,2,t,0),this.currentCommandEncoder.copyBufferToBuffer(t,0,n,0,16),this.submitQueue(),await n.mapAsync(GPUMapMode.READ);let s=new BigUint64Array(n.getMappedRange()),r=Number(s[1]-s[0]);return n.unmap(),this.bufferManager.releaseBuffer(n,16,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST),this.bufferManager.releaseBuffer(t,16,GPUBufferUsage.COPY_SRC|GPUBufferUsage.QUERY_RESOLVE),r/1e6}shouldExecuteOnCPU(e,t=Eye){return X().getBool("WEBGPU_CPU_FORWARD")&&e.every(n=>this.tensorMap.get(n.dataId).resourceInfo==null&&v.sizeFromShape(n.shape)<t)}numDataIds(){return this.tensorMap.numDataIds()-this.tensorDataPendingDisposal.length}dispose(){this.disposed||(this.bufferManager.dispose(),this.textureManager.dispose(),this.disposed=!0)}};E2.nextDataId=0;var fT={};Ve(fT,{WebGPUBackend:()=>E2,webgpu_util:()=>HC});rb()&&jl("webgpu",async()=>{X().set("CHECK_COMPUTATION_FOR_ERRORS",!1);let e={powerPreference:X().get("WEBGPU_USE_LOW_POWER_GPU")?"low-power":"high-performance"},t=await navigator.gpu.requestAdapter(e),n=t.limits,s={},r=t.features.has("timestamp-query");s.requiredLimits={maxComputeWorkgroupStorageSize:n.maxComputeWorkgroupStorageSize,maxComputeWorkgroupsPerDimension:n.maxComputeWorkgroupsPerDimension,maxStorageBufferBindingSize:n.maxStorageBufferBindingSize},r?s.requiredFeatures=["timestamp-query"]:console.warn("This device doesn't support timestamp-query extension. Start Chrome browser with flag --disable-dawn-features=disallow_unsafe_apis then try again. Or zero will shown for the kernel time when profiling mode isenabled. Using performance.now is not workable for webgpu sinceit doesn't support synchronously to read data from GPU.");let a=await t.requestDevice(s);return new E2(a,r)},3);var _ye="3.19.0",Dye="3.19.0",$ye="3.19.0",Pye="3.19.0",Fye="3.19.0",Oye="3.19.0",Mye="3.19.0",Vh={tfjs:_ye,"tfjs-core":Dye,"tfjs-data":$ye,"tfjs-layers":Pye,"tfjs-converter":Fye,"tfjs-backend-webgl":Oye,"tfjs-backend-wasm":Mye};var mT=`
  precision highp float;
  attribute vec2 pos;
  attribute vec2 uv;
  varying vec2 vUv;
  uniform float flipY;
  void main(void) {
    vUv = uv;
    gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);
  }
`;var gT=`
  precision highp float;
  varying vec2 vUv;
  uniform sampler2D texture;
  uniform float m[20];
  void main(void) {
    vec4 c = texture2D(texture, vUv);
    gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];
    gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];
    gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];
    gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];
  }
`,yT=`
  precision highp float;
  varying vec2 vUv;
  uniform sampler2D texture;
  uniform float m[20];
  void main(void) {
    vec4 c = texture2D(texture, vUv);
    gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];
    gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];
    gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];
    gl_FragColor.a = c.a;
  }
`,AT=`
  precision highp float;
  varying vec2 vUv;
  uniform vec2 size;
  uniform sampler2D texture;
  vec2 pixelate(vec2 coord, vec2 size) {
    return floor( coord / size ) * size;
  }
  void main(void) {
    gl_FragColor = vec4(0.0);
    vec2 coord = pixelate(vUv, size);
    gl_FragColor += texture2D(texture, coord);
  }
`,xT=`
  precision highp float;
  varying vec2 vUv;
  uniform sampler2D texture;
  uniform vec2 px;
  void main(void) {
    gl_FragColor = vec4(0.0);
    gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;
    gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;
    gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;
    gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;
    gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;
    gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;
    gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;
    gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;
    gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;
    gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;
    gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;
    gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;
    gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;
    gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;
    gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;
  }
`,bT=`
  precision highp float;
  varying vec2 vUv;
  uniform sampler2D texture;
  uniform vec2 px;
  uniform float m[9];
  void main(void) {
    vec4 c11 = texture2D(texture, vUv - px); // top left
    vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y)); // top center
    vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y)); // top right
    vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) ); // mid left
    vec4 c22 = texture2D(texture, vUv); // mid center
    vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) ); // mid right
    vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) ); // bottom left
    vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) ); // bottom center
    vec4 c33 = texture2D(texture, vUv + px ); // bottom right
    gl_FragColor = 
    c11 * m[0] + c12 * m[1] + c22 * m[2] +
    c21 * m[3] + c22 * m[4] + c23 * m[5] +
    c31 * m[6] + c32 * m[7] + c33 * m[8];
    gl_FragColor.a = c22.a;
  }
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A=Math.cos(x),b=Math.sin(x),w=.213,k=.715,S=.072;y.colorMatrix([w+A*(1-w)+b*-w,k+A*-k+b*-k,S+A*-S+b*(1-S),0,0,w+A*-w+b*.143,k+A*(1-k)+b*.14,S+A*-S+b*-.283,0,0,w+A*-w+b*-(1-w),k+A*-k+b*k,S+A*(1-S)+b*S,0,0,0,0,0,1,0])},desaturateLuminance:()=>{y.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},sepia:()=>{y.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},brownie:()=>{y.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},vintagePinhole:()=>{y.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},kodachrome:()=>{y.colorMatrix([1.1285582396593525,-.3967382283601348,-.03992559172921793,0,63.72958762196502,-.16404339962244616,1.0835251566291304,-.05498805115633132,0,24.732407896706203,-.16786010706155763,-.5603416277695248,1.6014850761964943,0,35.62982807460946,0,0,0,1,0])},technicolor:()=>{y.colorMatrix([1.9125277891456083,-.8545344976951645,-.09155508482755585,0,11.793603434377337,-.3087833385928097,1.7658908555458428,-.10601743074722245,0,-70.35205161461398,-.231103377548616,-.7501899197440212,1.847597816108189,0,30.950940869491138,0,0,0,1,0])},polaroid:()=>{y.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},shiftToBGR:()=>{y.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},convolution:x=>{let 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vT:null),fe.filter=!!$t,!$t||!$t.add?(t.debug&&ie("input process error: cannot initialize filters"),fe.webgl.supported=!1,t.filter.enabled=!1,D2(mt,cn)):($t.reset(),t.filter.brightness!==0&&$t.add("brightness",t.filter.brightness),t.filter.contrast!==0&&$t.add("contrast",t.filter.contrast),t.filter.sharpness!==0&&$t.add("sharpen",t.filter.sharpness),t.filter.blur!==0&&$t.add("blur",t.filter.blur),t.filter.saturation!==0&&$t.add("saturation",t.filter.saturation),t.filter.hue!==0&&$t.add("hue",t.filter.hue),t.filter.negative&&$t.add("negative"),t.filter.sepia&&$t.add("sepia"),t.filter.vintage&&$t.add("brownie"),t.filter.sepia&&$t.add("sepia"),t.filter.kodachrome&&$t.add("kodachrome"),t.filter.technicolor&&$t.add("technicolor"),t.filter.polaroid&&$t.add("polaroid"),t.filter.pixelate!==0&&$t.add("pixelate",t.filter.pixelate),$t.get()>0?cn=$t.apply(mt):cn=$t.draw(mt))):(D2(mt,cn),$t&&($t=null),fe.filter=!!$t),!n)return{tensor:null,canvas:cn};if(!cn)throw new Error("canvas error: cannot create output");let l,u=3;if(typeof ImageData!="undefined"&&e instanceof ImageData||e.data&&e.width&&e.height)if(fe.browser&&Ys)l=Ys?Ys.fromPixels(e):null;else{u=e.data.length/e.height/e.width;let d=new Uint8Array(e.data.buffer);l=ft(d,[e.height,e.width,u],"int32")}else if((!fd||cn.width!==fd.width||cn.height!==fd.height)&&(fd=is(cn.width,cn.height)),Ys&&fe.browser)t.backend==="webgl"||t.backend==="humangl"||t.backend==="webgpu"?l=Ys.fromPixels(cn):(fd=D2(cn),l=Ys.fromPixels(fd));else{let f=D2(cn).getContext("2d").getImageData(0,0,a,o);u=f.data.length/a/o;let m=new Uint8Array(f.data.buffer);l=ft(m,[a,o,u])}if(u===4){let d=ui(l,[0,0,0],[-1,-1,3]);ne(l),l=d}if(!l)throw new Error("input error: cannot create tensor");let c=ge(l,"float32"),p=t.filter.equalization?await R2(c):Kt(c,0);return ne([l,c]),{tensor:p,canvas:t.filter.return?cn:null}}}async function wT(e,t){let n=!1;if(e.cacheSensitivity===0||!t.shape||t.shape.length!==4||t.shape[1]>2048||t.shape[2]>2048)return 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gd=e=>[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])],O2=e=>[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2,1],M2=(e,t)=>e?[Math.trunc(Math.max(0,e.startPoint[0])),Math.trunc(Math.max(0,e.startPoint[1])),Math.trunc(Math.min(t.shape[2]||0,e.endPoint[0])-Math.max(0,e.startPoint[0])),Math.trunc(Math.min(t.shape[1]||0,e.endPoint[1])-Math.max(0,e.startPoint[1]))]:[0,0,0,0],z2=(e,t)=>e?[e.startPoint[0]/(t.shape[2]||0),e.startPoint[1]/(t.shape[1]||0),(e.endPoint[0]-e.startPoint[0])/(t.shape[2]||0),(e.endPoint[1]-e.startPoint[1])/(t.shape[1]||0)]:[0,0,0,0],GT=(e,t)=>{let n=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],s=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]];return{startPoint:n,endPoint:s,landmarks:e.landmarks,confidence:e.confidence}},Tb=(e,t,n)=>{let s=t.shape[1],r=t.shape[2],a=[e.startPoint[1]/s,e.startPoint[0]/r,e.endPoint[1]/s,e.endPoint[0]/r],o=Ne.cropAndResize(t,[a],[0],n),i=pe(o,nt.tf255);return ne(o),i},L2=(e,t)=>{let n=O2(e),s=gd(e),r=[t*s[0]/2,t*s[1]/2];return{startPoint:[n[0]-r[0],n[1]-r[1]],endPoint:[n[0]+r[0],n[1]+r[1]],landmarks:e.landmarks,confidence:e.confidence}},B2=e=>{let t=O2(e),n=gd(e),s=Math.max(...n)/2;return{startPoint:[Math.round(t[0]-s),Math.round(t[1]-s)],endPoint:[Math.round(t[0]+s),Math.round(t[1]+s)],landmarks:e.landmarks,confidence:e.confidence}},HT=e=>{let t=e.map(s=>s[0]),n=e.map(s=>s[1]);return{startPoint:[Math.min(...t),Math.min(...n)],endPoint:[Math.max(...t),Math.max(...n)],landmarks:e}},Nb=[[1,0,0],[0,1,0],[0,0,1]],qAe=e=>e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI)),XAe=(e,t)=>qAe(Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]));var VT=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]],lu=(e,t)=>{let n=0;for(let s=0;s<e.length;s++)n+=e[s]*t[s];return n},KAe=(e,t)=>{let n=[];for(let s=0;s<e.length;s++)n.push(e[s][t]);return n},UT=(e,t)=>{let n=[],s=e.length;for(let r=0;r<s;r++){n.push([]);for(let a=0;a<s;a++)n[r].push(lu(e[r],KAe(t,a)))}return n},jT=(e,t)=>{let n=Math.cos(e),s=Math.sin(e),r=[[n,-s,0],[s,n,0],[0,0,1]],a=VT(t[0],t[1]),o=UT(a,r),i=VT(-t[0],-t[1]);return UT(o,i)},ZAe=e=>{let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],n=[e[0][2],e[1][2]],s=[-lu(t[0],n),-lu(t[1],n)];return[t[0].concat(s[0]),t[1].concat(s[1]),[0,0,1]]},YAe=(e,t)=>[lu(e,t[0]),lu(e,t[1])];function qT(e){let t=e===192?{strides:[4],anchors:[1]}:{strides:[e/16,e/8],anchors:[2,6]},n=[];for(let s=0;s<t.strides.length;s++){let r=t.strides[s],a=Math.floor((e+r-1)/r),o=Math.floor((e+r-1)/r),i=t.anchors[s];for(let l=0;l<a;l++){let u=r*(l+.5);for(let c=0;c<o;c++){let p=r*(c+.5);for(let d=0;d<i;d++)n.push([p,u])}}}return n}function XT(e,t,n,s,r){let a=gd(t),o=e.map(h=>[a[0]/r*(h[0]-r/2),a[1]/r*(h[1]-r/2),h[2]||0]),i=n&&n!==0&&Math.abs(n)>.2,l=i?jT(n,[0,0]):Nb,u=i?o.map(h=>[...YAe(h,l),h[2]]):o,c=i?ZAe(s):Nb,p=O2(t),d=[lu(p,c[0]),lu(p,c[1])];return u.map(h=>[Math.trunc(h[0]+d[0]),Math.trunc(h[1]+d[1]),Math.trunc(h[2]||0)])}function KT(e,t,n,s){let r=t.landmarks.length>=Ib.count?Ib.symmetryLine:ou.symmetryLine,a=0,o=Nb,i;if(e&&fe.kernels.includes("rotatewithoffset"))if(a=XAe(t.landmarks[r[0]],t.landmarks[r[1]]),a&&a!==0&&Math.abs(a)>.2){let u=O2(t),c=[u[0]/n.shape[2],u[1]/n.shape[1]],p=Ne.rotateWithOffset(n,a,0,c);o=jT(-a,u),i=Tb(t,p,[s,s]),ne(p)}else i=Tb(t,n,[s,s]);else i=Tb(t,n,[s,s]);return[a,o,i]}var JAe=e=>{let t=e.map(s=>s[0]),n=e.map(s=>s[1]);return[Math.min(...t)+(Math.max(...t)-Math.min(...t))/2,Math.min(...n)+(Math.max(...n)-Math.min(...n))/2]},ZT=(e,t)=>{let n=JAe(e),s=gd(t);return{startPoint:[n[0]-s[0]/2,n[1]-s[1]/2],endPoint:[n[0]+s[0]/2,n[1]+s[1]/2]}};var YT=6,QAe=1.4,Qr,JT=null,fi=0,Hh=null,yd=()=>fi;async function QT(e){var t;return fe.initial&&(Qr=null),Qr?e.debug&&ie("cached model:",Qr.modelUrl):Qr=await qe((t=e.face.detector)==null?void 0:t.modelPath),fi=Qr.inputs[0].shape?Qr.inputs[0].shape[2]:0,Hh=Se(fi,"int32"),JT=or(qT(fi)),Qr}function e5e(e){let t={};t.boxStarts=Oe(e,[0,1],[-1,2]),t.centers=ce(t.boxStarts,JT),t.boxSizes=Oe(e,[0,3],[-1,2]),t.boxSizesNormalized=pe(t.boxSizes,Hh),t.centersNormalized=pe(t.centers,Hh),t.halfBoxSize=pe(t.boxSizesNormalized,nt.tf2),t.starts=he(t.centersNormalized,t.halfBoxSize),t.ends=ce(t.centersNormalized,t.halfBoxSize),t.startNormalized=L(t.starts,Hh),t.endNormalized=L(t.ends,Hh);let n=Xl([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(s=>ne(t[s])),n}async function eN(e,t){var i,l,u,c;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let n={};n.resized=Ne.resizeBilinear(e,[fi,fi]),n.div=pe(n.resized,nt.tf127),n.normalized=he(n.div,nt.tf05);let s=Qr==null?void 0:Qr.execute(n.normalized);if(Array.isArray(s)&&s.length>2){let p=s.sort((d,h)=>d.size-h.size);n.concat384=Ct([p[0],p[2]],2),n.concat512=Ct([p[1],p[3]],2),n.concat=Ct([n.concat512,n.concat384],1),n.batch=rt(n.concat,0)}else Array.isArray(s)?n.batch=rt(s[0]):n.batch=rt(s);ne(s),n.boxes=e5e(n.batch),n.logits=Oe(n.batch,[0,0],[-1,1]),n.sigmoid=Cn(n.logits),n.scores=rt(n.sigmoid),n.nms=await Ne.nonMaxSuppressionAsync(n.boxes,n.scores,((i=t.face.detector)==null?void 0:i.maxDetected)||0,((l=t.face.detector)==null?void 0:l.iouThreshold)||0,((u=t.face.detector)==null?void 0:u.minConfidence)||0);let r=await n.nms.array(),a=[],o=await n.scores.data();for(let p=0;p<r.length;p++){let d=o[r[p]];if(d>(((c=t.face.detector)==null?void 0:c.minConfidence)||0)){let h={};h.bbox=Oe(n.boxes,[r[p],0],[1,-1]),h.slice=Oe(n.batch,[r[p],YT-1],[1,-1]),h.squeeze=rt(h.slice),h.landmarks=U(h.squeeze,[YT,-1]);let f=await h.bbox.data(),m={startPoint:[f[0],f[1]],endPoint:[f[2],f[3]],landmarks:await h.landmarks.array(),confidence:d},g=GT(m,[(e.shape[2]||0)/fi,(e.shape[1]||0)/fi]),y=L2(g,t.face.scale||QAe),x=B2(y);a.push(x),Object.keys(h).forEach(A=>ne(h[A]))}}return Object.keys(n).forEach(p=>ne(n[p])),a}var W2={};oa(W2,{connected:()=>_b,kpt:()=>Rb});var Rb=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPinky","rightPinky","leftIndex","rightIndex","leftThumb","rightThumb","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","bodyCenter","bodyTop","leftPalm","leftHand","rightPalm","rightHand"],_b={shoulders:["leftShoulder","rightShoulder"],hips:["rightHip","leftHip"],mouth:["leftMouth","rightMouth"],leftLegUpper:["leftHip","leftKnee"],leftLegLower:["leftKnee","leftAnkle"],leftFoot:["leftAnkle","leftHeel","leftFoot"],leftTorso:["leftShoulder","leftHip"],leftArmUpper:["leftShoulder","leftElbow"],leftArmLower:["leftElbow","leftWrist"],leftHand:["leftWrist","leftPalm"],leftHandPinky:["leftPalm","leftPinky"],leftHandIndex:["leftPalm","leftIndex"],leftHandThumb:["leftPalm","leftThumb"],leftEyeOutline:["leftEyeInside","leftEyeOutside"],rightLegUpper:["rightHip","rightKnee"],rightLegLower:["rightKnee","rightAnkle"],rightFoot:["rightAnkle","rightHeel","rightFoot"],rightTorso:["rightShoulder","rightHip"],rightArmUpper:["rightShoulder","rightElbow"],rightArmLower:["rightElbow","rightWrist"],rightHand:["rightWrist","rightPalm"],rightHandPinky:["rightPalm","rightPinky"],rightHandIndex:["rightPalm","rightIndex"],rightHandThumb:["rightPalm","rightThumb"],rightEyeOutline:["rightEyeInside","rightEyeOutside"]};var nN=224,t5e,n5e=5,V2=[8,16,32,32,32];async function sN(){let e=[],t=0;for(;t<n5e;){let n=0,s=t;for(;s<V2.length&&V2[s]===V2[t];)n+=2,s++;let r=V2[t],a=Math.ceil(nN/r),o=Math.ceil(nN/r);for(let i=0;i<a;++i)for(let l=0;l<o;++l)for(let u=0;u<n;++u)e.push({x:(l+.5)/o,y:(i+.5)/a});t=s}t5e={x:Ft(e.map(n=>n.x)),y:Ft(e.map(n=>n.y))}}function Ta(e,t=[1,1]){let n=[e.map(i=>i[0]),e.map(i=>i[1])],s=[Math.min(...n[0]),Math.min(...n[1])],r=[Math.max(...n[0]),Math.max(...n[1])],a=[s[0],s[1],r[0]-s[0],r[1]-s[1]],o=[a[0]/t[0],a[1]/t[1],a[2]/t[0],a[3]/t[1]];return{box:a,boxRaw:o}}function rN(e,t=[1,1]){let n=[e.map(u=>u[0]),e.map(u=>u[1])],s=[Math.min(...n[0]),Math.min(...n[1])],r=[Math.max(...n[0]),Math.max(...n[1])],a=[(s[0]+r[0])/2,(s[1]+r[1])/2],o=Math.max(a[0]-s[0],a[1]-s[1],-a[0]+r[0],-a[1]+r[1]),i=[Math.trunc(a[0]-o),Math.trunc(a[1]-o),Math.trunc(2*o),Math.trunc(2*o)],l=[i[0]/t[0],i[1]/t[1],i[2]/t[0],i[3]/t[1]];return{box:i,boxRaw:l}}function U2(e,t){let n=[e[2]*t,e[3]*t];return[e[0]-(n[0]-e[2])/2,e[1]-(n[1]-e[3])/2,n[0],n[1]]}var iN={initial:!0},Ms={detector:null,landmarks:null},Ad={detector:[224,224],landmarks:[256,256]},Db=Number.MAX_SAFE_INTEGER,r5e={landmarks:["ld_3d","activation_segmentation","activation_heatmap","world_3d","output_poseflag"],detector:[]},H2=null,jh,mi=[[0,0],[0,0],[0,0],[0,0]],aN=0,oN=e=>1-1/(1+Math.exp(e));async function lN(e){if(iN.initial&&(Ms.detector=null),!Ms.detector&&e.body.detector&&e.body.detector.modelPath){Ms.detector=await qe(e.body.detector.modelPath);let t=Object.values(Ms.detector.modelSignature.inputs);Ad.detector[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,Ad.detector[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&Ms.detector&&ie("cached model:",Ms.detector.modelUrl);return await sN(),Ms.detector}async function uN(e){if(iN.initial&&(Ms.landmarks=null),Ms.landmarks)e.debug&&ie("cached model:",Ms.landmarks.modelUrl);else{Ms.landmarks=await qe(e.body.modelPath);let t=Object.values(Ms.landmarks.modelSignature.inputs);Ad.landmarks[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,Ad.landmarks[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return Ms.landmarks}async function a5e(e,t){let n={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;let s;if(jh&&(n.cropped=Ne.cropAndResize(e,[jh],[0],[e.shape[1],e.shape[2]])),e.shape[1]!==e.shape[2]){let r=[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],a=[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0];mi=[[0,0],r,a,[0,0]],n.pad=Js(n.cropped||e,mi),n.resize=Ne.resizeBilinear(n.pad,[t,t]),s=pe(n.resize,nt.tf255)}else e.shape[1]!==t?(n.resize=Ne.resizeBilinear(n.cropped||e,[t,t]),s=pe(n.resize,nt.tf255)):s=pe(n.cropped||e,nt.tf255);return Object.keys(n).forEach(r=>ne(n[r])),s}function o5e(e,t){for(let n of e)n.position=[Math.trunc(n.position[0]*(t[0]+mi[2][0]+mi[2][1])/t[0]-mi[2][0]),Math.trunc(n.position[1]*(t[1]+mi[1][0]+mi[1][1])/t[1]-mi[1][0]),n.position[2]],n.positionRaw=[n.position[0]/t[0],n.position[1]/t[1],2*n.position[2]/(t[0]+t[1])];if(jh)for(let n of e)n.positionRaw=[n.positionRaw[0]+jh[1],n.positionRaw[1]+jh[0],n.positionRaw[2]],n.position=[Math.trunc(n.positionRaw[0]*t[0]),Math.trunc(n.positionRaw[1]*t[1]),n.positionRaw[2]];return e}async function i5e(e){let t=e.find(i=>i.part==="leftPalm"),n=e.find(i=>i.part==="leftWrist"),s=e.find(i=>i.part==="leftIndex");t.position[2]=((n.position[2]||0)+(s.position[2]||0))/2;let r=e.find(i=>i.part==="rightPalm"),a=e.find(i=>i.part==="rightWrist"),o=e.find(i=>i.part==="rightIndex");r.position[2]=((a.position[2]||0)+(o.position[2]||0))/2}async function l5e(e,t,n){var f;let s={};[s.ld,s.segmentation,s.heatmap,s.world,s.poseflag]=(f=Ms.landmarks)==null?void 0:f.execute(e,r5e.landmarks);let r=(await s.poseflag.data())[0],a=await s.ld.data(),o=await s.world.data();Object.keys(s).forEach(m=>ne(s[m]));let i=[],l=5;for(let m=0;m<a.length/l;m++){let g=oN(a[l*m+3]),y=oN(a[l*m+4]),x=Math.trunc(100*g*y*r)/100,A=[a[l*m+0]/Ad.landmarks[0],a[l*m+1]/Ad.landmarks[1],a[l*m+2]+0],b=[Math.trunc(n[0]*A[0]),Math.trunc(n[1]*A[1]),A[2]],w=[o[l*m+0],o[l*m+1],o[l*m+2]+0];i.push({part:Rb[m],positionRaw:A,position:b,distance:w,score:x})}if(r<(t.body.minConfidence||0))return null;i5e(i);let u=o5e(i,n),c=u.map(m=>m.position),p=Ta(c,[n[0],n[1]]),d={};for(let[m,g]of Object.entries(_b)){let y=[];for(let x=0;x<g.length-1;x++){let A=u.find(w=>w.part===g[x]),b=u.find(w=>w.part===g[x+1]);A&&b&&y.push([A.position,b.position])}d[m]=y}return{id:0,score:Math.trunc(100*r)/100,box:p.box,boxRaw:p.boxRaw,keypoints:u,annotations:d}}async function $b(e,t){let n=[e.shape[2]||0,e.shape[1]||0],s=(t.body.skipTime||0)>ue()-aN,r=Db<(t.body.skipFrames||0);if(t.skipAllowed&&s&&r&&H2!==null)Db++;else{let a={};a.landmarks=await a5e(e,256),H2=await l5e(a.landmarks,t,n),Object.keys(a).forEach(o=>ne(a[o])),aN=ue(),Db=0}return H2?[H2]:[]}var xd=[{class:1,label:"person"},{class:2,label:"bicycle"},{class:3,label:"car"},{class:4,label:"motorcycle"},{class:5,label:"airplane"},{class:6,label:"bus"},{class:7,label:"train"},{class:8,label:"truck"},{class:9,label:"boat"},{class:10,label:"traffic light"},{class:11,label:"fire hydrant"},{class:12,label:"stop sign"},{class:13,label:"parking meter"},{class:14,label:"bench"},{class:15,label:"bird"},{class:16,label:"cat"},{class:17,label:"dog"},{class:18,label:"horse"},{class:19,label:"sheep"},{class:20,label:"cow"},{class:21,label:"elephant"},{class:22,label:"bear"},{class:23,label:"zebra"},{class:24,label:"giraffe"},{class:25,label:"backpack"},{class:26,label:"umbrella"},{class:27,label:"handbag"},{class:28,label:"tie"},{class:29,label:"suitcase"},{class:30,label:"frisbee"},{class:31,label:"skis"},{class:32,label:"snowboard"},{class:33,label:"sports ball"},{class:34,label:"kite"},{class:35,label:"baseball bat"},{class:36,label:"baseball glove"},{class:37,label:"skateboard"},{class:38,label:"surfboard"},{class:39,label:"tennis racket"},{class:40,label:"bottle"},{class:41,label:"wine glass"},{class:42,label:"cup"},{class:43,label:"fork"},{class:44,label:"knife"},{class:45,label:"spoon"},{class:46,label:"bowl"},{class:47,label:"banana"},{class:48,label:"apple"},{class:49,label:"sandwich"},{class:50,label:"orange"},{class:51,label:"broccoli"},{class:52,label:"carrot"},{class:53,label:"hot dog"},{class:54,label:"pizza"},{class:55,label:"donut"},{class:56,label:"cake"},{class:57,label:"chair"},{class:58,label:"couch"},{class:59,label:"potted plant"},{class:60,label:"bed"},{class:61,label:"dining table"},{class:62,label:"toilet"},{class:63,label:"tv"},{class:64,label:"laptop"},{class:65,label:"mouse"},{class:66,label:"remote"},{class:67,label:"keyboard"},{class:68,label:"cell phone"},{class:69,label:"microwave"},{class:70,label:"oven"},{class:71,label:"toaster"},{class:72,label:"sink"},{class:73,label:"refrigerator"},{class:74,label:"book"},{class:75,label:"clock"},{class:76,label:"vase"},{class:77,label:"scissors"},{class:78,label:"teddy bear"},{class:79,label:"hair drier"},{class:80,label:"toothbrush"}];var Na,uu=0,Pb=[],dN=0,Fb=Number.MAX_SAFE_INTEGER;async function pN(e){if(fe.initial&&(Na=null),Na)e.debug&&ie("cached model:",Na.modelUrl);else{Na=await qe(e.object.modelPath);let t=Object.values(Na.modelSignature.inputs);uu=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return Na}async function u5e(e,t,n){if(!e)return[];let s={},r=[],a=await e.array();s.squeeze=rt(e);let o=Zt(s.squeeze,6,1);s.stack=on([o[1],o[0],o[3],o[2]],1),s.boxes=rt(s.stack),s.scores=rt(o[4]),s.classes=rt(o[5]),ne([e,...o]),s.nms=await Ne.nonMaxSuppressionAsync(s.boxes,s.scores,n.object.maxDetected,n.object.iouThreshold,n.object.minConfidence||0);let i=await s.nms.data(),l=0;for(let u of Array.from(i)){let c=Math.trunc(100*a[0][u][4])/100,p=a[0][u][5],d=xd[p].label,[h,f]=[a[0][u][0]/uu,a[0][u][1]/uu],m=[h,f,a[0][u][2]/uu-h,a[0][u][3]/uu-f],g=[Math.trunc(m[0]*t[0]),Math.trunc(m[1]*t[1]),Math.trunc(m[2]*t[0]),Math.trunc(m[3]*t[1])];r.push({id:l++,score:c,class:p,label:d,box:g,boxRaw:m})}return Object.keys(s).forEach(u=>ne(s[u])),r}async function Ob(e,t){let n=(t.object.skipTime||0)>ue()-dN,s=Fb<(t.object.skipFrames||0);return t.skipAllowed&&n&&s&&Pb.length>0?(Fb++,Pb):(Fb=0,new Promise(async r=>{let a=[e.shape[2]||0,e.shape[1]||0],o=Ne.resizeBilinear(e,[uu,uu]),i=t.object.enabled?Na==null?void 0:Na.execute(o,["tower_0/detections"]):null;dN=ue(),ne(o);let l=await u5e(i,a,t);Pb=l,r(l)}))}var j2={};oa(j2,{connected:()=>zb,kpt:()=>Mb});var Mb=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","bodyCenter","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"],zb={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var Ln,fN=0,us={id:0,keypoints:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,annotations:{}},Lb=Number.MAX_SAFE_INTEGER;async function mN(e){return fe.initial&&(Ln=null),Ln?e.debug&&ie("cached model:",Ln.modelUrl):Ln=await qe(e.body.modelPath),Ln}async function c5e(e,t){let[n,s]=e.shape,r=U(e,[s*n]),a=mn(r,0),o=(await a.data())[0];if(ne([r,a]),o>t){let i=Es(r,0),l=Zl(i,n),u=(await l.data())[0],c=pe(i,Se(n,"int32")),p=(await c.data())[0];return ne([l,c]),[u,p,o]}return[0,0,o]}async function Bb(e,t){let n=(t.body.skipTime||0)>ue()-fN,s=Lb<(t.body.skipFrames||0);return t.skipAllowed&&n&&s&&Object.keys(us.keypoints).length>0?(Lb++,[us]):(Lb=0,new Promise(async r=>{var p;let a=J(()=>{if(!(Ln!=null&&Ln.inputs[0].shape))return null;let d=Ne.resizeBilinear(e,[Ln.inputs[0].shape[2],Ln.inputs[0].shape[1]],!1),h=L(d,nt.tf2);return he(h,nt.tf1)}),o;if(t.body.enabled&&(o=Ln==null?void 0:Ln.execute(a)),fN=ue(),ne(a),o){us.keypoints.length=0;let d=o.squeeze();ne(o);let h=d.unstack(2);ne(d);for(let f=0;f<h.length;f++){let[m,g,y]=await c5e(h[f],t.body.minConfidence);y>(((p=t.body)==null?void 0:p.minConfidence)||0)&&us.keypoints.push({score:Math.round(100*y)/100,part:Mb[f],positionRaw:[m/Ln.inputs[0].shape[2],g/Ln.inputs[0].shape[1]],position:[Math.round(e.shape[2]*m/Ln.inputs[0].shape[2]),Math.round(e.shape[1]*g/Ln.inputs[0].shape[1])]})}h.forEach(f=>ne(f))}us.score=us.keypoints.reduce((d,h)=>h.score>d?h.score:d,0);let i=us.keypoints.map(d=>d.position[0]),l=us.keypoints.map(d=>d.position[1]);us.box=[Math.min(...i),Math.min(...l),Math.max(...i)-Math.min(...i),Math.max(...l)-Math.min(...l)];let u=us.keypoints.map(d=>d.positionRaw[0]),c=us.keypoints.map(d=>d.positionRaw[1]);us.boxRaw=[Math.min(...u),Math.min(...c),Math.max(...u)-Math.min(...u),Math.max(...c)-Math.min(...c)];for(let[d,h]of Object.entries(zb)){let f=[];for(let m=0;m<h.length-1;m++){let g=us.keypoints.find(x=>x.part===h[m]),y=us.keypoints.find(x=>x.part===h[m+1]);g&&y&&g.score>(t.body.minConfidence||0)&&y.score>(t.body.minConfidence||0)&&f.push([g.position,y.position])}us.annotations[d]=f}r([us])}))}var d5e=["angry","disgust","fear","happy","sad","surprise","neutral"],er,q2=[],yN=0,AN=0,Wb=Number.MAX_SAFE_INTEGER;async function xN(e){var t;return fe.initial&&(er=null),er?e.debug&&ie("cached model:",er.modelUrl):er=await qe((t=e.face.emotion)==null?void 0:t.modelPath),er}async function Vb(e,t,n,s){var o,i;if(!er)return[];let r=Wb<(((o=t.face.emotion)==null?void 0:o.skipFrames)||0),a=(((i=t.face.emotion)==null?void 0:i.skipTime)||0)>ue()-AN;return t.skipAllowed&&a&&r&&yN===s&&q2[n]&&q2[n].length>0?(Wb++,q2[n]):(Wb=0,new Promise(async l=>{var c,p;let u=[];if((c=t.face.emotion)!=null&&c.enabled){let d={},h=er!=null&&er.inputs[0].shape?er.inputs[0].shape[2]:0;d.resize=Ne.resizeBilinear(e,[h,h],!1),d.channels=L(d.resize,nt.rgb),d.grayscale=ke(d.channels,3,!0),d.grayscaleSub=he(d.grayscale,nt.tf05),d.grayscaleMul=L(d.grayscaleSub,nt.tf2),d.emotion=er==null?void 0:er.execute(d.grayscaleMul),AN=ue();let f=await d.emotion.data();for(let m=0;m<f.length;m++)f[m]>(((p=t.face.emotion)==null?void 0:p.minConfidence)||0)&&u.push({score:Math.min(.99,Math.trunc(100*f[m])/100),emotion:d5e[m]});u.sort((m,g)=>g.score-m.score),Object.keys(d).forEach(m=>ne(d[m]))}q2[n]=u,yN=s,l(u)}))}var zs,Ub=[],vN=0,wN=0,kN=Number.MAX_SAFE_INTEGER;async function IN(e){return fe.initial&&(zs=null),zs?e.debug&&ie("cached model:",zs.modelUrl):zs=await qe(e.face.mobilefacenet.modelPath),zs}async function Gb(e,t,n,s){var o,i;if(!zs)return[];let r=kN<(((o=t.face.embedding)==null?void 0:o.skipFrames)||0),a=(((i=t.face.embedding)==null?void 0:i.skipTime)||0)>ue()-wN;return t.skipAllowed&&a&&r&&vN===s&&Ub[n]?(kN++,Ub[n]):new Promise(async l=>{var c;let u=[];if(((c=t.face.embedding)==null?void 0:c.enabled)&&(zs==null?void 0:zs.inputs[0].shape)){let p={};p.crop=Ne.resizeBilinear(e,[zs.inputs[0].shape[2],zs.inputs[0].shape[1]],!1),p.data=zs==null?void 0:zs.execute(p.crop);let d=await p.data.data();u=Array.from(d)}Ub[n]=u,vN=s,wN=ue(),l(u)})}var Ea,gi=0,p5e=2.3,Hb=gr.leftEyeLower0,jb=gr.rightEyeLower0,bd={leftBounds:[Hb[0],Hb[Hb.length-1]],rightBounds:[jb[0],jb[jb.length-1]]},vd={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function EN(e){var t;return fe.initial&&(Ea=null),Ea?e.debug&&ie("cached model:",Ea.modelUrl):Ea=await qe((t=e.face.iris)==null?void 0:t.modelPath),gi=Ea.inputs[0].shape?Ea.inputs[0].shape[2]:0,gi===-1&&(gi=64),Ea}function X2(e,t,n,s){for(let r=0;r<Sb.length;r++){let{key:a,indices:o}=Sb[r],i=gr[`${n}${a}`];if(!s||s.includes(a))for(let l=0;l<o.length;l++){let u=o[l];e[i[l]]=[t[u][0],t[u][1],(t[u][2]+e[i[l]][2])/2]}}}var h5e=e=>{let t=e[bd.leftBounds[0]][2],n=e[bd.rightBounds[0]][2];return t-n},CN=(e,t,n,s,r,a=!1)=>{let o=B2(L2(HT([e[n],e[s]]),p5e)),i=gd(o),l=Ne.cropAndResize(t,[[o.startPoint[1]/r,o.startPoint[0]/r,o.endPoint[1]/r,o.endPoint[0]/r]],[0],[gi,gi]);if(a&&fe.kernels.includes("flipleftright")){let u=Ne.flipLeftRight(l);ne(l),l=u}return{box:o,boxSize:i,crop:l}},TN=(e,t,n,s=!1)=>{let r=[];for(let a=0;a<vd.numCoordinates;a++){let o=e[a*3],i=e[a*3+1],l=e[a*3+2];r.push([(s?1-o/gi:o/gi)*n[0]+t.startPoint[0],i/gi*n[1]+t.startPoint[1],l])}return{rawCoords:r,iris:r.slice(vd.index)}},NN=(e,t,n)=>{let s=e[gr[`${n}EyeUpper0`][vd.upperCenter]][2],r=e[gr[`${n}EyeLower0`][vd.lowerCenter]][2],a=(s+r)/2;return t.map((o,i)=>{let l=a;return i===2?l=s:i===4&&(l=r),[o[0],o[1],l]})};async function RN(e,t,n,s){if(!Ea)return n.debug&&ie("face mesh iris detection requested, but model is not loaded"),e;let{box:r,boxSize:a,crop:o}=CN(e,t,bd.leftBounds[0],bd.leftBounds[1],s,!0),{box:i,boxSize:l,crop:u}=CN(e,t,bd.rightBounds[0],bd.rightBounds[1],s,!0),c=Ct([o,u]);ne(o),ne(u);let p=Ea.execute(c);ne(c);let d=await p.data();ne(p);let h=d.slice(0,vd.numCoordinates*3),{rawCoords:f,iris:m}=TN(h,r,a,!0),g=d.slice(vd.numCoordinates*3),{rawCoords:y,iris:x}=TN(g,i,l,!1),A=h5e(e);Math.abs(A)<30?(X2(e,f,"left",null),X2(e,y,"right",null)):A<1?X2(e,f,"left",["EyeUpper0","EyeLower0"]):X2(e,y,"right",["EyeUpper0","EyeLower0"]);let b=NN(e,m,"left"),w=NN(e,x,"right");return e.concat(b).concat(w)}var f5e=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],m5e=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],g5e=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],y5e=[[474,475],[475,476],[476,477],[477,474]],A5e=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],x5e=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],b5e=[[469,470],[470,471],[471,472],[472,469]],v5e=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]];function yi(e){let t=e.map(n=>n[0]);return t.push(e[e.length-1][1]),t}var w5e={lips:yi(f5e),leftEye:yi(m5e),leftEyebrow:yi(g5e),leftIris:yi(y5e),rightEye:yi(A5e),rightEyebrow:yi(x5e),rightIris:yi(b5e),faceOval:yi(v5e)},k5e=Object.entries(w5e).map(([e,t])=>t.map(n=>[n,e])).flat(),Ake=new Map(k5e),qh=[61,146,91,181,84,17,314,405,321,375,291,185,40,39,37,0,267,269,270,409,78,95,88,178,87,14,317,402,318,324,308,191,80,81,82,13,312,311,310,415,76,77,90,180,85,16,315,404,320,307,306,184,74,73,72,11,302,303,304,408,62,96,89,179,86,15,316,403,319,325,292,183,42,41,38,12,268,271,272,407],cu=[33,7,163,144,145,153,154,155,133,246,161,160,159,158,157,173,130,25,110,24,23,22,26,112,243,247,30,29,27,28,56,190,226,31,228,229,230,231,232,233,244,113,225,224,223,222,221,189,35,124,46,53,52,65,143,111,117,118,119,120,121,128,245,156,70,63,105,66,107,55,193],du=[263,249,390,373,374,380,381,382,362,466,388,387,386,385,384,398,359,255,339,254,253,252,256,341,463,467,260,259,257,258,286,414,446,261,448,449,450,451,452,453,464,342,445,444,443,442,441,413,265,353,276,283,282,295,372,340,346,347,348,349,350,357,465,383,300,293,334,296,336,285,417];async function $N(e,t){let n={lips:await t.filter(a=>a.size===160)[0].data(),irisL:await t.filter(a=>a.size===10)[0].data(),eyeL:await t.filter(a=>a.size===142)[0].data(),irisR:await t.filter(a=>a.size===10)[1].data(),eyeR:await t.filter(a=>a.size===142)[1].data()},s=cu.reduce((a,o)=>a+=e[o][2],0)/cu.length;for(let a=0;a<n.irisL.length/2;a++)e.push([n.irisL[2*a+0],n.irisL[2*a+1],s]);let r=du.reduce((a,o)=>a+=e[o][2],0)/du.length;for(let a=0;a<n.irisR.length/2;a++)e.push([n.irisR[2*a+0],n.irisR[2*a+1],r]);for(let a=0;a<n.eyeL.length/2;a++)e[cu[a]]=[n.eyeL[2*a+0],n.eyeL[2*a+1],e[cu[a]][2]];for(let a=0;a<n.eyeR.length/2;a++)e[du[a]]=[n.eyeR[2*a+0],n.eyeR[2*a+1],e[du[a]][2]];for(let a=0;a<n.lips.length/2;a++)e[qh[a]]=[n.lips[2*a+0],n.lips[2*a+1],e[qh[a]][2]];return e}var ea={boxes:[],skipped:Number.MAX_SAFE_INTEGER,timestamp:0},Bn=null,pu=0;async function PN(e,t){var i,l,u,c,p,d,h,f,m,g,y;let n=(((i=t.face.detector)==null?void 0:i.skipTime)||0)>ue()-ea.timestamp,s=ea.skipped<(((l=t.face.detector)==null?void 0:l.skipFrames)||0);!t.skipAllowed||!n||!s||ea.boxes.length===0?(ea.boxes=await eN(e,t),ea.timestamp=ue(),ea.skipped=0):ea.skipped++;let r=[],a=[],o=0;for(let x=0;x<ea.boxes.length;x++){let A=ea.boxes[x],b=0,w,k={id:o++,mesh:[],meshRaw:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,boxScore:0,faceScore:0,annotations:{}};if([b,w,k.tensor]=KT((u=t.face.detector)==null?void 0:u.rotation,A,e,(c=t.face.mesh)!=null&&c.enabled?pu:yd()),(p=t==null?void 0:t.filter)!=null&&p.equalization){let S=await R2(k.tensor);ne(k.tensor),k.tensor=S}if(k.boxScore=Math.round(100*A.confidence)/100,(d=t.face.mesh)!=null&&d.enabled)if(!Bn)t.debug&&ie("face mesh detection requested, but model is not loaded");else{let S=Bn.execute(k.tensor),R=await S.find(P=>P.shape[P.shape.length-1]===1).data();if(k.faceScore=Math.round(100*R[0])/100,k.faceScore<(((h=t.face.detector)==null?void 0:h.minConfidence)||1)){if(A.confidence=k.faceScore,(f=t.face.mesh)!=null&&f.keepInvalid){k.box=M2(A,e),k.boxRaw=z2(A,e),k.score=k.boxScore,k.mesh=A.landmarks.map(P=>[(A.startPoint[0]+A.endPoint[0])/2+(A.endPoint[0]+A.startPoint[0])*P[0]/yd(),(A.startPoint[1]+A.endPoint[1])/2+(A.endPoint[1]+A.startPoint[1])*P[1]/yd()]),k.meshRaw=k.mesh.map(P=>[P[0]/(e.shape[2]||1),P[1]/(e.shape[1]||1),(P[2]||0)/pu]);for(let P of Object.keys(ou))k.annotations[P]=[k.mesh[ou[P]]]}}else{let P=S.find(F=>F.shape[F.shape.length-1]===1404),_=U(P,[-1,3]),$=await _.array();ne(_),(m=t.face.attention)!=null&&m.enabled?$=await $N($,S):(g=t.face.iris)!=null&&g.enabled&&($=await RN($,k.tensor,t,pu)),k.mesh=XT($,A,b,w,pu),k.meshRaw=k.mesh.map(F=>[F[0]/(e.shape[2]||0),F[1]/(e.shape[1]||0),(F[2]||0)/pu]);for(let F of Object.keys(gr))k.annotations[F]=gr[F].map(G=>k.mesh[G]);k.score=k.faceScore;let T={...ZT(k.mesh,A),confidence:A.confidence,landmarks:A.landmarks};k.box=M2(T,e),k.boxRaw=z2(T,e),a.push(T)}ne(S)}else{k.box=M2(A,e),k.boxRaw=z2(A,e),k.score=k.boxScore,k.mesh=A.landmarks.map(S=>[(A.startPoint[0]+A.endPoint[0])/2+(A.endPoint[0]+A.startPoint[0])*S[0]/yd(),(A.startPoint[1]+A.endPoint[1])/2+(A.endPoint[1]+A.startPoint[1])*S[1]/yd()]),k.meshRaw=k.mesh.map(S=>[S[0]/(e.shape[2]||0),S[1]/(e.shape[1]||0),(S[2]||0)/pu]);for(let S of Object.keys(ou))k.annotations[S]=[k.mesh[ou[S]]]}k.score>(((y=t.face.detector)==null?void 0:y.minConfidence)||1)?r.push(k):ne(k.tensor)}return ea.boxes=a,r}async function FN(e){var t,n,s,r,a,o;return fe.initial&&(Bn=null),((n=(t=e==null?void 0:e.face)==null?void 0:t.attention)==null?void 0:n.enabled)&&(Bn==null?void 0:Bn.signature)&&Object.keys(((s=Bn==null?void 0:Bn.signature)==null?void 0:s.outputs)||{}).length<6&&(Bn=null),Bn?e.debug&&ie("cached model:",Bn.modelUrl):(r=e.face.attention)!=null&&r.enabled?Bn=await qe((a=e.face.attention)==null?void 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s={};s.reshape=U(t,[-1,7,2]),s.div=pe(s.reshape,this.inputSizeTensor),s.landmarks=ce(s.div,this.anchors[n]);let r=L(s.landmarks,this.inputSizeTensor);return Object.keys(s).forEach(a=>ne(s[a])),r}async predict(t,n){let s={};s.resize=Ne.resizeBilinear(t,[this.inputSize,this.inputSize]),s.div=pe(s.resize,nt.tf127),s.image=he(s.div,nt.tf1),s.batched=this.model.execute(s.image),s.predictions=rt(s.batched),s.slice=Oe(s.predictions,[0,0],[-1,1]),s.sigmoid=Cn(s.slice),s.scores=rt(s.sigmoid);let r=await s.scores.data();s.boxes=Oe(s.predictions,[0,1],[-1,4]),s.norm=this.normalizeBoxes(s.boxes),s.nms=await Ne.nonMaxSuppressionAsync(s.norm,s.scores,3*n.hand.maxDetected,n.hand.iouThreshold,n.hand.minConfidence);let a=await s.nms.array(),o=[];for(let i of a){let l={};l.box=Oe(s.norm,[i,0],[1,-1]),l.slice=Oe(s.predictions,[i,5],[1,14]),l.norm=this.normalizeLandmarks(l.slice,i),l.palmLandmarks=U(l.norm,[-1,2]);let u=await l.box.data(),c=u.slice(0,2),p=u.slice(2,4),d=await l.palmLandmarks.array(),h={startPoint:c,endPoint:p,palmLandmarks:d,confidence:r[i]},f=GN(h,[t.shape[2]/this.inputSize,t.shape[1]/this.inputSize]);o.push(f),Object.keys(l).forEach(m=>ne(l[m]))}return Object.keys(s).forEach(i=>ne(s[i])),o}};var E5e=5,KN=1.65,ZN=[0,5,9,13,17,1,2],R5e=0,_5e=2,YN=0,e1=class{constructor(t,n){me(this,"handDetector");me(this,"handPoseModel");me(this,"inputSize");me(this,"storedBoxes");me(this,"skipped");me(this,"detectedHands");this.handDetector=t,this.handPoseModel=n,this.inputSize=this.handPoseModel&&this.handPoseModel.inputs[0].shape?this.handPoseModel.inputs[0].shape[2]:0,this.storedBoxes=[],this.skipped=Number.MAX_SAFE_INTEGER,this.detectedHands=0}calculateLandmarksBoundingBox(t){let n=t.map(o=>o[0]),s=t.map(o=>o[1]),r=[Math.min(...n),Math.min(...s)],a=[Math.max(...n),Math.max(...s)];return{startPoint:r,endPoint:a}}getBoxForPalmLandmarks(t,n){let s=t.map(a=>Qb([...a,1],n)),r=this.calculateLandmarksBoundingBox(s);return Y2(J2(r),E5e)}getBoxForHandLandmarks(t){let n=this.calculateLandmarksBoundingBox(t),s=Y2(J2(n),KN);s.palmLandmarks=[];for(let r=0;r<ZN.length;r++)s.palmLandmarks.push(t[ZN[r]].slice(0,2));return s}transformRawCoords(t,n,s,r){let a=Z2(n),o=[a[0]/this.inputSize,a[1]/this.inputSize,(a[0]+a[1])/this.inputSize/2],i=t.map(h=>[o[0]*(h[0]-this.inputSize/2),o[1]*(h[1]-this.inputSize/2),o[2]*h[2]]),l=Jb(s,[0,0]),u=i.map(h=>[...Qb(h,l),h[2]]),c=jN(r),p=[...Xh(n),1],d=[Ai(p,c[0]),Ai(p,c[1])];return u.map(h=>[Math.trunc(h[0]+d[0]),Math.trunc(h[1]+d[1]),Math.trunc(h[2])])}async estimateHands(t,n){let s=!1,r,a=(n.hand.skipTime||0)>ue()-YN,o=this.skipped<(n.hand.skipFrames||0);n.skipAllowed&&a&&o&&(r=await this.handDetector.predict(t,n),this.skipped=0),n.skipAllowed&&this.skipped++,r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==n.hand.maxDetected||!n.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(s=!0));let i=[];for(let l=0;l<this.storedBoxes.length;l++){let u=this.storedBoxes[l];if(!!u)if(n.hand.landmarks){let c=n.hand.rotation?HN(u.palmLandmarks[R5e],u.palmLandmarks[_5e]):0,p=Xh(u),d=[p[0]/t.shape[2],p[1]/t.shape[1]],h=n.hand.rotation&&fe.kernels.includes("rotatewithoffset")?Ne.rotateWithOffset(t,c,0,d):t.clone(),f=Jb(-c,p),m=s?this.getBoxForPalmLandmarks(u.palmLandmarks,f):u,g=UN(m,h,[this.inputSize,this.inputSize]),y=pe(g,nt.tf255);ne(g),ne(h);let[x,A]=this.handPoseModel.execute(y);YN=ue(),ne(y);let b=(await x.data())[0];if(ne(x),b>=n.hand.minConfidence/4){let w=U(A,[-1,3]),k=await w.array();ne(A),ne(w);let S=this.transformRawCoords(k,m,c,f),E=this.getBoxForHandLandmarks(S);this.storedBoxes[l]={...E,confidence:b};let R={landmarks:S,confidence:b,boxConfidence:u.confidence,fingerConfidence:b,box:{topLeft:E.startPoint,bottomRight:E.endPoint}};i.push(R)}else this.storedBoxes[l]=null;ne(A)}else{let c=Y2(J2(u),KN),p={confidence:u.confidence,boxConfidence:u.confidence,fingerConfidence:0,box:{topLeft:c.startPoint,bottomRight:c.endPoint},landmarks:[]};i.push(p)}}return this.storedBoxes=this.storedBoxes.filter(l=>l!==null),this.detectedHands=i.length,i.length>n.hand.maxDetected&&(i.length=n.hand.maxDetected),i}};var cs={thumb:0,index:1,middle:2,ring:3,pinky:4,all:[0,1,2,3,4],nameMapping:{0:"thumb",1:"index",2:"middle",3:"ring",4:"pinky"},pointsMapping:{0:[[0,1],[1,2],[2,3],[3,4]],1:[[0,5],[5,6],[6,7],[7,8]],2:[[0,9],[9,10],[10,11],[11,12]],3:[[0,13],[13,14],[14,15],[15,16]],4:[[0,17],[17,18],[18,19],[19,20]]},getName:e=>cs.nameMapping[e],getPoints:e=>cs.pointsMapping[e]},bi={none:0,half:1,full:2,nameMapping:{0:"none",1:"half",2:"full"},getName:e=>bi.nameMapping[e]},jt={verticalUp:0,verticalDown:1,horizontalLeft:2,horizontalRight:3,diagonalUpRight:4,diagonalUpLeft:5,diagonalDownRight:6,diagonalDownLeft:7,nameMapping:{0:"verticalUp",1:"verticalDown",2:"horizontalLeft",3:"horizontalRight",4:"diagonalUpRight",5:"diagonalUpLeft",6:"diagonalDownRight",7:"diagonalDownLeft"},getName:e=>jt.nameMapping[e]},xi=class{constructor(t){me(this,"name");me(this,"curls");me(this,"directions");me(this,"weights");me(this,"weightsRelative");this.name=t,this.curls={},this.directions={},this.weights=[1,1,1,1,1],this.weightsRelative=[1,1,1,1,1]}curl(t,n,s){typeof this.curls[t]=="undefined"&&(this.curls[t]=[]),this.curls[t].push([n,s])}direction(t,n,s){this.directions[t]||(this.directions[t]=[]),this.directions[t].push([n,s])}weight(t,n){this.weights[t]=n;let s=this.weights.reduce((r,a)=>r+a,0);this.weightsRelative=this.weights.map(r=>r*5/s)}matchAgainst(t,n){let s=0;for(let r in t){let a=t[r],o=this.curls[r];if(typeof o=="undefined"){s+=this.weightsRelative[r];continue}for(let[i,l]of o)if(a===i){s+=l*this.weightsRelative[r];break}}for(let r in n){let a=n[r],o=this.directions[r];if(typeof o=="undefined"){s+=this.weightsRelative[r];continue}for(let[i,l]of o)if(a===i){s+=l*this.weightsRelative[r];break}}return s/10}};var{thumb:Or,index:Ra,middle:_a,ring:hu,pinky:fu}=cs,{none:Mr,half:$5e,full:zr}=bi,{verticalUp:wd,verticalDown:$ke,horizontalLeft:e4,horizontalRight:P5e,diagonalUpRight:F5e,diagonalUpLeft:kd,diagonalDownRight:Pke,diagonalDownLeft:Fke}=jt,vi=new xi("thumbs up");vi.curl(Or,Mr,1);vi.direction(Or,wd,1);vi.direction(Or,kd,.25);vi.direction(Or,F5e,.25);for(let e of[cs.index,cs.middle,cs.ring,cs.pinky])vi.curl(e,zr,1),vi.direction(e,e4,1),vi.direction(e,P5e,1);var dn=new xi("victory");dn.curl(Or,$5e,.5);dn.curl(Or,Mr,.5);dn.direction(Or,wd,1);dn.direction(Or,kd,1);dn.curl(Ra,Mr,1);dn.direction(Ra,wd,.75);dn.direction(Ra,kd,1);dn.curl(_a,Mr,1);dn.direction(_a,wd,1);dn.direction(_a,kd,.75);dn.curl(hu,zr,1);dn.direction(hu,wd,.2);dn.direction(hu,kd,1);dn.direction(hu,e4,.2);dn.curl(fu,zr,1);dn.direction(fu,wd,.2);dn.direction(fu,kd,1);dn.direction(fu,e4,.2);dn.weight(Ra,2);dn.weight(_a,2);var wi=new xi("point");wi.curl(Or,zr,1);wi.curl(Ra,Mr,.5);wi.curl(_a,zr,.5);wi.curl(hu,zr,.5);wi.curl(fu,zr,.5);wi.weight(Ra,2);wi.weight(_a,2);var ki=new xi("middle finger");ki.curl(Or,Mr,1);ki.curl(Ra,zr,.5);ki.curl(_a,zr,.5);ki.curl(hu,zr,.5);ki.curl(fu,zr,.5);ki.weight(Ra,2);ki.weight(_a,2);var Id=new xi("open palm");Id.curl(Or,Mr,.75);Id.curl(Ra,Mr,.75);Id.curl(_a,Mr,.75);Id.curl(hu,Mr,.75);Id.curl(fu,Mr,.75);var JN=[vi,dn,wi,ki,Id];var O5e=.7,mu={HALF_CURL_START_LIMIT:60,NO_CURL_START_LIMIT:130,DISTANCE_VOTE_POWER:1.1,SINGLE_ANGLE_VOTE_POWER:.9,TOTAL_ANGLE_VOTE_POWER:1.6};function QN(e,t,n,s){let r=(t-s)/(e-n),a=Math.atan(r)*180/Math.PI;return a<=0?a=-a:a>0&&(a=180-a),a}function tE(e,t){if(!e||!t)return[0,0];let n=QN(e[0],e[1],t[0],t[1]);if(e.length===2)return n;let s=QN(e[1],e[2],t[1],t[2]);return[n,s]}function eE(e,t=1){let n=0,s=0,r=0;return e>=75&&e<=105?n=1*t:e>=25&&e<=155?s=1*t:r=1*t,[n,s,r]}function M5e(e,t,n){let s=e[0]-t[0],r=e[0]-n[0],a=t[0]-n[0],o=e[1]-t[1],i=e[1]-n[1],l=t[1]-n[1],u=e[2]-t[2],c=e[2]-n[2],p=t[2]-n[2],d=Math.sqrt(s*s+o*o+u*u),h=Math.sqrt(r*r+i*i+c*c),f=Math.sqrt(a*a+l*l+p*p),m=(f*f+d*d-h*h)/(2*f*d);m>1?m=1:m<-1&&(m=-1);let g=Math.acos(m);g=57.2958*g%180;let y;return g>mu.NO_CURL_START_LIMIT?y=bi.none:g>mu.HALF_CURL_START_LIMIT?y=bi.half:y=bi.full,y}function nE(e,t,n,s){let r;return s===Math.abs(e)?e>0?r=jt.horizontalLeft:r=jt.horizontalRight:s===Math.abs(t)?t>0?r=jt.horizontalLeft:r=jt.horizontalRight:n>0?r=jt.horizontalLeft:r=jt.horizontalRight,r}function sE(e,t,n,s){let r;return s===Math.abs(e)?e<0?r=jt.verticalDown:r=jt.verticalUp:s===Math.abs(t)?t<0?r=jt.verticalDown:r=jt.verticalUp:n<0?r=jt.verticalDown:r=jt.verticalUp,r}function z5e(e,t,n,s,r,a,o,i){let l,u=sE(e,t,n,s),c=nE(r,a,o,i);return u===jt.verticalUp?c===jt.horizontalLeft?l=jt.diagonalUpLeft:l=jt.diagonalUpRight:c===jt.horizontalLeft?l=jt.diagonalDownLeft:l=jt.diagonalDownRight,l}function L5e(e,t,n,s){let r=e[0]-t[0],a=e[0]-n[0],o=t[0]-n[0],i=e[1]-t[1],l=e[1]-n[1],u=t[1]-n[1],c=Math.max(Math.abs(r),Math.abs(a),Math.abs(o)),p=Math.max(Math.abs(i),Math.abs(l),Math.abs(u)),d=0,h=0,f=0,m=p/(c+1e-5);m>1.5?d+=mu.DISTANCE_VOTE_POWER:m>.66?h+=mu.DISTANCE_VOTE_POWER:f+=mu.DISTANCE_VOTE_POWER;let g=Math.sqrt(r*r+i*i),y=Math.sqrt(a*a+l*l),x=Math.sqrt(o*o+u*u),A=Math.max(g,y,x),b=e[0],w=e[1],k=n[0],S=n[1];A===g?(k=n[0],S=n[1]):A===x&&(b=t[0],w=t[1]);let P=tE([b,w],[k,S]),_=eE(P,mu.TOTAL_ANGLE_VOTE_POWER);d+=_[0],h+=_[1],f+=_[2];for(let T of s){let F=eE(T,mu.SINGLE_ANGLE_VOTE_POWER);d+=F[0],h+=F[1],f+=F[2]}let $;return d===Math.max(d,h,f)?$=sE(l,i,u,p):f===Math.max(h,f)?$=nE(a,r,o,c):$=z5e(l,i,u,p,a,r,o,c),$}function rE(e){let t=[],n=[],s=[],r=[];if(!e)return{curls:s,directions:r};for(let a of cs.all){let o=cs.getPoints(a),i=[],l=[];for(let u of o){let c=e[u[0]],p=e[u[1]],d=tE(c,p),h=d[0],f=d[1];i.push(h),l.push(f)}t.push(i),n.push(l)}for(let a of cs.all){let o=a===cs.thumb?1:0,i=cs.getPoints(a),l=e[i[o][0]],u=e[i[o+1][1]],c=e[i[3][1]],p=M5e(l,u,c),d=L5e(l,u,c,t[a].slice(o));s[a]=p,r[a]=d}return{curls:s,directions:r}}function t1(e){if(!e||e.length===0)return null;let t=rE(e),n={};for(let s of cs.all)n[cs.getName(s)]={curl:bi.getName(t.curls[s]),direction:jt.getName(t.directions[s])};return n}function aE(e){let t=[];if(!e||e.length===0)return t;let n=rE(e);for(let s of JN){let r=s.matchAgainst(n.curls,n.directions);r>=O5e&&t.push({name:s.name,confidence:r})}return t}var oE={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],palm:[0]},Sd,Cd,iE;async function n4(e,t){let n=await iE.estimateHands(e,t);if(!n)return[];let s=[];for(let r=0;r<n.length;r++){let a={};if(n[r].landmarks)for(let c of Object.keys(oE))a[c]=oE[c].map(p=>n[r].landmarks[p]);let o=n[r].landmarks,i=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],l=[0,0,0,0];if(o&&o.length>0){for(let c of o)c[0]<i[0]&&(i[0]=c[0]),c[1]<i[1]&&(i[1]=c[1]),c[0]>i[2]&&(i[2]=c[0]),c[1]>i[3]&&(i[3]=c[1]);i[2]-=i[0],i[3]-=i[1],l=[i[0]/(e.shape[2]||0),i[1]/(e.shape[1]||0),i[2]/(e.shape[2]||0),i[3]/(e.shape[1]||0)]}else i=n[r].box?[Math.trunc(Math.max(0,n[r].box.topLeft[0])),Math.trunc(Math.max(0,n[r].box.topLeft[1])),Math.trunc(Math.min(e.shape[2]||0,n[r].box.bottomRight[0])-Math.max(0,n[r].box.topLeft[0])),Math.trunc(Math.min(e.shape[1]||0,n[r].box.bottomRight[1])-Math.max(0,n[r].box.topLeft[1]))]:[0,0,0,0],l=[n[r].box.topLeft[0]/(e.shape[2]||0),n[r].box.topLeft[1]/(e.shape[1]||0),(n[r].box.bottomRight[0]-n[r].box.topLeft[0])/(e.shape[2]||0),(n[r].box.bottomRight[1]-n[r].box.topLeft[1])/(e.shape[1]||0)];let u=t1(o);s.push({id:r,score:Math.round(100*n[r].confidence)/100,boxScore:Math.round(100*n[r].boxConfidence)/100,fingerScore:Math.round(100*n[r].fingerConfidence)/100,label:"hand",box:i,boxRaw:l,keypoints:o,annotations:a,landmarks:u})}return s}async function s4(e){var n,s;fe.initial&&(Sd=null,Cd=null),!Sd||!Cd?[Sd,Cd]=await Promise.all([e.hand.enabled?qe((n=e.hand.detector)==null?void 0:n.modelPath):null,e.hand.landmarks?qe((s=e.hand.skeleton)==null?void 0:s.modelPath):null]):(e.debug&&ie("cached model:",Sd.modelUrl),e.debug&&ie("cached model:",Cd.modelUrl));let t=new Q2(Sd);return iE=new e1(t,Cd),[Sd,Cd]}var An=[null,null],B5e=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],Ii=[[0,0],[0,0]],W5e=["hand","fist","pinch","point","face","tip","pinchtip"],uE=4,cE=1.6,V5e=512,U5e=1.4,n1=Number.MAX_SAFE_INTEGER,r4=0,Da=[0,0],Jt={boxes:[],hands:[]},dE={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],base:[0],palm:[0,17,13,9,5,1,0]};async function pE(e){var t;if(fe.initial&&(An[0]=null),An[0])e.debug&&ie("cached model:",An[0].modelUrl);else{s1(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),An[0]=await qe((t=e.hand.detector)==null?void 0:t.modelPath);let n=Object.values(An[0].modelSignature.inputs);Ii[0][0]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[1].size):0,Ii[0][1]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[2].size):0}return An[0]}async function hE(e){var t;if(fe.initial&&(An[1]=null),An[1])e.debug&&ie("cached model:",An[1].modelUrl);else{An[1]=await qe((t=e.hand.skeleton)==null?void 0:t.modelPath);let n=Object.values(An[1].modelSignature.inputs);Ii[1][0]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[1].size):0,Ii[1][1]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[2].size):0}return An[1]}async function G5e(e,t){let n=[];if(!e||!An[0])return n;let s={},r=(e.shape[2]||1)/(e.shape[1]||1),a=Math.min(Math.round((e.shape[1]||0)/8)*8,V5e),o=Math.round(a*r/8)*8;s.resize=Ne.resizeBilinear(e,[a,o]),s.cast=ge(s.resize,"int32"),[s.rawScores,s.rawBoxes]=await An[0].executeAsync(s.cast,B5e),s.boxes=rt(s.rawBoxes,[0,2]),s.scores=rt(s.rawScores,[0]);let i=es(s.scores,1);ne(i[uE]),i.splice(uE,1),s.filtered=on(i,1),ne(i),s.max=mn(s.filtered,1),s.argmax=Es(s.filtered,1);let l=0;s.nms=await Ne.nonMaxSuppressionAsync(s.boxes,s.max,(t.hand.maxDetected||0)+1,t.hand.iouThreshold||0,t.hand.minConfidence||1);let u=await s.nms.data(),c=await s.max.data(),p=await s.argmax.data();for(let d of Array.from(u)){let h=Oe(s.boxes,d,1),f=await h.data();ne(h);let m=[f[1],f[0],f[3]-f[1],f[2]-f[0]],g=U2(m,U5e),y=[Math.trunc(m[0]*Da[0]),Math.trunc(m[1]*Da[1]),Math.trunc(m[2]*Da[0]),Math.trunc(m[3]*Da[1])],x=c[d],A=W5e[p[d]],b={id:l++,score:x,box:y,boxRaw:g,label:A};n.push(b)}return Object.keys(s).forEach(d=>ne(s[d])),n.sort((d,h)=>h.score-d.score),n.length>(t.hand.maxDetected||1)&&(n.length=t.hand.maxDetected||1),n}async function a4(e,t,n){let s={id:t.id,score:Math.round(100*t.score)/100,boxScore:Math.round(100*t.score)/100,fingerScore:0,box:t.box,boxRaw:t.boxRaw,label:t.label,keypoints:[],landmarks:{},annotations:{}};if(e&&An[1]&&n.hand.landmarks&&t.score>(n.hand.minConfidence||0)){let r={},a=[t.boxRaw[1],t.boxRaw[0],t.boxRaw[3]+t.boxRaw[1],t.boxRaw[2]+t.boxRaw[0]];r.crop=Ne.cropAndResize(e,[a],[0],[Ii[1][0],Ii[1][1]],"bilinear"),r.div=pe(r.crop,nt.tf255),[r.score,r.keypoints]=An[1].execute(r.div,["Identity_1","Identity"]);let o=(await r.score.data())[0],i=(100-Math.trunc(100/(1+Math.exp(o))))/100;if(i>=(n.hand.minConfidence||0)){s.fingerScore=i,r.reshaped=U(r.keypoints,[-1,3]);let c=(await r.reshaped.array()).map(p=>[p[0]/Ii[1][1],p[1]/Ii[1][0],p[2]||0]).map(p=>[p[0]*t.boxRaw[2],p[1]*t.boxRaw[3],p[2]||0]);s.keypoints=c.map(p=>[Da[0]*(p[0]+t.boxRaw[0]),Da[1]*(p[1]+t.boxRaw[1]),p[2]||0]),s.landmarks=t1(s.keypoints);for(let p of Object.keys(dE))s.annotations[p]=dE[p].map(d=>s.landmarks&&s.keypoints[d]?s.keypoints[d]:null)}Object.keys(r).forEach(l=>ne(r[l]))}return s}async function o4(e,t){var r,a;if(!An[0]||!An[1]||!((r=An[0])!=null&&r.inputs[0].shape)||!((a=An[1])!=null&&a.inputs[0].shape))return[];Da=[e.shape[2]||0,e.shape[1]||0],n1++;let n=(t.hand.skipTime||0)>ue()-r4,s=n1<(t.hand.skipFrames||0);return t.skipAllowed&&n&&s?Jt.hands:new Promise(async o=>{let i=3*(t.hand.skipTime||0)>ue()-r4,l=n1<3*(t.hand.skipFrames||0);t.skipAllowed&&Jt.hands.length===t.hand.maxDetected?Jt.hands=await Promise.all(Jt.boxes.map(c=>a4(e,c,t))):t.skipAllowed&&i&&l&&Jt.hands.length>0?Jt.hands=await Promise.all(Jt.boxes.map(c=>a4(e,c,t))):(Jt.boxes=await G5e(e,t),r4=ue(),Jt.hands=await Promise.all(Jt.boxes.map(c=>a4(e,c,t))),n1=0);let u=[...Jt.boxes];if(Jt.boxes.length=0,t.cacheSensitivity>0)for(let c=0;c<Jt.hands.length;c++){let p=rN(Jt.hands[c].keypoints,Da);if(p.box[2]/(e.shape[2]||1)>.05&&p.box[3]/(e.shape[1]||1)>.05&&Jt.hands[c].fingerScore&&Jt.hands[c].fingerScore>(t.hand.minConfidence||0)){let d=U2(p.box,cE),h=U2(p.boxRaw,cE);Jt.boxes.push({...u[c],box:d,boxRaw:h})}}for(let c=0;c<Jt.hands.length;c++){let p=Ta(Jt.hands[c].keypoints,Da);Jt.hands[c].box=p.box,Jt.hands[c].boxRaw=p.boxRaw}o(Jt.hands)})}var Wn,r1=[],i4=Number.MAX_SAFE_INTEGER,mE=0,gE=0;async function yE(e){var t;return fe.initial&&(Wn=null),Wn?e.debug&&ie("cached model:",Wn.modelUrl):Wn=await qe((t=e.face.liveness)==null?void 0:t.modelPath),Wn}async function l4(e,t,n,s){var o,i;if(!Wn)return 0;let r=(((o=t.face.liveness)==null?void 0:o.skipTime)||0)>ue()-gE,a=i4<(((i=t.face.liveness)==null?void 0:i.skipFrames)||0);return t.skipAllowed&&r&&a&&mE===s&&r1[n]?(i4++,r1[n]):(i4=0,new Promise(async l=>{let 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d=a[3*p+2];if(d>t.body.minConfidence){let h=[a[3*p+1],a[3*p+0]];i.push({part:a1[p],score:Math.round(100*d)/100,positionRaw:h,position:[Math.round((n.shape[2]||0)*h[0]),Math.round((n.shape[1]||0)*h[1])]})}}let l=Ta(i.map(p=>p.position),[n.shape[2],n.shape[1]]),u={};for(let[p,d]of Object.entries(o1)){let h=[];for(let f=0;f<d.length-1;f++){let m=i.find(y=>y.part===d[f]),g=i.find(y=>y.part===d[f+1]);m&&g&&m.score>(t.body.minConfidence||0)&&g.score>(t.body.minConfidence||0)&&h.push([m.position,g.position])}u[p]=h}let c={id:r,score:o,box:l.box,boxRaw:l.boxRaw,keypoints:[...i],annotations:u};p4(c),s.push(c)}}return s.sort((r,a)=>a.score-r.score),s.length>t.body.maxDetected&&(s.length=t.body.maxDetected),s}async function f4(e,t){if(!Ws||!(Ws!=null&&Ws.inputs[0].shape))return[];t.skipAllowed||(gu.boxes.length=0),h4++;let n=(t.body.skipTime||0)>ue()-gu.last,s=h4<(t.body.skipFrames||0);return t.skipAllowed&&n&&s?gu.bodies:new Promise(async r=>{let a={};h4=0,a.input=vE(e,i1),a.res=Ws==null?void 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${yu(e.rotation.gaze.bearing)}\xB0`)),n.length===0&&n.push("face"),t.fillStyle=gt.color;for(let s=n.length-1;s>=0;s--){let r=Math.max(e.box[0],0),a=s*gt.lineHeight+e.box[1];gt.shadowColor&&gt.shadowColor!==""&&(t.fillStyle=gt.shadowColor,t.fillText(n[s],r+5,a+16)),t.fillStyle=gt.labelColor,t.fillText(n[s],r+4,a+15)}}}function uxe(e,t){if(e.annotations&&e.annotations.leftEyeIris&&e.annotations.leftEyeIris[0]){t.strokeStyle=gt.useDepth?"rgba(255, 200, 255, 0.3)":gt.color,t.beginPath();let n=Math.abs(e.annotations.leftEyeIris[3][0]-e.annotations.leftEyeIris[1][0])/2,s=Math.abs(e.annotations.leftEyeIris[4][1]-e.annotations.leftEyeIris[2][1])/2;t.ellipse(e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1],n,s,0,0,2*Math.PI),t.stroke(),gt.fillPolygons&&(t.fillStyle=gt.useDepth?"rgba(255, 255, 200, 0.3)":gt.color,t.fill())}if(e.annotations&&e.annotations.rightEyeIris&&e.annotations.rightEyeIris[0]){t.strokeStyle=gt.useDepth?"rgba(255, 200, 255, 0.3)":gt.color,t.beginPath();let n=Math.abs(e.annotations.rightEyeIris[3][0]-e.annotations.rightEyeIris[1][0])/2,s=Math.abs(e.annotations.rightEyeIris[4][1]-e.annotations.rightEyeIris[2][1])/2;t.ellipse(e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1],n,s,0,0,2*Math.PI),t.stroke(),gt.fillPolygons&&(t.fillStyle=gt.useDepth?"rgba(255, 255, 200, 0.3)":gt.color,t.fill())}}function cxe(e,t){var n;if(gt.drawGaze&&((n=e.rotation)==null?void 0:n.angle)&&typeof Path2D!="undefined"){t.strokeStyle="pink";let s=e.box[0]+e.box[2]/2-e.box[3]*yu(e.rotation.angle.yaw)/90,r=e.box[1]+e.box[3]/2+e.box[2]*yu(e.rotation.angle.pitch)/90,a=new Path2D(`
      M ${e.box[0]+e.box[2]/2} ${e.box[1]}
      C
        ${s} ${e.box[1]},
        ${s} ${e.box[1]+e.box[3]},
        ${e.box[0]+e.box[2]/2} ${e.box[1]+e.box[3]}
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      M ${e.box[0]} ${e.box[1]+e.box[3]/2}
      C 
        ${e.box[0]} ${r},
        ${e.box[0]+e.box[2]} ${r},
        ${e.box[0]+e.box[2]} ${e.box[1]+e.box[3]/2}
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pxe(e,t){if(gt.drawPolygons&&e.mesh.length>=468){t.lineWidth=1;for(let n=0;n<iu.length/3;n++){let s=[iu[n*3+0],iu[n*3+1],iu[n*3+2]].map(r=>e.mesh[r]);T4(t,s,gt)}uxe(e,t)}}function hxe(e,t){if(gt.drawPoints&&e.mesh.length>=468)for(let n=0;n<e.mesh.length;n++)Pa(t,e.mesh[n][0],e.mesh[n][1],e.mesh[n][2],gt),gt.drawAttention&&(qh.includes(n)&&Pa(t,e.mesh[n][0],e.mesh[n][1],e.mesh[n][2]+127,gt),cu.includes(n)&&Pa(t,e.mesh[n][0],e.mesh[n][1],e.mesh[n][2]-127,gt),du.includes(n)&&Pa(t,e.mesh[n][0],e.mesh[n][1],e.mesh[n][2]-127,gt))}function fxe(e,t){gt.drawBoxes&&na(t,e.box[0],e.box[1],e.box[2],e.box[3],gt)}async function Ed(e,t,n){if(gt=Xt(Vn,n),!t||!e)return;let s=tr(e);if(!!s){s.font=gt.font,s.strokeStyle=gt.color,s.fillStyle=gt.color;for(let r of t)fxe(r,s),lxe(r,s),r.mesh&&r.mesh.length>0&&(hxe(r,s),pxe(r,s),cxe(r,s),dxe(r,s))}}async function Rd(e,t,n){var a;let s=Xt(Vn,n);if(!t||!e)return;let r=tr(e);if(!!r){r.lineJoin="round";for(let o=0;o<t.length;o++){if(r.strokeStyle=s.color,r.fillStyle=s.color,r.lineWidth=s.lineWidth,r.font=s.font,s.drawBoxes&&t[o].box&&((a=t[o].box)==null?void 0:a.length)===4&&(na(r,t[o].box[0],t[o].box[1],t[o].box[2],t[o].box[3],s),s.drawLabels&&(s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(`body ${100*t[o].score}%`,t[o].box[0]+3,1+t[o].box[1]+s.lineHeight,t[o].box[2])),r.fillStyle=s.labelColor,r.fillText(`body ${100*t[o].score}%`,t[o].box[0]+2,0+t[o].box[1]+s.lineHeight,t[o].box[2]))),s.drawPoints&&t[o].keypoints)for(let i=0;i<t[o].keypoints.length;i++)!t[o].keypoints[i].score||t[o].keypoints[i].score===0||(r.fillStyle=$a(t[o].keypoints[i].position[2],s),Pa(r,t[o].keypoints[i].position[0],t[o].keypoints[i].position[1],0,s));if(s.drawLabels&&t[o].keypoints){r.font=s.font;for(let i of t[o].keypoints)!i.score||i.score===0||(r.fillStyle=$a(i.position[2],s),r.fillText(`${i.part} ${Math.trunc(100*i.score)}%`,i.position[0]+4,i.position[1]+4))}if(s.drawPolygons&&t[o].keypoints&&t[o].annotations)for(let i of Object.values(t[o].annotations))for(let l of i)BE(r,l,s)}}}async function _d(e,t,n){let s=Xt(Vn,n);if(!t||!e)return;let r=tr(e);if(!!r){r.lineJoin="round",r.font=s.font;for(let a of t){if(s.drawBoxes&&(r.strokeStyle=s.color,r.fillStyle=s.color,na(r,a.box[0],a.box[1],a.box[2],a.box[3],s),s.drawLabels&&(s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(`hand:${Math.trunc(100*a.score)}%`,a.box[0]+3,1+a.box[1]+s.lineHeight,a.box[2])),r.fillStyle=s.labelColor,r.fillText(`hand:${Math.trunc(100*a.score)}%`,a.box[0]+2,0+a.box[1]+s.lineHeight,a.box[2])),r.stroke()),s.drawPoints&&a.keypoints&&a.keypoints.length>0)for(let o of a.keypoints)r.fillStyle=$a(o[2],s),Pa(r,o[0],o[1],0,s);if(s.drawLabels&&a.annotations){let o=(i,l)=>{if(!i||i.length===0||!i[0])return;let u=i[i.length-1][2]||-256;r.fillStyle=$a(u,s),r.fillText(l,i[i.length-1][0]+4,i[i.length-1][1]+4)};r.font=s.font,o(a.annotations.index,"index"),o(a.annotations.middle,"middle"),o(a.annotations.ring,"ring"),o(a.annotations.pinky,"pinky"),o(a.annotations.thumb,"thumb"),o(a.annotations.palm,"palm")}if(s.drawPolygons&&a.annotations){let o=i=>{if(!(!i||i.length===0||!i[0]))for(let l=0;l<i.length;l++){r.beginPath();let u=i[l][2]||0;r.strokeStyle=$a(l*u,s),r.moveTo(i[l>0?l-1:0][0],i[l>0?l-1:0][1]),r.lineTo(i[l][0],i[l][1]),r.stroke()}};r.lineWidth=s.lineWidth,o(a.annotations.index),o(a.annotations.middle),o(a.annotations.ring),o(a.annotations.pinky),o(a.annotations.thumb)}}}}async function Dd(e,t,n){let s=Xt(Vn,n);if(!t||!e)return;let r=tr(e);if(!!r){r.lineJoin="round",r.font=s.font;for(let a of t)if(s.drawBoxes){if(r.strokeStyle=s.color,r.fillStyle=s.color,na(r,a.box[0],a.box[1],a.box[2],a.box[3],s),s.drawLabels){let o=`${a.label} ${Math.round(100*a.score)}%`;s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(o,a.box[0]+3,1+a.box[1]+s.lineHeight,a.box[2])),r.fillStyle=s.labelColor,r.fillText(o,a.box[0]+2,0+a.box[1]+s.lineHeight,a.box[2])}r.stroke()}}}async function $d(e,t,n){let s=Xt(Vn,n);if(!(!t||!e)&&s.drawGestures){let r=tr(e);if(!r)return;r.font=s.font,r.fillStyle=s.color;let a=1;for(let o=0;o<t.length;o++){let i=[],l=[];if([i,l]=Object.entries(t[o]),l.length>1&&l[1].length>0){let u=i[1]>0?`#${i[1]}`:"",c=`${i[0]} ${u}: ${l[1]}`;s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(c,8,2+a*s.lineHeight)),r.fillStyle=s.labelColor,r.fillText(c,6,0+a*s.lineHeight),a+=1}}}}var E4=0;async function R4(e,t,n){let s=Xt(Vn,n);if(!t||!e)return;let r=tr(e);if(!!r){r.lineJoin="round",r.font=s.font;for(let a=0;a<t.length;a++)if(s.drawBoxes){if(r.strokeStyle=s.color,r.fillStyle=s.color,na(r,t[a].box[0],t[a].box[1],t[a].box[2],t[a].box[3],s),s.drawLabels){let o=`person #${a}`;s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(o,t[a].box[0]+3,1+t[a].box[1]+s.lineHeight,t[a].box[2])),r.fillStyle=s.labelColor,r.fillText(o,t[a].box[0]+2,0+t[a].box[1]+s.lineHeight,t[a].box[2])}r.stroke()}}}async function _4(e,t){if(!e||!t)return;let n=tr(t);!n||n.drawImage(e,0,0)}async function D4(e,t,n){if(!t||!t.performance||!t||!e)return null;let s=ue(),r=Xt(Vn,n),a=Promise.all([Ed(e,t.face,r),Rd(e,t.body,r),_d(e,t.hand,r),Dd(e,t.object,r),$d(e,t.gesture,r)]);return E4=fe.perfadd?E4+Math.round(ue()-s):Math.round(ue()-s),t.performance.draw=E4,a}var Pd=.1,P4=.5;function mxe(e,t,n){let s=!1,r=n.length-1;for(let a=0;a<n.length;r=a++)n[a].y>t!=n[r].y>t&&e<(n[r].x-n[a].x)*(t-n[a].y)/(n[r].y-n[a].y)+n[a].x&&(s=!s);return s}async function WE(e){if(!e.tensor||!e.mesh||e.mesh.length<100)return e.tensor;let t=e.tensor.shape[2]||0,n=e.tensor.shape[1]||0,s=await e.tensor.buffer(),r=[];for(let o of gr.silhouette)r.push({x:(e.mesh[o][0]-e.box[0])/e.box[2],y:(e.mesh[o][1]-e.box[1])/e.box[3]});Pd&&Pd>0&&(r=r.map(o=>({x:o.x>.5?o.x+Pd:o.x-Pd,y:o.y>.5?o.y+Pd:o.y-Pd})));for(let o=0;o<t;o++)for(let i=0;i<n;i++)mxe(o/t,i/t,r)||(s.set(P4*s.get(0,i,o,0),0,i,o,0),s.set(P4*s.get(0,i,o,1),0,i,o,1),s.set(P4*s.get(0,i,o,2),0,i,o,2));let a=s.toTensor();return ne(s),a}var yxe=e=>{let t=(p,d)=>Math.atan2(p[1]-d[1],p[0]-d[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let n=[0,-.1],s=1,r=(e.mesh[33][2]||0)>(e.mesh[263][2]||0),a=r?e.mesh[473]:e.mesh[468],o=r?[(e.mesh[133][0]+e.mesh[33][0])/2,(e.mesh[133][1]+e.mesh[33][1])/2]:[(e.mesh[263][0]+e.mesh[362][0])/2,(e.mesh[263][1]+e.mesh[362][1])/2],i=r?[e.mesh[133][0]-e.mesh[33][0],e.mesh[23][1]-e.mesh[27][1]]:[e.mesh[263][0]-e.mesh[362][0],e.mesh[253][1]-e.mesh[257][1]],l=[(o[0]-a[0])/i[0]-n[0],s*(a[1]-o[1])/i[1]-n[1]],u=Math.sqrt(l[0]*l[0]+l[1]*l[1]);return u=Math.min(u,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],l)+Math.PI/2)%Math.PI,strength:u}},VE=(e,t)=>{let n=m=>{let g=Math.sqrt(m[0]*m[0]+m[1]*m[1]+m[2]*m[2]);return m[0]/=g,m[1]/=g,m[2]/=g,m},s=(m,g)=>{let y=m[0]-g[0],x=m[1]-g[1],A=m[2]-g[2];return[y,x,A]},r=(m,g)=>{let y=m[1]*g[2]-m[2]*g[1],x=m[2]*g[0]-m[0]*g[2],A=m[0]*g[1]-m[1]*g[0];return[y,x,A]},a=m=>{let[g,y,x,A,b,w,k,S,E]=m,R,P,_;return A<1?A>-1?(_=Math.asin(A),P=Math.atan2(-k,g),R=Math.atan2(-w,b)):(_=-Math.PI/2,P=-Math.atan2(S,E),R=0):(_=Math.PI/2,P=Math.atan2(S,E),R=0),isNaN(R)&&(R=0),isNaN(P)&&(P=0),isNaN(_)&&(_=0),{pitch:2*-R,yaw:2*-P,roll:2*-_}},o=e.meshRaw;if(!o||o.length<300)return{angle:{pitch:0,yaw:0,roll:0},matrix:[1,0,0,0,1,0,0,0,1],gaze:{bearing:0,strength:0}};let i=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,l=[o[10],o[152],o[234],o[454]].map(m=>[m[0]*t[0]/i,m[1]*t[1]/i,m[2]]),u=n(s(l[1],l[0])),c=n(s(l[3],l[2])),p=n(r(c,u));c=r(u,p);let d=[c[0],c[1],c[2],u[0],u[1],u[2],p[0],p[1],p[2]],h=a(d),f=o.length===478?yxe(e):{bearing:0,strength:0};return{angle:h,matrix:d,gaze:f}};var F4=async(e,t)=>{var h,f,m,g,y,x,A,b,w,k,S,E,R,P,_,$,T,F,G,q,z,Z;let n=ue(),s,r,a,o,i,l,u,c,p=[];e.state="run:face";let d=await PN(t,e.config);if(e.performance.face=fe.perfadd?(e.performance.face||0)+Math.trunc(ue()-n):Math.trunc(ue()-n),!t.shape||t.shape.length!==4)return[];if(!d)return[];for(let B=0;B<d.length;B++){if(e.analyze("Get Face"),!d[B].tensor||d[B].tensor.isDisposedInternal){ie("Face object is disposed:",d[B].tensor);continue}if((h=e.config.face.detector)!=null&&h.mask){let ae=await WE(d[B]);ne(d[B].tensor),d[B].tensor=ae}let ee=d[B].mesh&&d[B].mesh.length>200?VE(d[B],[t.shape[2],t.shape[1]]):null;e.analyze("Start Emotion:"),e.config.async?o=(f=e.config.face.emotion)!=null&&f.enabled?Vb(d[B].tensor||ft([]),e.config,B,d.length):[]:(e.state="run:emotion",n=ue(),o=(m=e.config.face.emotion)!=null&&m.enabled?await Vb(d[B].tensor||ft([]),e.config,B,d.length):[],e.performance.emotion=fe.perfadd?(e.performance.emotion||0)+Math.trunc(ue()-n):Math.trunc(ue()-n)),e.analyze("End Emotion:"),e.analyze("Start AntiSpoof:"),e.config.async?l=(g=e.config.face.antispoof)!=null&&g.enabled?kb(d[B].tensor||ft([]),e.config,B,d.length):0:(e.state="run:antispoof",n=ue(),l=(y=e.config.face.antispoof)!=null&&y.enabled?await kb(d[B].tensor||ft([]),e.config,B,d.length):0,e.performance.antispoof=fe.perfadd?(e.performance.antispoof||0)+Math.trunc(ue()-n):Math.trunc(ue()-n)),e.analyze("End AntiSpoof:"),e.analyze("Start Liveness:"),e.config.async?u=(x=e.config.face.liveness)!=null&&x.enabled?l4(d[B].tensor||ft([]),e.config,B,d.length):0:(e.state="run:liveness",n=ue(),u=(A=e.config.face.liveness)!=null&&A.enabled?await l4(d[B].tensor||ft([]),e.config,B,d.length):0,e.performance.liveness=fe.perfadd?(e.performance.antispoof||0)+Math.trunc(ue()-n):Math.trunc(ue()-n)),e.analyze("End Liveness:"),e.analyze("Start GEAR:"),e.config.async?r=(b=e.config.face.gear)!=null&&b.enabled?gb(d[B].tensor||ft([]),e.config,B,d.length):null:(e.state="run:gear",n=ue(),r=(w=e.config.face.gear)!=null&&w.enabled?await gb(d[B].tensor||ft([]),e.config,B,d.length):null,e.performance.gear=Math.trunc(ue()-n)),e.analyze("End GEAR:"),e.analyze("Start SSRNet:"),e.config.async?(s=(k=e.config.face.ssrnet)!=null&&k.enabled?Ab(d[B].tensor||ft([]),e.config,B,d.length):null,a=(S=e.config.face.ssrnet)!=null&&S.enabled?vb(d[B].tensor||ft([]),e.config,B,d.length):null):(e.state="run:ssrnet",n=ue(),s=(E=e.config.face.ssrnet)!=null&&E.enabled?await Ab(d[B].tensor||ft([]),e.config,B,d.length):null,a=(R=e.config.face.ssrnet)!=null&&R.enabled?await vb(d[B].tensor||ft([]),e.config,B,d.length):null,e.performance.ssrnet=Math.trunc(ue()-n)),e.analyze("End SSRNet:"),e.analyze("Start MobileFaceNet:"),e.config.async?i=(P=e.config.face.mobilefacenet)!=null&&P.enabled?Gb(d[B].tensor||ft([]),e.config,B,d.length):null:(e.state="run:mobilefacenet",n=ue(),i=(_=e.config.face.mobilefacenet)!=null&&_.enabled?await Gb(d[B].tensor||ft([]),e.config,B,d.length):null,e.performance.mobilefacenet=Math.trunc(ue()-n)),e.analyze("End MobileFaceNet:"),e.analyze("Start Description:"),e.config.async?c=($=e.config.face.description)!=null&&$.enabled?Zb(d[B].tensor||ft([]),e.config,B,d.length):null:(e.state="run:description",n=ue(),c=(T=e.config.face.description)!=null&&T.enabled?await Zb(d[B].tensor||ft([]),e.config,B,d.length):null,e.performance.description=fe.perfadd?(e.performance.description||0)+Math.trunc(ue()-n):Math.trunc(ue()-n)),e.analyze("End Description:"),e.config.async&&([s,a,o,i,c,r,l,u]=await Promise.all([s,a,o,i,c,r,l,u])),e.analyze("Finish Face:"),((F=e.config.face.ssrnet)==null?void 0:F.enabled)&&s&&a&&(c={...c,age:s.age,gender:a.gender,genderScore:a.genderScore}),((G=e.config.face.gear)==null?void 0:G.enabled)&&r&&(c={...c,age:r.age,gender:r.gender,genderScore:r.genderScore,race:r.race}),((q=e.config.face.mobilefacenet)==null?void 0:q.enabled)&&i&&(c.descriptor=i),(z=e.config.face.iris)!=null&&z.enabled;let Q=d[B].annotations&&d[B].annotations.leftEyeIris&&d[B].annotations.leftEyeIris[0]&&d[B].annotations.rightEyeIris&&d[B].annotations.rightEyeIris[0]&&d[B].annotations.leftEyeIris.length>0&&d[B].annotations.rightEyeIris.length>0&&d[B].annotations.leftEyeIris[0]!==null&&d[B].annotations.rightEyeIris[0]!==null?Math.max(Math.abs(d[B].annotations.leftEyeIris[3][0]-d[B].annotations.leftEyeIris[1][0]),Math.abs(d[B].annotations.rightEyeIris[4][1]-d[B].annotations.rightEyeIris[2][1]))/t.shape[2]:0,oe=(Z=e.config.face.detector)!=null&&Z.return?rt(d[B].tensor):null;ne(d[B].tensor),d[B].tensor&&delete d[B].tensor;let Y={...d[B],id:B};c!=null&&c.age&&(Y.age=c.age),c!=null&&c.gender&&(Y.gender=c.gender),c!=null&&c.genderScore&&(Y.genderScore=c==null?void 0:c.genderScore),c!=null&&c.descriptor&&(Y.embedding=c==null?void 0:c.descriptor),c!=null&&c.race&&(Y.race=c==null?void 0:c.race),o&&(Y.emotion=o),l&&(Y.real=l),u&&(Y.live=u),Q&&Q!==0&&(Y.iris=Math.trunc(500/Q/11.7)/100),ee&&(Y.rotation=ee),oe&&(Y.tensor=oe),p.push(Y),e.analyze("End Face")}return e.analyze("End FaceMesh:"),e.config.async&&(e.performance.face&&delete e.performance.face,e.performance.age&&delete e.performance.age,e.performance.gender&&delete e.performance.gender,e.performance.emotion&&delete e.performance.emotion),p};var UE=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){let s=e[n].keypoints.find(l=>l.part==="leftWrist"),r=e[n].keypoints.find(l=>l.part==="rightWrist"),a=e[n].keypoints.find(l=>l.part==="nose");a&&s&&r&&s.position[1]<a.position[1]&&r.position[1]<a.position[1]?t.push({body:n,gesture:"i give up"}):a&&s&&s.position[1]<a.position[1]?t.push({body:n,gesture:"raise left hand"}):a&&r&&r.position[1]<a.position[1]&&t.push({body:n,gesture:"raise right hand"});let o=e[n].keypoints.find(l=>l.part==="leftShoulder"),i=e[n].keypoints.find(l=>l.part==="rightShoulder");o&&i&&Math.abs(o.positionRaw[1]-i.positionRaw[1])>.1&&t.push({body:n,gesture:`leaning ${o.position[1]>i.position[1]?"left":"right"}`})}return t},GE=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++)if(e[n].mesh&&e[n].mesh.length>450){let s=(e[n].mesh[33][2]||0)-(e[n].mesh[263][2]||0),r=e[n].mesh[33][0]-e[n].mesh[263][0];Math.abs(s/r)<=.15?t.push({face:n,gesture:"facing center"}):t.push({face:n,gesture:`facing ${s<0?"left":"right"}`}),Math.abs(e[n].mesh[374][1]-e[n].mesh[386][1])/Math.abs(e[n].mesh[443][1]-e[n].mesh[450][1])<.2&&t.push({face:n,gesture:"blink left eye"}),Math.abs(e[n].mesh[145][1]-e[n].mesh[159][1])/Math.abs(e[n].mesh[223][1]-e[n].mesh[230][1])<.2&&t.push({face:n,gesture:"blink right eye"});let i=Math.min(100,500*Math.abs(e[n].mesh[13][1]-e[n].mesh[14][1])/Math.abs(e[n].mesh[10][1]-e[n].mesh[152][1]));i>10&&t.push({face:n,gesture:`mouth ${Math.trunc(i)}% open`});let l=e[n].mesh[152][2]||0;Math.abs(l)>10&&t.push({face:n,gesture:`head ${l<0?"up":"down"}`})}return t},HE=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){if(!e[n].annotations||!e[n].annotations.leftEyeIris||!e[n].annotations.leftEyeIris[0]||!e[n].annotations.rightEyeIris||!e[n].annotations.rightEyeIris[0])continue;let s=e[n].annotations.leftEyeIris[3][0]-e[n].annotations.leftEyeIris[1][0],r=e[n].annotations.leftEyeIris[4][1]-e[n].annotations.leftEyeIris[2][1],a=Math.abs(s*r),o=e[n].annotations.rightEyeIris[3][0]-e[n].annotations.rightEyeIris[1][0],i=e[n].annotations.rightEyeIris[4][1]-e[n].annotations.rightEyeIris[2][1],l=Math.abs(o*i),u=!1;Math.abs(a-l)/Math.max(a,l)<.25&&(u=!0,t.push({iris:n,gesture:"facing center"}));let p=Math.abs(e[n].mesh[263][0]-e[n].annotations.leftEyeIris[0][0])/e[n].box[2],d=Math.abs(e[n].mesh[33][0]-e[n].annotations.rightEyeIris[0][0])/e[n].box[2];(p>.06||d>.06)&&(u=!1),p>d?p>.05&&t.push({iris:n,gesture:"looking right"}):d>.05&&t.push({iris:n,gesture:"looking left"});let h=Math.abs(e[n].mesh[145][1]-e[n].annotations.rightEyeIris[0][1])/e[n].box[3],f=Math.abs(e[n].mesh[374][1]-e[n].annotations.leftEyeIris[0][1])/e[n].box[3];(f<.01||h<.01||f>.022||h>.022)&&(u=!1),(f<.01||h<.01)&&t.push({iris:n,gesture:"looking down"}),(f>.022||h>.022)&&t.push({iris:n,gesture:"looking up"}),u&&t.push({iris:n,gesture:"looking center"})}return t},jE=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){let s=[];if(e[n].annotations)for(let[r,a]of Object.entries(e[n].annotations))r!=="palmBase"&&Array.isArray(a)&&a[0]&&s.push({name:r.toLowerCase(),position:a[0]});if(s&&s.length>0){let r=s.reduce((o,i)=>(o.position[2]||0)<(i.position[2]||0)?o:i);t.push({hand:n,gesture:`${r.name} forward`});let a=s.reduce((o,i)=>o.position[1]<i.position[1]?o:i);t.push({hand:n,gesture:`${a.name} up`})}if(e[n].keypoints){let r=aE(e[n].keypoints);for(let a of r)t.push({hand:n,gesture:a.name})}}return t};var Ee={face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null},O4=0;function qE(e,t){var o,i,l,u,c,p,d,h,f,m,g,y,x,A,b,w,k,S,E,R,P,_,$,T,F,G,q;let n=ue();if(!e)return{face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null};let s=Date.now()-e.timestamp,r=s<1e3?8-Math.log(s+1):1;if(e.canvas&&(Ee.canvas=e.canvas),e.error&&(Ee.error=e.error),!Ee.body||e.body.length!==Ee.body.length)Ee.body=JSON.parse(JSON.stringify(e.body));else for(let z=0;z<e.body.length;z++){let Z=e.body[z].box.map((Y,ae)=>((r-1)*Ee.body[z].box[ae]+Y)/r),B=e.body[z].boxRaw.map((Y,ae)=>((r-1)*Ee.body[z].boxRaw[ae]+Y)/r),ee=e.body[z].keypoints.map((Y,ae)=>{var le,ye,we,Re,_e,Be,Ge,ot,dt;return{score:Y.score,part:Y.part,position:[Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].position[0]||0)+(Y.position[0]||0))/r:Y.position[0],Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].position[1]||0)+(Y.position[1]||0))/r:Y.position[1],Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].position[2]||0)+(Y.position[2]||0))/r:Y.position[2]],positionRaw:[Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].positionRaw[0]||0)+(Y.positionRaw[0]||0))/r:Y.positionRaw[0],Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].positionRaw[1]||0)+(Y.positionRaw[1]||0))/r:Y.positionRaw[1],Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].positionRaw[2]||0)+(Y.positionRaw[2]||0))/r:Y.positionRaw[2]],distance:[Ee.body[z].keypoints[ae]?((r-1)*(((le=Ee.body[z].keypoints[ae].distance)==null?void 0:le[0])||0)+(((ye=Y.distance)==null?void 0:ye[0])||0))/r:(we=Y.distance)==null?void 0:we[0],Ee.body[z].keypoints[ae]?((r-1)*(((Re=Ee.body[z].keypoints[ae].distance)==null?void 0:Re[1])||0)+(((_e=Y.distance)==null?void 0:_e[1])||0))/r:(Be=Y.distance)==null?void 0:Be[1],Ee.body[z].keypoints[ae]?((r-1)*(((Ge=Ee.body[z].keypoints[ae].distance)==null?void 0:Ge[2])||0)+(((ot=Y.distance)==null?void 0:ot[2])||0))/r:(dt=Y.distance)==null?void 0:dt[2]]}}),Q={},oe={connected:{}};(i=(o=t.body)==null?void 0:o.modelPath)!=null&&i.includes("efficientpose")?oe=j2:(u=(l=t.body)==null?void 0:l.modelPath)!=null&&u.includes("blazepose")?oe=W2:(p=(c=t.body)==null?void 0:c.modelPath)!=null&&p.includes("movenet")&&(oe=Kh);for(let[Y,ae]of Object.entries(oe.connected)){let le=[];for(let ye=0;ye<ae.length-1;ye++){let we=ee.find(_e=>_e.part===ae[ye]),Re=ee.find(_e=>_e.part===ae[ye+1]);we&&Re&&le.push([we.position,Re.position])}Q[Y]=le}Ee.body[z]={...e.body[z],box:Z,boxRaw:B,keypoints:ee,annotations:Q}}if(!Ee.hand||e.hand.length!==Ee.hand.length)Ee.hand=JSON.parse(JSON.stringify(e.hand));else for(let z=0;z<e.hand.length;z++){let Z=e.hand[z].box.map((oe,Y)=>((r-1)*Ee.hand[z].box[Y]+oe)/r),B=e.hand[z].boxRaw.map((oe,Y)=>((r-1)*Ee.hand[z].boxRaw[Y]+oe)/r);Ee.hand[z].keypoints.length!==e.hand[z].keypoints.length&&(Ee.hand[z].keypoints=e.hand[z].keypoints);let ee=e.hand[z].keypoints&&e.hand[z].keypoints.length>0?e.hand[z].keypoints.map((oe,Y)=>oe.map((ae,le)=>((r-1)*(Ee.hand[z].keypoints[Y][le]||1)+(ae||0))/r)):[],Q={};if(Object.keys(Ee.hand[z].annotations).length!==Object.keys(e.hand[z].annotations).length)Ee.hand[z].annotations=e.hand[z].annotations,Q=Ee.hand[z].annotations;else if(e.hand[z].annotations)for(let oe of Object.keys(e.hand[z].annotations))Q[oe]=e.hand[z].annotations[oe]&&e.hand[z].annotations[oe][0]?e.hand[z].annotations[oe].map((Y,ae)=>Y.map((le,ye)=>((r-1)*Ee.hand[z].annotations[oe][ae][ye]+le)/r)):null;Ee.hand[z]={...e.hand[z],box:Z,boxRaw:B,keypoints:ee,annotations:Q}}if(!Ee.face||e.face.length!==Ee.face.length)Ee.face=JSON.parse(JSON.stringify(e.face));else for(let z=0;z<e.face.length;z++){let Z=e.face[z].box.map((ee,Q)=>((r-1)*Ee.face[z].box[Q]+ee)/r),B=e.face[z].boxRaw.map((ee,Q)=>((r-1)*Ee.face[z].boxRaw[Q]+ee)/r);if(e.face[z].rotation){let ee={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};ee.matrix=(d=e.face[z].rotation)==null?void 0:d.matrix,ee.angle={roll:((r-1)*(((f=(h=Ee.face[z].rotation)==null?void 0:h.angle)==null?void 0:f.roll)||0)+(((g=(m=e.face[z].rotation)==null?void 0:m.angle)==null?void 0:g.roll)||0))/r,yaw:((r-1)*(((x=(y=Ee.face[z].rotation)==null?void 0:y.angle)==null?void 0:x.yaw)||0)+(((b=(A=e.face[z].rotation)==null?void 0:A.angle)==null?void 0:b.yaw)||0))/r,pitch:((r-1)*(((k=(w=Ee.face[z].rotation)==null?void 0:w.angle)==null?void 0:k.pitch)||0)+(((E=(S=e.face[z].rotation)==null?void 0:S.angle)==null?void 0:E.pitch)||0))/r},ee.gaze={bearing:((r-1)*(((P=(R=Ee.face[z].rotation)==null?void 0:R.gaze)==null?void 0:P.bearing)||0)+((($=(_=e.face[z].rotation)==null?void 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O4=fe.perfadd?O4+Math.round(a-n):Math.round(a-n),e.performance&&(Ee.performance={...e.performance,interpolate:O4}),Ee}var L4={};oa(L4,{distance:()=>Qh,match:()=>z4,similarity:()=>M4});function Qh(e,t,n={order:2,multiplier:25}){let s=0;for(let r=0;r<e.length;r++){let a=!n.order||n.order===2?e[r]-t[r]:Math.abs(e[r]-t[r]);s+=!n.order||n.order===2?a*a:a**n.order}return(n.multiplier||20)*s}var XE=(e,t,n,s)=>{if(e===0)return 1;let r=t===2?Math.sqrt(e):e**(1/t),a=(1-r/100-n)/(s-n);return Math.max(Math.min(a,1),0)};function M4(e,t,n={order:2,multiplier:25,min:.2,max:.8}){let s=Qh(e,t,n);return XE(s,n.order||2,n.min||0,n.max||1)}function z4(e,t,n={order:2,multiplier:25,threshold:0,min:.2,max:.8}){if(!Array.isArray(e)||!Array.isArray(t)||e.length<64||t.length===0||e.length!==t[0].length)return{index:-1,distance:Number.POSITIVE_INFINITY,similarity:0};let s=Number.MAX_SAFE_INTEGER,r=-1;for(let o=0;o<t.length;o++){let i=Qh(e,t[o],n);if(i<s&&(s=i,r=o),s<(n.threshold||0))break}let 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this.performance.body):(r=ue(),(b=this.config.body.modelPath)!=null&&b.includes("posenet")?u=this.config.body.enabled?await v4(i.tensor,d):[]:(w=this.config.body.modelPath)!=null&&w.includes("blazepose")?u=this.config.body.enabled?await $b(i.tensor,d):[]:(k=this.config.body.modelPath)!=null&&k.includes("efficientpose")?u=this.config.body.enabled?await Bb(i.tensor,d):[]:(S=this.config.body.modelPath)!=null&&S.includes("movenet")&&(u=this.config.body.enabled?await f4(i.tensor,d):[]),this.performance.body=this.env.perfadd?(this.performance.body||0)+Math.trunc(ue()-r):Math.trunc(ue()-r)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.state="detect:hand";let h=this.config.hand.maxDetected===-1?Xt(this.config,{hand:{maxDetected:this.config.face.enabled?2*l.length:1}}):this.config;this.config.async?((R=(E=this.config.hand.detector)==null?void 0:E.modelPath)!=null&&R.includes("handdetect")?c=this.config.hand.enabled?n4(i.tensor,h):[]:(_=(P=this.config.hand.detector)==null?void 0:P.modelPath)!=null&&_.includes("handtrack")&&(c=this.config.hand.enabled?o4(i.tensor,h):[]),this.performance.hand&&delete this.performance.hand):(r=ue(),(T=($=this.config.hand.detector)==null?void 0:$.modelPath)!=null&&T.includes("handdetect")?c=this.config.hand.enabled?await n4(i.tensor,h):[]:(G=(F=this.config.hand.detector)==null?void 0:F.modelPath)!=null&&G.includes("handtrack")&&(c=this.config.hand.enabled?await o4(i.tensor,h):[]),this.performance.hand=this.env.perfadd?(this.performance.hand||0)+Math.trunc(ue()-r):Math.trunc(ue()-r)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.state="detect:object",this.config.async?((q=this.config.object.modelPath)!=null&&q.includes("nanodet")?p=this.config.object.enabled?g4(i.tensor,this.config):[]:(z=this.config.object.modelPath)!=null&&z.includes("centernet")&&(p=this.config.object.enabled?Ob(i.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(r=ue(),(Z=this.config.object.modelPath)!=null&&Z.includes("nanodet")?p=this.config.object.enabled?await g4(i.tensor,this.config):[]:(B=this.config.object.modelPath)!=null&&B.includes("centernet")&&(p=this.config.object.enabled?await Ob(i.tensor,this.config):[]),this.performance.object=this.env.perfadd?(this.performance.object||0)+Math.trunc(ue()-r):Math.trunc(ue()-r)),this.analyze("End Object:"),this.state="detect:await",this.config.async&&([l,u,c,p]=await Promise.all([l,u,c,p])),this.state="detect:gesture";let f=[];this.config.gesture.enabled&&(r=ue(),f=[...GE(l),...UE(u),...jE(c),...HE(l)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=this.env.perfadd?(this.performance.gesture||0)+Math.trunc(ue()-r):Math.trunc(ue()-r)),this.performance.total=this.env.perfadd?(this.performance.total||0)+Math.trunc(ue()-o):Math.trunc(ue()-o);let m=((Q=(ee=this.process)==null?void 0:ee.tensor)==null?void 0:Q.shape)||[];this.result={face:l,body:u,hand:c,gesture:f,object:p,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,get persons(){return KE(l,u,c,f,m)}},ne(i.tensor),this.emit("detect"),this.state="idle",s(this.result)})}};Fd=new WeakMap,ef=new WeakMap,tf=new WeakMap,A1=new WeakMap;return KR(Exe);})();