human/dist/human.js

/*
  Human
  homepage: <https://github.com/vladmandic/human>
  author: <https://github.com/vladmandic>'
*/

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To get the original bytes, call tensor.bytes().")}return e}async bytes(){this.throwIfDisposed();let e=await Pr().read(this.dataId);return this.dtype==="string"?e:new Uint8Array(e.buffer)}dispose(){this.isDisposed||(Pr().disposeTensor(this),this.isDisposedInternal=!0)}get isDisposed(){return this.isDisposedInternal}throwIfDisposed(){if(this.isDisposed)throw new Error("Tensor is disposed.")}print(e=!1){return tc.print(this,e)}clone(){return this.throwIfDisposed(),tc.clone(this)}toString(e=!1){let t=this.dataSync();return jD(t,this.shape,this.dtype,e)}cast(e){return this.throwIfDisposed(),tc.cast(this,e)}variable(e=!0,t,n){return this.throwIfDisposed(),Pr().makeVariable(this,e,t,n)}};Object.defineProperty(it,Symbol.hasInstance,{value:e=>!!e&&e.data!=null&&e.dataSync!=null&&e.throwIfDisposed!=null});function oe(){return Vy("Tensor",()=>it)}oe();var Np=class extends it{constructor(e,t,n,s){super(e.shape,e.dtype,e.dataId,s),this.trainable=t,this.name=n}assign(e){if(e.dtype!==this.dtype)throw new Error(`dtype of the new value (${e.dtype}) and previous value (${this.dtype}) must match`);if(!Ao(e.shape,this.shape))throw new Error(`shape of the new value (${e.shape}) and previous value (${this.shape}) must match`);Pr().disposeTensor(this),this.dataId=e.dataId,Pr().incRef(this,null)}dispose(){Pr().disposeVariable(this),this.isDisposedInternal=!0}};Object.defineProperty(Np,Symbol.hasInstance,{value:e=>e instanceof it&&e.assign!=null&&e.assign instanceof Function});var zr={};qe(zr,{assertTypesMatch:()=>W6,getTensorsInContainer:()=>Gy,isTensorInList:()=>QD,makeTypesMatch:()=>Xt});var F3;(function(e){e.R0="R0",e.R1="R1",e.R2="R2",e.R3="R3",e.R4="R4",e.R5="R5",e.R6="R6"})(F3||(F3={}));var O3;(function(e){e.float32="float32",e.int32="int32",e.bool="int32",e.complex64="complex64"})(O3||(O3={}));var M3;(function(e){e.float32="float32",e.int32="int32",e.bool="bool",e.complex64="complex64"})(M3||(M3={}));var z3;(function(e){e.float32="float32",e.int32="float32",e.bool="float32",e.complex64="complex64"})(z3||(z3={}));var L3;(function(e){e.float32="complex64",e.int32="complex64",e.bool="complex64",e.complex64="complex64"})(L3||(L3={}));var JD={float32:z3,int32:O3,bool:M3,complex64:L3};function Hn(e,t){if(e==="string"||t==="string"){if(e==="string"&&t==="string")return"string";throw new Error(`Can not upcast ${e} with ${t}`)}return JD[e][t]}function ch(e){return Hn(e,"int32")}function Xt(e,t){if(e.dtype===t.dtype)return[e,t];let n=Hn(e.dtype,t.dtype);return[e.cast(n),t.cast(n)]}function W6(e,t){O(e.dtype===t.dtype,()=>`The dtypes of the first(${e.dtype}) and second(${t.dtype}) input must match`)}function QD(e,t){return t.some(n=>n.id===e.id)}function Gy(e){let t=[];return V6(e,t,new Set),t}function V6(e,t,n){if(e==null)return;if(e instanceof it){t.push(e);return}if(!e$(e))return;let s=e;for(let r in s){let a=s[r];n.has(a)||(n.add(a),V6(a,t,n))}}function e$(e){return Array.isArray(e)||typeof e=="object"}function x3(e){return e.kernelName!=null}var Ov=class{constructor(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null,get kernelNames(){return Array.from(new Set(this.kernels.map(e=>e.name)))}}}dispose(){for(let e in this.registeredVariables)this.registeredVariables[e].dispose()}},Ep=class{constructor(e){this.ENV=e,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new Ov}async ready(){if(this.pendingBackendInit!=null)return this.pendingBackendInit.then(()=>{});if(this.backendInstance!=null)return;let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let n=e[t];if(await this.initializeBackend(n).success){await this.setBackend(n);return}}throw new Error("Could not initialize any backends, all backend initializations failed.")}get backend(){if(this.pendingBackendInit!=null)throw new Error(`Backend '${this.backendName}' has not yet been initialized. 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Reusing existing backend factory.`),!1):(this.registryFactory[e]={factory:t,priority:n},!0)}async setBackend(e){if(this.registryFactory[e]==null)throw new Error(`Backend name '${e}' not found in registry`);if(this.backendName=e,this.registry[e]==null){this.backendInstance=null;let{success:t,asyncInit:n}=this.initializeBackend(e);if(!(n?await t:t))return!1}return this.backendInstance=this.registry[e],this.setupRegisteredKernels(),this.profiler=new WD(this.backendInstance),!0}setupRegisteredKernels(){ra(this.backendName).forEach(t=>{t.setupFunc!=null&&t.setupFunc(this.backendInstance)})}disposeRegisteredKernels(e){ra(e).forEach(n=>{n.disposeFunc!=null&&n.disposeFunc(this.registry[e])})}initializeBackend(e){let t=this.registryFactory[e];if(t==null)throw new Error(`Cannot initialize backend ${e}, no registration found.`);try{let n=t.factory();if(n&&!(n instanceof Cc)&&typeof n.then=="function"){let s=++this.pendingBackendInitId,r=n.then(a=>s<this.pendingBackendInitId?!1:(this.registry[e]=a,this.pendingBackendInit=null,!0)).catch(a=>(s<this.pendingBackendInitId||(this.pendingBackendInit=null,Ya(`Initialization of backend ${e} failed`),Ya(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 Ya(`Initialization of backend ${e} failed`),Ya(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw new Error(`${e} backend not found in registry`);this.backendName===e&&this.pendingBackendInit!=null&&this.pendingBackendInitId++,e in this.registry&&(this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e]),delete this.registryFactory[e],this.backendName===e&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)}getSortedBackends(){if(Object.keys(this.registryFactory).length===0)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((e,t)=>this.registryFactory[t].priority-this.registryFactory[e].priority)}initializeBackendsAndReturnBest(){let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let n=e[t],{success:s,asyncInit:r}=this.initializeBackend(n);if(r||s)return{name:n,asyncInit:r}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){let n=this.state.tensorInfo.get(t),s=n.backend,r=this.readSync(t),a=s.refCount(t);s.disposeData(t,!0),n.backend=e,e.move(t,r,n.shape,n.dtype,a),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(e,t){let n=null;if(t==null){if(typeof e!="function")throw new Error("Please provide a function to tidy()");t=e}else{if(typeof e!="string"&&!(e instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if(typeof t!="function")throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");n=e}let s;return this.scopedRun(()=>this.startScope(n),()=>this.endScope(s),()=>(s=t(),s instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),s))}scopedRun(e,t,n){e();try{let s=n();return t(),s}catch(s){throw t(),s}}nextTensorId(){return Ep.nextTensorId++}nextVariableId(){return Ep.nextVariableId++}clone(e){let t=B.runKernel(zo,{x:e}),n={x:e},s=a=>({x:()=>{let o="float32",i={x:a},l={dtype:o};return B.runKernel(ko,i,l)}}),r=[];return this.addTapeNode(this.state.activeScope.name,n,[t],s,r,{}),t}runKernel(e,t,n){if(this.backendName==null&&this.backend,!(Cm(e,this.backendName)!=null))throw new Error(`Kernel '${e}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,n){let s=this.backend.numDataIds(),r=0;n.forEach(i=>{r+=i.dtype==="complex64"?3:1});let a=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],o=s-t-r-a;if(o>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${o} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[],s=this.isTapeOn(),r=this.state.numBytes,a=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let o;this.backendName==null&&this.backend;let i,l=x3(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(x3(e)){let{kernelName:h,inputs:f,attrs:m}=e;this.backendName==null&&this.backend;let g=Cm(h,this.backendName);O(g!=null,()=>`Cannot find registered kernel '${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=x3(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=$3(e);if(s!=null){let r=s.inputsToSave||[],a=s.outputsToSave||[],o;s.saveAllInputs?(O(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),o=Object.keys(t).map(l=>t[l])):o=r.map(l=>t[l]);let i=n.filter((l,u)=>a[u]);return o.concat(i)}return[]}makeTensor(e,t,n,s){if(e==null)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",s=s||this.backend;let r=e;n==="string"&&Ja(e[0])&&(r=e.map(i=>uh(i)));let a=s.write(r,t,n),o=new it(t,n,a,this.nextTensorId());if(this.trackTensor(o,s),n==="string"){let i=this.state.tensorInfo.get(a),l=N6(r);this.state.numBytes+=l-i.bytes,i.bytes=l}return o}makeTensorFromDataId(e,t,n,s){n=n||"float32";let r={dataId:e,shape:t,dtype:n};return this.makeTensorFromTensorInfo(r,s)}makeTensorFromTensorInfo(e,t){let{dataId:n,shape:s,dtype:r}=e,a=new it(s,r,n,this.nextTensorId());return this.trackTensor(a,t),a}makeVariable(e,t=!0,n,s){n=n||this.nextVariableId().toString(),s!=null&&s!==e.dtype&&(e=e.cast(s));let r=new Np(e,t,n,this.nextTensorId());if(this.state.registeredVariables[r.name]!=null)throw new Error(`Variable with name ${r.name} was already registered`);return this.state.registeredVariables[r.name]=r,this.incRef(r,this.backend),r}trackTensor(e,t){this.state.numTensors++,e.dtype==="string"&&this.state.numStringTensors++;let n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*D3(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 Np||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*D3(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=$3(e);i!=null&&(s=i.gradFunc),s!=null&&(o.gradient=l=>(l=l.map((u,c)=>{if(u==null){let p=n[c],d=t0(p.size,p.dtype);return this.makeTensor(d,p.shape,p.dtype)}return u}),s(l.length>1?l:l[0],r,a))),this.state.activeTape.push(o)}keep(e){return e.kept=!0,e}startTape(){this.state.gradientDepth===0&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(e){let t={track:[],name:"unnamed scope",id:this.state.nextScopeId++};e&&(t.name=e),this.state.scopeStack.push(t),this.state.activeScope=t}endScope(e){let t=Gy(e),n=new Set(t.map(r=>r.id));for(let r=0;r<this.state.activeScope.track.length;r++){let a=this.state.activeScope.track[r];!a.kept&&!n.has(a.id)&&a.dispose()}let s=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(r=>{!r.kept&&r.scopeId===s.id&&this.track(r)})}gradients(e,t,n,s=!1){if(O(t.length>0,()=>"gradients() received an empty list of xs."),n!=null&&n.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);let r=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));O(r instanceof it,()=>"The result y returned by f() must be a tensor.");let a=GD(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?t$(r.shape):n,HD(o,a,l=>this.tidy(l),n$);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 O(ro(e),()=>"The f passed in customGrad(f) must be a function."),(...t)=>{O(t.every(o=>o instanceof it),()=>"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),O(n.value instanceof it,()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"),O(ro(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];O(u.length===t.length,()=>"The function f passed in customGrad(f) must 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Tw=W({basicLSTMCell_:xF});function bF(e,t,n){let s=D(e,"x","batchToSpaceND"),r=t.reduce((i,l)=>i*l);O(s.rank>=1+t.length,()=>`input rank is ${s.rank} but should be > than blockShape.length ${t.length}`),O(n.length===t.length,()=>`crops.length is ${n.length} but should be equal to blockShape.length  ${t.length}`),O(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 B.runKernel(vl,a,o)}var Ah=W({batchToSpaceND_:bF});function vF(e){let t;return e.rank===0||e.rank===1?t=V(e,[1,1,1,e.size]):e.rank===2?t=V(e,[1,1,e.shape[0],e.shape[1]]):e.rank===3?t=V(e,[1,e.shape[0],e.shape[1],e.shape[2]]):t=e,t}function wF(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")),O(i.rank===l.rank,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),O(c==null||i.rank===c.rank,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),O(u==null||i.rank===u.rank,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let d={x:vF(o),scale:u,offset:c,mean:i,variance:l},h={varianceEpsilon:a},f=B.runKernel(Oo,d,h);return V(f,o.shape)}var Qc=W({batchNorm_:wF});function kF(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")),O(o.rank===2,()=>`Error in batchNorm2D: x must be rank 2 but got rank ${o.rank}.`),O(i.rank===2||i.rank===1,()=>`Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank ${i.rank}.`),O(l.rank===2||l.rank===1,()=>`Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank ${l.rank}.`),u!=null&&O(u.rank===2||u.rank===1,()=>`Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank ${u.rank}.`),c!=null&&O(c.rank===2||c.rank===1,()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${c.rank}.`),Qc(o,i,l,c,u,a)}var xA=W({batchNorm2d_:kF});function SF(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")),O(o.rank===3,()=>`Error in batchNorm3D: x must be rank 3 but got rank ${o.rank}.`),O(i.rank===3||i.rank===1,()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${i.rank}.`),O(l.rank===3||l.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${l.rank}.`),u!=null&&O(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${u.rank}.`),c!=null&&O(c.rank===3||c.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${c.rank}.`),Qc(o,i,l,c,u,a)}var bA=W({batchNorm3d_:SF});function IF(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")),O(o.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${o.rank}.`),O(i.rank===4||i.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${i.rank}.`),O(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${l.rank}.`),u!=null&&O(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${u.rank}.`),c!=null&&O(c.rank===4||c.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${c.rank}.`),Qc(o,i,l,c,u,a)}var vA=W({batchNorm4d_:IF});function CF(e,t,n){let s=D(e,"x","bincount"),r=D(t,"weights","bincount");O(s.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${s.dtype}`),O(n>=0,()=>`size must be non-negative, but got ${n}.`),O(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 B.runKernel(r0,a,o)}var wA=W({bincount_:CF});function TF(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 ${s.rank}`);let r={s0:n,s1:s};return B.runKernel(a0,r)}var Nw=W({broadcastArgs_:TF});function NF(e,t){let n=D(e,"broadcastTo","x"),s=n.shape;if(t.some(u=>!(u>0)||u%1!==0))throw new Error(`broadcastTo(): Invalid broadcast shape [${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=V(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 Gn(n);let i={x:n},l={reps:a};return B.runKernel(Pa,i,l)}var nl=W({broadcastTo_:NF});function EF(e){let n={x:D(e,"x","ceil","float32")};return B.runKernel(So,n)}var kA=W({ceil_:EF});function RF(e,t,n){let s=D(e,"x","clipByValue");O(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 B.runKernel($a,r,a)}var ws=W({clipByValue_:RF});function _F(e){return ct(e,0)}var SA=W({concat1d_:_F});function DF(e,t){return ct(e,t)}var cu=W({concat2d_:DF});function $F(e,t){return ct(e,t)}var IA=W({concat3d_:$F});function PF(e,t){return ct(e,t)}var CA=W({concat4d_:PF});function FF(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=V(i,[1,i.shape[0],i.shape[1],i.shape[2]])),O(u.rank===4,()=>`Error in conv2d: input must be rank 4, but got rank ${u.rank}.`),O(l.rank===4,()=>`Error in conv2d: filter must be rank 4, but got rank ${l.rank}.`),ps("conv2d",s,o);let p=r==="NHWC"?u.shape[3]:u.shape[1];O(p===l.shape[2],()=>`Error in conv2d: depth of input (${p}) must match input depth for filter ${l.shape[2]}.`),O(ua(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=B.runKernel(Io,d,h);return c?V(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var Na=W({conv2d_:FF});function OF(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=V(i,[1,i.shape[0],i.shape[1]])),O(u.rank===3,()=>`Error in conv1d: input must be rank 3, but got rank ${u.rank}.`),O(l.rank===3,()=>`Error in conv1d: filter must be rank 3, but got rank ${l.rank}.`),ps("conv1d",s,o),O(u.shape[2]===l.shape[1],()=>`Error in conv1d: depth of input (${u.shape[2]}) must match input depth for filter ${l.shape[1]}.`),O(ua(n,a),()=>`Error in conv1D: Either stride or dilation must be 1. Got stride ${n} and dilation '${a}'`),O(r==="NWC",()=>`Error in conv1d: got dataFormat of ${r} but only NWC is currently supported.`);let p=V(l,[1,l.shape[0],l.shape[1],l.shape[2]]),d=V(u,[u.shape[0],1,u.shape[1],u.shape[2]]),g=Na(d,p,[1,n],s,"NHWC",[1,a],o);return c?V(g,[g.shape[2],g.shape[3]]):V(g,[g.shape[0],g.shape[2],g.shape[3]])}var R0=W({conv1d_:OF});function MF(e,t,n,s,r,a="NHWC",o){O(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let i=e,l=t,u=!1;t.rank===3&&(u=!0,l=V(t,[1,t.shape[0],t.shape[1],t.shape[2]]),i=[1,e[0],e[1],e[2]]),O(i.length===4,()=>`Error in conv2dDerInput: inShape must be length 4, but got length ${i.length}.`),O(l.rank===4,()=>`Error in conv2dDerInput: dy must be rank 4, but got rank ${l.rank}`),O(n.rank===4,()=>`Error in conv2dDerInput: filter must be rank 4, but got rank ${n.rank}`);let c=a==="NHWC"?i[3]:i[1],p=a==="NHWC"?l.shape[3]:l.shape[1];O(c===n.shape[2],()=>`Error in conv2dDerInput: depth of input (${c}) must match input depth for filter ${n.shape[2]}.`),O(p===n.shape[3],()=>`Error in conv2dDerInput: depth of output (${p}) must match output depth for filter ${n.shape[3]}.`),ps("conv2dDerInput",r,o);let d={dy:l,filter:n},h={strides:s,pad:r,dataFormat:a,dimRoundingMode:o,inputShape:i},f=B.runKernel(Co,d,h);return u?V(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var TA=W({conv2DBackpropInput_:MF});function zF(e,t,n,s,r,a){let o=D(e,"x","conv2dTranspose"),i=D(t,"filter","conv2dTranspose");return TA(n,o,i,s,r,"NHWC",a)}var _0=W({conv2dTranspose_:zF});function LF(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=V(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),O(l.rank===5,()=>`Error in conv3d: input must be rank 5, but got rank ${l.rank}.`),O(i.rank===5,()=>`Error in conv3d: filter must be rank 5, but got rank ${i.rank}.`),O(l.shape[4]===i.shape[3],()=>`Error in conv3d: depth of input (${l.shape[4]}) must match input depth for filter ${i.shape[3]}.`),O(ua(n,a),()=>`Error in conv3D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`),O(r==="NDHWC",()=>`Error in conv3d: got dataFormat of ${r} but only NDHWC is currently supported.`);let c={x:l,filter:i},p={strides:n,pad:s,dataFormat:r,dilations:a},d=B.runKernel(Xp,c,p);return u?V(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var NA=W({conv3d_:LF});function BF(e,t,n,s,r){O(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let a=e,o=t,i=!1;t.rank===4&&(i=!0,o=V(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];O(a.length===5,()=>`Error in conv3dDerInput: inShape must be length 5, but got length ${a.length}.`),O(o.rank===5,()=>`Error in conv3dDerInput: dy must be rank 5, but got rank ${o.rank}`),O(n.rank===5,()=>`Error in conv3dDerInput: filter must be rank 5, but got rank ${n.rank}`),O(l===n.shape[3],()=>`Error in conv3dDerInput: depth of input (${l}) must match input depth for filter ${n.shape[3]}.`),O(u===n.shape[4],()=>`Error in conv3dDerInput: depth of output (${u}) must match output depth for filter ${n.shape[4]}.`);let c={dy:o,filter:n},p={pad:r,strides:s,inputShape:a},d=B.runKernel(l0,c,p);return i?V(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var Ew=W({conv3DBackpropInput_:BF});function WF(e,t,n,s,r){let a=D(e,"x","conv3dTranspose"),o=D(t,"filter","conv3dTranspose");return Ew(n,a,o,s,r)}var EA=W({conv3dTranspose_:WF});function VF(e){let n={x:D(e,"x","cos","float32")};return B.runKernel(To,n)}var xh=W({cos_:VF});function UF(e){let n={x:D(e,"x","cosh","float32")};return B.runKernel(No,n)}var D0=W({cosh_:UF});function GF(e,t=0,n=!1,s=!1){let a={x:D(e,"x","cumprod")},o={axis:t,exclusive:n,reverse:s};return B.runKernel(kl,a,o)}var Dp=W({cumprod_:GF});function HF(e,t=0,n=!1,s=!1){let a={x:D(e,"x","cumsum")},o={axis:t,exclusive:n,reverse:s};return B.runKernel(Eo,a,o)}var $0=W({cumsum_:HF});function jF(e,t,n,s=!1){let r=D(e,"x","denseBincount"),a=D(t,"weights","denseBincount");O(r.dtype==="int32",()=>`Error in denseBincount: input dtype must be int32, but got ${r.dtype}`),O(r.rank<=2,()=>`Error in denseBincount: input must be at most rank 2, but got rank ${r.rank}.`),O(n>=0,()=>`size must be non-negative, but got ${n}.`),O(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 B.runKernel(u0,o,i)}var Rw=W({denseBincount_:jF});function qF(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];O(t>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${t}`),O(r*t>=0,()=>`Negative dimension size caused by overflow when multiplying
    ${r} and ${t}  for depthToSpace with input shape
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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)}};l2.className="Adamax";fi(l2);var Rh=class extends Oa{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=B.registeredVariables[n];Y(()=>{let o=de(z(this.c,r),a);a.assign(o)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=Tn(Te(-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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instead`);if(a==="channelsFirst"&&(e=at(e,[0,2,1])),r==="causal")throw new Je("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let i=R0(e,t,s,r==="same"?"same":"valid","NWC",o);return n!=null&&(i=Hr(i,n)),i})}function A7(e,t,n,s=[1,1],r="valid",a,o,i=null){return Y(()=>{if(a==null&&(a=Vr()),en(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=V5(e,a);if(r==="causal")throw new Je("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=gc.conv2d({x:l,filter:t,strides:s,pad:r==="same"?"same":"valid",dilations:o,dataFormat:"NHWC",bias:n,activation:i}),a==="channelsFirst"&&(l=at(l,[0,3,1,2])),l})}function eH(e,t,n,s=[1,1,1],r="valid",a,o){return Y(()=>{if(a==null&&(a=Vr()),en(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 ${e.rank}.`);let i=E8(e,a);if(r==="causal")throw new Je("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return i=NA(i,t,s,r==="same"?"same":"valid","NDHWC",o),n!=null&&(i=Hr(i,n)),a==="channelsFirst"&&(i=at(i,[0,4,1,2,3])),i})}var U5=class extends pt{constructor(e,t){if(super(t),this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",U5.verifyArgs(t),this.rank=e,Nn(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Je(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=ic(t.kernelSize,e,"kernelSize"),this.strides=ic(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,or(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,en(this.dataFormat),this.activation=ho(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=Mt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=vn(t.biasConstraint),this.biasRegularizer=zt(t.biasRegularizer),this.activityRegularizer=zt(t.activityRegularizer),this.dilationRate=ic(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(Qr("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!h5(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:po(this.activation),useBias:this.useBias,biasInitializer:Ht(this.biasInitializer),biasRegularizer:Ct(this.biasRegularizer),activityRegularizer:Ct(this.activityRegularizer),biasConstraint:bn(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Mh=class extends U5{constructor(e,t){super(e,t),this.kernel=null,Mh.verifyArgs(t),this.filters=t.filters,Nn(this.filters,"filters"),this.kernelInitializer=Mt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=vn(t.kernelConstraint),this.kernelRegularizer=zt(t.kernelRegularizer)}build(e){e=bt(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 Y(()=>{e=et(e);let n,s=this.bias==null?null:this.bias.read(),r=Mk(this.activation.getClassName());if(r!=null&&this.rank===2)n=A7(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate,r);else{if(this.rank===1)n=QG(e,this.kernel.read(),s,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=A7(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=eH(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new Je("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=bt(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=Br(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:Ht(this.kernelInitializer),kernelRegularizer:Ct(this.kernelRegularizer),kernelConstraint:bn(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)}`)}},zh=class extends Mh{constructor(e){super(2,e),zh.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!h5(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)}.`)}};zh.className="Conv2D";he.registerClass(zh);var Lh=class extends Mh{constructor(e){super(3,e),Lh.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)}.`)}};Lh.className="Conv3D";he.registerClass(Lh);var G5=class extends zh{constructor(e){if(super(e),this.inputSpec=[new on({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new j(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=bt(e),e.length!==4)throw new j("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new j("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],s=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",s,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new on({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return Y(()=>{let n=et(e);if(n.shape.length!==4)throw new j(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${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=ea(i,p,u,this.padding),f=ea(l,d,c,this.padding),m=[r,h,f,this.filters];this.dataFormat!=="channelsLast"&&(n=at(n,[0,2,3,1]));let g=_0(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(g=at(g,[0,3,1,2])),this.bias!=null&&(g=Hr(g,this.bias.read(),this.dataFormat)),this.activation!=null&&(g=this.activation.apply(g)),g})}computeOutputShape(e){e=bt(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]=ea(t[s],i,a,this.padding),t[r]=ea(t[r],l,o,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};G5.className="Conv2DTranspose";he.registerClass(G5);var H5=class extends Lh{constructor(e){if(super(e),this.inputSpec=[new on({ndim:5})],this.padding!=="same"&&this.padding!=="valid")throw new j(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=bt(e),e.length!==5)throw new j("Input should have rank 5; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new j("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],s=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",s,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new on({ndim:5,axes:{[t]:n}})],this.built=!0}call(e,t){return Y(()=>{let n=et(e);if(n.shape.length!==5)throw new j(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${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=ea(l,f,p,this.padding),x=ea(u,m,d,this.padding),A=ea(c,g,h,this.padding),b=[r,y,x,A,this.filters];this.dataFormat!=="channelsLast"&&(n=at(n,[0,2,3,4,1]));let w=EA(n,this.kernel.read(),b,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(w=at(w,[0,4,1,2,3])),this.bias!==null&&(w=Hr(w,this.bias.read(),this.dataFormat)),this.activation!==null&&(w=this.activation.apply(w)),w})}computeOutputShape(e){e=bt(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]=ea(t[s],u,o,this.padding),t[r]=ea(t[r],c,i,this.padding),t[a]=ea(t[a],p,l,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};H5.className="Conv3DTranspose";he.registerClass(H5);var R8=class extends Mh{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 ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=Mt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=zt(t.depthwiseRegularizer),this.depthwiseConstraint=vn(t.depthwiseConstraint),this.pointwiseInitializer=Mt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=zt(t.pointwiseRegularizer),this.pointwiseConstraint=vn(t.pointwiseConstraint)}build(e){if(e=bt(e),e.length<this.rank+2)throw new j(`Inputs to SeparableConv${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 on({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return Y(()=>{e=et(e);let n;if(this.rank===1)throw new Je("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=at(e,[0,2,3,1])),n=j0(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Hr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=at(n,[0,3,1,2])),n})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=Ht(this.depthwiseInitializer),e.pointwiseInitializer=Ht(this.pointwiseInitializer),e.depthwiseRegularizer=Ct(this.depthwiseRegularizer),e.pointwiseRegularizer=Ct(this.pointwiseRegularizer),e.depthwiseConstraint=bn(this.depthwiseConstraint),e.pointwiseConstraint=bn(this.pointwiseConstraint),e}};R8.className="SeparableConv";var j5=class extends R8{constructor(e){super(2,e)}};j5.className="SeparableConv2D";he.registerClass(j5);var S2=class extends Mh{constructor(e){super(1,e),S2.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"&&!h5(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)}.`)}};S2.className="Conv1D";he.registerClass(S2);var q5=class extends pt{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 Y(()=>{if(e=et(e),this.dataFormat==="channelsLast"){let n=em(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return em(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=em(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return em(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}};q5.className="Cropping2D";he.registerClass(q5);var X5=class extends pt{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,en(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,cU(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 Y(()=>{let n=et(e),s=n.shape;if(this.dataFormat==="channelsFirst"){n=at(n,[0,2,3,1]);let r=this.size[0]*s[2],a=this.size[1]*s[3],o=this.interpolation==="nearest"?Ce.resizeNearestNeighbor(n,[r,a]):Ce.resizeBilinear(n,[r,a]);return at(o,[0,3,1,2])}else{let r=this.size[0]*s[1],a=this.size[1]*s[2];return this.interpolation==="nearest"?Ce.resizeNearestNeighbor(n,[r,a]):Ce.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}};X5.className="UpSampling2D";he.registerClass(X5);function tH(e,t,n=[1,1],s="valid",r,a){return Y(()=>{r==null&&(r=Vr()),en(r);let o=V5(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=ed(o,t,n,s==="same"?"same":"valid","NHWC",a),r==="channelsFirst"&&(o=at(o,[0,3,1,2])),o})}var K5=class extends U5{constructor(e){super(2,e),this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=Mt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=vn(e.depthwiseConstraint),this.depthwiseRegularizer=zt(e.depthwiseRegularizer)}build(e){if(e=bt(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 Y(()=>{e=et(e);let n=tH(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Hr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=bt(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=Br(t,this.kernelSize[0],this.padding,this.strides[0]),a=Br(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=Ht(this.depthwiseInitializer),e.depthwiseRegularizer=Ct(this.depthwiseRegularizer),e.depthwiseConstraint=bn(this.depthwiseRegularizer),e}};K5.className="DepthwiseConv2D";he.registerClass(K5);function _8(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 D8(e,t,n,s=!1,r,a,o=!1,i=!1){return Y(()=>{let l=t.shape.length;if(l<3)throw new j(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(Wr(2,l));if(t=at(t,u),a!=null)throw new Je("The rnn() functoin of the deeplearn.js backend does not support constants yet.");o&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),r!=null&&(r=ge(ge(r,"bool"),"float32"),r.rank===l-1&&(r=Ft(r,-1)),r=at(r,u)),s&&(t=nr(t,0),r!=null&&(r=nr(r,0)));let c=[],p,d=n,h=t.shape[0],f=wn(t),m;r!=null&&(m=wn(r));for(let y=0;y<h;++y){let x=f[y],A=Y(()=>e(x,d));if(r==null)p=A[0],d=A[1];else{let b=Y(()=>{let w=m[y],k=Ae(Ws(w),w),C=de(z(A[0],w),z(d[0],k)),E=d.map((_,$)=>de(z(A[1][$],w),z(_,k)));return{output:C,newStates:E}});p=b.output,d=b.newStates}i&&c.push(p)}let g;return i&&(g=un(c,1)),[p,g,d]})}var pa=class extends pt{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 T2({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 on({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return Wr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){J3(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 Y(()=>{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 Je("Constants support is not implemented in RNN yet.");J3(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,s=e.slice(2);this.inputSpec[0]=new on({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 on({shape:[null,o]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){Y(()=>{if(!this.stateful)throw new ba("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=>Gt([n,s])):this.states_=[Gt([n,this.cell.stateSize])];else if(e==null)Q(this.states_),this.keptStates!=null&&(Q(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(s=>Gt([n,s])):this.states_[0]=Gt([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()):Q(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=>Tn(s.clone()))})}apply(e,t){let n=t==null?null:t.initialState,s=t==null?null:t.constants;t==null&&(t={});let r=_8(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 on({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 Mr){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 Y(()=>{let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;e=et(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=D8((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 Y(()=>{let t=Gt(e.shape);return t=Se(t,[1,2]),t=Dh(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?Z3(t,[1,n]):t):this.cell.stateSize>1?[Z3(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()===pa.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let s=t.cell,r=Lr(s,n);return new e(Object.assign(t,{cell:r}))}};pa.className="RNN";he.registerClass(pa);var Bh=class extends pt{},I2=class extends Bh{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,Nn(this.units,"units"),this.activation=ho(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Mt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Mt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Mt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=zt(e.kernelRegularizer),this.recurrentRegularizer=zt(e.recurrentRegularizer),this.biasRegularizer=zt(e.biasRegularizer),this.kernelConstraint=vn(e.kernelConstraint),this.recurrentConstraint=vn(e.recurrentConstraint),this.biasConstraint=vn(e.biasConstraint),this.dropout=yc([1,co([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=yc([1,co([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=bt(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 Y(()=>{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=fo({ones:()=>Ws(e),rate:this.dropout,training:s,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=fo({ones:()=>Ws(n),rate:this.recurrentDropout,training:s,dropoutFunc:this.dropoutFunc}));let r,a=this.dropoutMask,o=this.recurrentDropoutMask;a!=null?r=sa(z(e,a),this.kernel.read()):r=sa(e,this.kernel.read()),this.bias!=null&&(r=Hr(r,this.bias.read())),o!=null&&(n=z(n,o));let i=de(r,sa(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:po(this.activation),useBias:this.useBias,kernelInitializer:Ht(this.kernelInitializer),recurrentInitializer:Ht(this.recurrentInitializer),biasInitializer:Ht(this.biasInitializer),kernelRegularizer:Ct(this.kernelRegularizer),recurrentRegularizer:Ct(this.recurrentRegularizer),biasRegularizer:Ct(this.biasRegularizer),activityRegularizer:Ct(this.activityRegularizer),kernelConstraint:bn(this.kernelConstraint),recurrentConstraint:bn(this.recurrentConstraint),biasConstraint:bn(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};I2.className="SimpleRNNCell";he.registerClass(I2);var Z5=class extends pa{constructor(e){e.cell=new I2(e),super(e)}call(e,t){return Y(()=>{this.cell.dropoutMask!=null&&(Q(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Q(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)}};Z5.className="SimpleRNN";he.registerClass(Z5);var C2=class extends Bh{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,Nn(this.units,"units"),this.activation=ho(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ho(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Mt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Mt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Mt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=zt(e.kernelRegularizer),this.recurrentRegularizer=zt(e.recurrentRegularizer),this.biasRegularizer=zt(e.biasRegularizer),this.kernelConstraint=vn(e.kernelConstraint),this.recurrentConstraint=vn(e.recurrentConstraint),this.biasConstraint=vn(e.biasConstraint),this.dropout=yc([1,co([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=yc([1,co([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=bt(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 Y(()=>{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=fo({ones:()=>Ws(e),rate:this.dropout,training:n,count:3,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=fo({ones:()=>Ws(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=z(e,r[0]));let u=sa(e,this.kernel.read());this.useBias&&(u=Hr(u,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(s=z(s,a[0]));let c=this.recurrentKernel.read(),[p,d]=qt(c,[2*this.units,this.units],c.rank-1),h=sa(s,p),[f,m,g]=qt(u,3,u.rank-1),[y,x]=qt(h,2,h.rank-1);o=this.recurrentActivation.apply(de(f,y)),i=this.recurrentActivation.apply(de(m,x));let A=sa(z(i,s),d);l=this.activation.apply(de(g,A));let b=de(z(o,s),z(de(1,Pt(o)),l));return[b,b]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:po(this.activation),recurrentActivation:po(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Ht(this.kernelInitializer),recurrentInitializer:Ht(this.recurrentInitializer),biasInitializer:Ht(this.biasInitializer),kernelRegularizer:Ct(this.kernelRegularizer),recurrentRegularizer:Ct(this.recurrentRegularizer),biasRegularizer:Ct(this.biasRegularizer),activityRegularizer:Ct(this.activityRegularizer),kernelConstraint:bn(this.kernelConstraint),recurrentConstraint:bn(this.recurrentConstraint),biasConstraint:bn(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};C2.className="GRUCell";he.registerClass(C2);var Y5=class extends pa{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. 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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 xr{apply(p,d){let h=l.apply([u]),f=Os([u]),m=l.apply([u*2]);return f5([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 Y(()=>{if(e.length!==3)throw new j(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,s=e[0],r=e[1],a=e[2],o=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=fo({ones:()=>Ws(s),rate:this.dropout,training:n,count:o,dropoutFunc:this.dropoutFunc}));let i=this.dropoutMask,l=(Z,J,te)=>!J||!J[te]?Z:z(J[te],Z),u=l(s,i,0),c=l(s,i,1),p=l(s,i,2),d=l(s,i,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=fo({ones:()=>Ws(r),rate:this.recurrentDropout,training:n,count:o,dropoutFunc:this.dropoutFunc}));let h=this.recurrentDropoutMask,f=l(r,h,0),m=l(r,h,1),g=l(r,h,2),y=l(r,h,3),x=3,[A,b,w,k]=qt(this.kernel.read(),o,x),[C,E,_,$]=this.useBias?qt(this.bias.read(),o):[null,null,null,null];u=this.inputConv(u,A,C,this.padding),c=this.inputConv(c,b,E,this.padding),p=this.inputConv(p,w,_,this.padding),d=this.inputConv(d,k,$,this.padding);let[R,P,S,M]=qt(this.recurrentKernel.read(),o,x);f=this.recurrentConv(f,R),m=this.recurrentConv(m,P),g=this.recurrentConv(g,S),y=this.recurrentConv(y,M);let L=this.recurrentActivation.apply(de(u,f)),U=this.recurrentActivation.apply(de(c,m)),K=de(z(U,a),z(L,this.activation.apply(de(p,g)))),q=z(this.recurrentActivation.apply(de(d,y)),this.activation.apply(K));return[q,q,K]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=nH(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=Na(e,t,this.strides,s||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Hr(r,n,this.dataFormat):r}recurrentConv(e,t){return Na(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};N2.className="ConvLSTM2DCell";he.registerClass(N2);var Q5=class extends $8{constructor(e){let t=new N2(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};Q5.className="ConvLSTM2D";he.registerClass(Q5);var E2=class extends pt{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 Y(()=>{this.invokeCallHook(e,t);let n=et(e);if(0<this.rate&&this.rate<1){let s=t.training==null?!1:t.training,r=this.getNoiseShape(n);return Ph(()=>Gk(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()}};E2.className="Dropout";he.registerClass(E2);var ex=class extends E2{constructor(e){super(e),this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};ex.className="SpatialDropout1D";he.registerClass(ex);var tx=class extends pt{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,Nn(this.units,"units"),this.activation=ho(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=Mt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=Mt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=vn(e.kernelConstraint),this.biasConstraint=vn(e.biasConstraint),this.kernelRegularizer=zt(e.kernelRegularizer),this.biasRegularizer=zt(e.biasRegularizer),this.activityRegularizer=zt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=bt(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=bt(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return Y(()=>{this.invokeCallHook(e,t);let n=et(e),s=Mk(this.activation.getClassName()),r;return s!=null?r=sa(n,this.kernel.read(),s,this.bias?this.bias.read():null):(r=sa(n,this.kernel.read()),this.bias!=null&&(r=Hr(r,this.bias.read())),this.activation!=null&&(r=this.activation.apply(r))),r})}getConfig(){let 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e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Ht(this.betaInitializer),gammaInitializer:Ht(this.gammaInitializer),betaRegularizer:Ct(this.betaRegularizer),gammaRegularizer:Ct(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};bx.className="LayerNormalization";he.registerClass(bx);function iH(e,t,n){return Y(()=>{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=Vr()),n!=="channelsLast"&&n!=="channelsFirst")throw new j(`Unknown data format: ${n}. 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a==="max"?o=kh(e,t,n,i):o=yh(e,t,n,i),r==="channelsFirst"&&(o=at(o,[0,3,1,2])),o})}function P8(e,t,n,s,r,a){return Y(()=>{en(r),Lk(a),or(s),n==null&&(n=[1,1,1]),s==null&&(s="valid"),r==null&&(r=Vr()),a==null&&(a="max"),e=E8(e,r);let o,i=s==="same"?"same":"valid";return a==="max"?o=HA(e,t,n,i):o=AA(e,t,n,i),r==="channelsFirst"&&(o=at(o,[0,4,1,2,3])),o})}var F8=class extends pt{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(Nn(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 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en(r),or(s),R2(e,t,n,s,r,"avg")}};kx.className="AveragePooling1D";he.registerClass(kx);var O8=class extends pt{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];Nn(this.poolSize,"poolSize"),Nn(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,en(this.dataFormat),or(this.padding),this.inputSpec=[new on({ndim:4})]}computeOutputShape(e){e=bt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Br(t,this.poolSize[0],this.padding,this.strides[0]),n=Br(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return Y(()=>(this.invokeCallHook(e,t),this.poolingFunction(et(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}},Sx=class extends O8{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return en(r),or(s),R2(e,t,n,s,r,"max")}};Sx.className="MaxPooling2D";he.registerClass(Sx);var Ix=class extends O8{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return en(r),or(s),R2(e,t,n,s,r,"avg")}};Ix.className="AveragePooling2D";he.registerClass(Ix);var M8=class extends pt{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];Nn(this.poolSize,"poolSize"),Nn(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,en(this.dataFormat),or(this.padding),this.inputSpec=[new on({ndim:5})]}computeOutputShape(e){e=bt(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=Br(t,this.poolSize[0],this.padding,this.strides[0]),n=Br(n,this.poolSize[1],this.padding,this.strides[1]),s=Br(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 Y(()=>(this.invokeCallHook(e,t),this.poolingFunction(et(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}},Cx=class extends M8{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return en(r),or(s),P8(e,t,n,s,r,"max")}};Cx.className="MaxPooling3D";he.registerClass(Cx);var Tx=class extends M8{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return en(r),or(s),P8(e,t,n,s,r,"avg")}};Tx.className="AveragePooling3D";he.registerClass(Tx);var z8=class extends pt{constructor(e){super(e),this.inputSpec=[new on({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new Je}},Nx=class extends z8{constructor(e){super(e||{})}call(e,t){return Y(()=>{let n=et(e);return Ut(n,1)})}};Nx.className="GlobalAveragePooling1D";he.registerClass(Nx);var Ex=class extends z8{constructor(e){super(e||{})}call(e,t){return Y(()=>{let n=et(e);return xn(n,1)})}};Ex.className="GlobalMaxPooling1D";he.registerClass(Ex);var L8=class extends pt{constructor(e){super(e),this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,en(this.dataFormat),this.inputSpec=[new on({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new Je}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Rx=class extends L8{call(e,t){return Y(()=>{let n=et(e);return this.dataFormat==="channelsLast"?Ut(n,[1,2]):Ut(n,[2,3])})}};Rx.className="GlobalAveragePooling2D";he.registerClass(Rx);var _x=class extends L8{call(e,t){return Y(()=>{let n=et(e);return 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e(a)}},Dx=class extends B8{constructor(e){super(e),this.supportsMasking=!0}build(e){if(e=bt(e),e.length<3)throw new j(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=bt(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),s=e[1];return[n[0],s].concat(n.slice(1))}call(e,t){return Y(()=>(e=et(e),D8((a,o)=>[et(this.layer.call(a,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};Dx.className="TimeDistributed";he.registerClass(Dx);function lH(e){mu(uU,"BidirectionalMergeMode",e)}var uH="concat",$x=class extends B8{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Lr(n),t.goBackwards=t.goBackwards!==!0;let s={};if(s.className=e.layer.getClassName(),s.config=t,this.backwardLayer=Lr(s),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?uH:e.mergeMode,lH(this.mergeMode),e.weights)throw new Je("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 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on({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 Je("Support for constants in Bidirectional layers is not implemented yet.");let i=a[0]instanceof Mr;for(let l of a)if(l instanceof Mr!==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 Y(()=>{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=nr(r,1));let 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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 T7(e,t,n,s){let r=new Set,a=[],o=null,i=null,l=new Set,u=Object.keys(e).map(d=>$s(d)[0]),c=[];s!=null&&(c=s.map(d=>$s(d.name)[0]));let p=[...t];for(;p.length>0;){let d=p.pop();if((AS(d)||Bq(d)||Wq(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 Oq(e,t,n){let{usedNodes:s,inputs:r}=n,a=[],o=Object.keys(r).map(c=>$s(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 Mq=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],zq=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],Lq=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function AS(e){return Mq.indexOf(e.op)>=0}function Bq(e){return zq.indexOf(e.op)>=0}function Wq(e){return Lq.indexOf(e.op)>=0}var gy=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 gy(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}:${e.defaultOutput}`:t})}get functions(){return Object.keys(this._functions).reduce((e,t)=>(e[t]=this._functions[t].signature,e),{})}getCompilationKey(e,t){let n=e.map(r=>r.name).sort(),s=t.map(r=>r.name).sort();return n.join(this.SEPERATOR)+"--"+s.join(this.SEPERATOR)}compile(e,t){let n=T7(e,t,this.weightMap,this._initNodes),{missingInputs:s,dynamicNode:r,syncInputs:a}=n;if(r!=null)throw new Error(`This execution contains the node '${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: [${s}]`)}return Oq(this.graph,this.weightMap,n)}execute(e,t){e=this.mapInputs(e);let n=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let s=n.map(c=>this.graph.nodes[$s(c)[0]]),r=t.map(c=>$s(c)[0]),a=r.map(c=>this.graph.nodes[c]);this.resetIntermediateTensors(),a.length===0&&(a=this._outputs);let o=this.getCompilationKey(s,a),i=this.compiledMap.get(o);i==null&&(i=this.compile(e,a),this.compiledMap.set(o,i));let l={},u={};return Y(()=>{let c=new C7(this.weightMap,l,u,this.functionExecutorMap),p=Object.assign({},this.weightMap);Object.keys(e).forEach(f=>{let[m,g]=$s(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=I7(m,p,c,this._resourceManager);if(v.isPromise(g))throw new Error(`The execution of the op '${m.op}' returned a promise. Please use model.executeAsync() instead.`);p[m.name]=g,this.checkTensorForDisposal(m.name,m,p,c,d,r,h)}}return this.parent==null&&c.dispose(d),t.map(f=>ls(f,p,c))})}getFrozenTensorIds(e){let t=[].concat.apply([],Object.keys(e).map(n=>e[n]).map(n=>n.map(s=>s.id)));return new Set(t)}checkTensorForDisposal(e,t,n,s,r,a,o){t.category==="control"||a.indexOf(e)!==-1||(n[e].forEach(i=>{i!=null&&(o[i.id]=(o[i.id]||0)+t.children.length)}),t.inputs.forEach(i=>{if(i.category!=="control"){let l=Uj(i.name,n,s);l!=null&&l.forEach(u=>{if(u&&!u.kept&&!r.has(u.id)){let c=o[u.id];if(c===1){if(!this.keepTensorForDebug)u.dispose();else{let[p,d]=ta(t.name,s);this.intermediateTensors[p]?this.intermediateTensors[p][d]=u:(this.intermediateTensors[p]=[],this.intermediateTensors[p][d]=u)}delete o[u.id]}else c!=null&&o[u.id]--}})}}))}async executeAsync(e,t){return this._executeAsync(e,t)}disposeIntermediateTensors(){!this.intermediateTensors||(Object.keys(this.intermediateTensors).forEach(e=>this.intermediateTensors[e].forEach(t=>t.dispose())),this.disposeTensorsMap())}disposeTensorsMap(){!this.tensorsMap||Object.keys(this.tensorsMap).forEach(e=>{this.tensorsMap[e].forEach(n=>{n&&!n.kept&&!n.isDisposed&&!this.keepIds.has(n.id)&&n.dispose()})})}getIntermediateTensors(){return this.tensorsMap}resetIntermediateTensors(){for(let e in this.intermediateTensors)this.intermediateTensors[e].forEach(t=>t.dispose()),delete this.intermediateTensors[e]}async _executeAsync(e,t,n=!1,s={},r={}){n||(e=this.mapInputs(e),this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t));try{this.keepTensorForDebug=H().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(u){console.warn(u.message)}this.resetIntermediateTensors();let a=new C7(this.weightMap,s,r,this.functionExecutorMap);this.tensorsMap=await this.executeWithControlFlow(e,a,t,n);let o=t.map(u=>ls(u,this.tensorsMap,a)),i=o.map(u=>u.id),l=Object.keys(e).map(u=>e[u].id);return this.keepIds=new Set([...i,...l,...this.weightIds]),this.keepTensorForDebug||this.disposeTensorsMap(),this.parent==null&&a.dispose(this.keepIds),o}async executeFunctionAsync(e,t,n){let s=e.reduce((r,a,o)=>(r[this.inputs[o].name]=a,r),{});return this._executeAsync(s,this.outputNodes,!0,t,n)}async executeWithControlFlow(e,t,n,s){let r=Object.keys(e),a=r.map(x=>this.graph.nodes[$s(x)[0]]),o=n.map(x=>$s(x)[0]),i=o.map(x=>this.graph.nodes[x]);i.length===0&&(i=this._outputs);let{usedNodes:l,missingInputs:u,dynamicNode:c,syncInputs:p}=T7(e,i,this.weightMap,this._initNodes),d=[...a,...this.graph.weights,...this._initNodes||[]].map(x=>({node:x,contexts:t.currentContext})),h=Object.assign({},this.weightMap);Object.keys(e).forEach(x=>{let[A,b]=$s(x),w=[];w[b]=e[x],h[A]=w});let f={},m=this.getFrozenTensorIds(h),g={};for(;d.length>0;){let x=this.processStack(a,d,t,h,g,m,o,f,l);await Promise.all(x)}c==null&&!s&&console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");let y=i.filter(x=>!AS(x)&&!ls(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 [${r}]. Consider providing the following inputs: [${u}]. ${x}`)}return h}processStack(e,t,n,s,r,a,o,i,l){let u=[];for(;t.length>0;){let c=t.pop();n.currentContext=c.contexts;let p="";if(c.node.op==="Enter"&&I("isConstant",c.node,s,n)&&([p]=ta(c.node.name,n)),s[c.node.name]==null){let d=I7(c.node,s,n,this._resourceManager);p||([p]=ta(c.node.name,n));let h=n.currentContext;v.isPromise(d)?u.push(d.then(f=>(s[p]=f,n.currentContext=h,this.checkTensorForDisposal(p,c.node,s,n,a,o,i),this.processChildNodes(c.node,t,n,s,r,l),f))):(s[p]=d,this.checkTensorForDisposal(p,c.node,s,n,a,o,i),this.processChildNodes(c.node,t,n,s,r,l))}else this.processChildNodes(c.node,t,n,s,r,l)}return u}processChildNodes(e,t,n,s,r,a){e.children.forEach(o=>{let[i]=ta(o.name,n);r[i]||!a.has(o.name)||(o.op==="Merge"?o.inputNames.some(l=>!!ls(l,s,n))&&(r[i]=!0,t.push({contexts:n.currentContext,node:o})):o.inputNames.every(l=>!!ls(l,s,n))&&(r[i]=!0,t.push({contexts:n.currentContext,node:o})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let n=e[t],[s]=$s(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 ${n.dtype}`)})}mapInputs(e){let t={};for(let n in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let s=this._signature.inputs[n];t[s.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[s]=$s(n);return this.graph.nodes[s]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${t}] that are not part of graph`)}mapOutputs(e){return e.map(t=>this._signature!=null&&this._signature.outputs!=null&&this._signature.outputs[t]!=null?this._signature.outputs[t].name:t,{})}checkOutputs(e){e.forEach(t=>{let[n]=$s(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}},Vq=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},Uq="?tfjs-format=file",Gq="model.json",Vh=class{constructor(e,t={},n=Fs){this.modelUrl=e,this.loadOptions=t,this.version="n/a",this.io=n,t==null&&(this.loadOptions={}),this.resourceManager=new Vq}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}get modelStructuredOutputKeys(){return this.structuredOutputKeys}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=this.io.browserHTTPRequest(e,this.loadOptions);else{let t=this.io.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(this.io.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${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}.${t.versions.minConsumer}`;let s=this.io.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new gy(v7.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(s),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let r=v7.Instance.transformGraph(e.modelInitializer);this.initializer=new gy(r),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=this.io.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${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 n=this.execute(e,this.outputNodes);if(this.structuredOutputKeys){let s=n instanceof it?[n]:n,r={};return s.forEach((a,o)=>r[this.structuredOutputKeys[o]]=a),r}return n}normalizeInputs(e){if(!(e instanceof it)&&!Array.isArray(e))return e;if(e=Array.isArray(e)?e:[e],e.length!==this.inputNodes.length)throw new Error(`Input tensor count mismatch,the graph model has ${this.inputNodes.length} placeholders, while there are ${e.length} input tensors.`);return this.inputNodes.reduce((t,n,s)=>(t[n]=e[s],t),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}getIntermediateTensors(){return 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RangeError("Can't set item at a negative index.");this.data[e%this.capacity]=t}length(){let e=this.end-this.begin;return e<0&&(e=this.doubledCapacity+e),e}isFull(){return this.length()===this.capacity}isEmpty(){return this.length()===0}push(e){if(this.isFull())throw new RangeError("Ring buffer is full.");this.set(this.end,e),this.end=this.wrap(this.end+1)}pushAll(e){for(let t of e)this.push(t)}pop(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");this.end=this.wrap(this.end-1);let e=this.get(this.end);return this.set(this.end,void 0),e}unshift(e){if(this.isFull())throw new RangeError("Ring buffer is full.");this.begin=this.wrap(this.begin-1),this.set(this.begin,e)}shift(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let e=this.get(this.begin);return this.set(this.begin,void 0),this.begin=this.wrap(this.begin+1),e}shuffleExcise(e){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let t=this.wrap(this.begin+e),n=this.get(t);return this.set(t,this.pop()),n}},Bx=class extends kS{constructor(){super(Bx.INITIAL_CAPACITY)}isFull(){return!1}push(e){super.isFull()&&this.expand(),super.push(e)}unshift(e){super.isFull()&&this.expand(),super.unshift(e)}expand(){let e=this.capacity*2,t=new Array(e),n=this.length();for(let s=0;s<n;s++)t[s]=this.get(this.wrap(this.begin+s));this.data=t,this.capacity=e,this.doubledCapacity=2*this.capacity,this.begin=0,this.end=n}};Bx.INITIAL_CAPACITY=32;function SS(e){return new rX(e)}function Wx(e){return new aX(e)}function nX(e,t){return new IS(e,t)}function sX(e,t=eo.FAIL){return new fX(e,t)}var En=class{async toArray(){let e=[],t=await this.next();for(;!t.done;)e.push(t.value),t=await this.next();return e}async toArrayForTest(){let e=this.prefetch(100),t=[],n=await e.next();for(;!n.done;)t.push(n.value),n=await e.next();return t}async resolveFully(){let e=await this.next();for(;!e.done;)e=await this.next()}async resolveWhile(e){let t=await this.next(),n=e(t.value);for(;!t.done&&n;)t=await this.next(),n=e(t.value)}handleErrors(e){return new pX(this,e)}filter(e){return new cX(this,e)}map(e){return new dX(this,e)}mapAsync(e){return new N7(this,e)}serialMapAsync(e){return new N7(this,e).serial()}flatmap(e){return new hX(this,e)}async forEachAsync(e){return this.map(e).resolveFully()}async serialForEach(e){return this.serialMapAsync(e).resolveWhile(t=>t===!0)}rowMajorBatch(e,t=!0){return new uX(this,e,t)}columnMajorBatch(e,t=!0,n=vS){return this.rowMajorBatch(e,t).map(r=>Yq(r,n))}concatenate(e,t){return new IS(SS([this,e]),t)}take(e){return e<0||e==null?this:new lX(this,e)}skip(e){return e<0||e==null?this:new iX(this,e)}prefetch(e){return new CS(this,e)}shuffle(e,t){return new mX(this,e,t)}serial(){return new oX(this)}},rX=class extends En{constructor(e){super(),this.items=e,this.trav=0}summary(){return`Array of ${this.items.length} items`}async next(){if(this.trav>=this.items.length)return{value:null,done:!0};let e=this.items[this.trav];return this.trav++,{value:eX(e),done:!1}}},aX=class extends En{constructor(e){super(),this.nextFn=e}summary(){return"Function call"}async next(){try{return this.nextFn()}catch(e){throw e.message=`Error thrown while iterating through a dataset: ${e.message}`,e}}},oX=class extends En{constructor(e){super(),this.upstream=e,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Serial`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){return this.upstream.next()}},iX=class extends En{constructor(e,t){super(),this.upstream=e,this.maxCount=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Skip`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.count++<this.maxCount;){let e=await this.upstream.next();if(e.done)return e;Q(e.value)}return this.upstream.next()}},lX=class extends En{constructor(e,t){super(),this.upstream=e,this.maxCount=t,this.count=0}summary(){return`${this.upstream.summary()} -> Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},uX=class extends En{constructor(e,t,n=!0){super(),this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=n,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length<this.batchSize;){let t=await this.upstream.next();if(t.done)return this.enableSmallLastBatch&&e.length>0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},cX=class extends En{constructor(e,t){super(),this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;Q(e.value)}}},dX=class extends En{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=zr.getTensorsInContainer(e.value),n=this.transform(e.value),s=zr.getTensorsInContainer(n);for(let r of t)zr.isTensorInList(r,s)||r.dispose();return{value:n,done:!1}}},pX=class extends En{constructor(e,t){super(),this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}},N7=class extends En{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=zr.getTensorsInContainer(e.value),n=await this.transform(e.value),s=zr.getTensorsInContainer(n);for(let r of t)zr.isTensorInList(r,s)||r.dispose();return{value:n,done:!1}}},Vx=class extends En{constructor(){super(),this.outputQueue=new Bx,this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.outputQueue.length()===0;)if(!await this.pump())return{value:null,done:!0};return{value:this.outputQueue.shift(),done:!1}}},hX=class extends Vx{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){let e=await this.upstream.next();if(e.done)return!1;let t=zr.getTensorsInContainer(e.value),n=this.transform(e.value),s=zr.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let r of t)zr.isTensorInList(r,s)||r.dispose();return!0}},IS=class extends En{constructor(e,t){super(),this.baseErrorHandler=t,this.lastRead=null,this.iterator=null,this.moreIterators=e}summary(){return"TODO: fill in upstream of chained summaries -> Chained"}async next(){return this.lastRead=this.readFromChain(this.lastRead),this.lastRead}async readFromChain(e){if(await e,this.iterator==null){let n=await this.moreIterators.next();if(n.done)return{value:null,done:!0};this.iterator=n.value,this.baseErrorHandler!=null&&(this.iterator=this.iterator.handleErrors(this.baseErrorHandler))}let t=await this.iterator.next();return t.done?(this.iterator=null,this.readFromChain(e)):t}},eo;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(eo||(eo={}));var fX=class extends En{constructor(e,t=eo.FAIL){super(),this.iterators=e,this.mismatchMode=t,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(e){await e;let t=0,n=0;function s(a){return a instanceof En?{value:a.next().then(i=>(t++,i.done&&n++,i.value)),recurse:!1}:{value:null,recurse:!0}}let r=await wS(this.iterators,s);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case eo.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case eo.SHORTEST:return{value:null,done:!0};case eo.LONGEST:default:}return this.count++,{value:r,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},CS=class extends En{constructor(e,t){super(),this.upstream=e,this.bufferSize=t,this.buffer=new kS(t)}summary(){return`${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()}},mX=class extends CS{constructor(e,t,n){super(e,t),this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=Kq.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}}},cd=class{constructor(){this.size=null}batch(e,t=!0){let n=this;v.assert(e>0,()=>`batchSize needs to be positive, but it is
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`).map(s=>(s.endsWith("\r")&&(s=s.slice(0,-1)),s))}},sm='"',ip=Symbol("out"),E7=Symbol("field"),rm=Symbol("quote"),N3=Symbol("quoteafterquote"),R7=Symbol("quoteinquote"),NS=class extends cd{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 TS(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=ip;for(let o=0;o<r;o++)switch(a){case ip:switch(e.charAt(o)){case sm:s=o+1,a=rm;break;case this.delimiter:if(s=o+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),a=ip;break;default:a=E7,s=o;break}break;case E7:switch(e.charAt(o)){case this.delimiter:n.push(e.substring(s,o)),a=ip,s=o+1;break;default:}break;case rm:switch(e.charAt(o)){case sm:a=N3;break;default:}break;case N3:switch(e.charAt(o)){case this.delimiter:n.push(e.substring(s,o-1)),a=ip,s=o+1;break;case sm:a=rm;break;default:a=R7;break}break;case R7:switch(e.charAt(o)){case sm:a=rm;break;default:}break;default:}if(a===N3?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}},ES=class extends En{constructor(e){super(),this.microphoneConfig=e,this.isClosed=!1,this.fftSize=e.fftSize||1024;let t=Math.log2(this.fftSize);if(this.fftSize<0||t<4||t>14||!Number.isInteger(t))throw new Error(`Invalid fftSize: it must be a power of 2 between 2 to 4 and 2 to 14, but got ${this.fftSize}`);if(this.numFrames=e.numFramesPerSpectrogram||43,this.sampleRateHz=e.sampleRateHz,this.columnTruncateLength=e.columnTruncateLength||this.fftSize,this.audioTrackConstraints=e.audioTrackConstraints,this.smoothingTimeConstant=e.smoothingTimeConstant||0,this.includeSpectrogram=e.includeSpectrogram!==!1,this.includeWaveform=e.includeWaveform===!0,!this.includeSpectrogram&&!this.includeWaveform)throw new Error("Both includeSpectrogram and includeWaveform are false. At least one type of data should be returned.")}summary(){return"microphone"}static async create(e={}){if(!H().get("IS_BROWSER"))throw new Error("microphone API is only supported in browser environment.");let t=new ES(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),Xe(n,t)}},RS=class extends En{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=Ot([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=mr([a,r,i,o],[1,4])}else this.cropBox=mr([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(!H().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 RS(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: ${this.webcamConfig.facingMode}. 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VS=pn((e,t)=>e===t?1:0),US=Rn(Cl,VS,null,"bool"),GX={kernelName:Cl,backendName:"cpu",kernelFunc:US},GS=Ai(e=>Math.exp(e)),HS=dd($o,GS,"float32"),HX={kernelName:$o,backendName:"cpu",kernelFunc:HS},jS=Ai(e=>Math.expm1(e)),jX=dd(Nl,jS),qX={kernelName:Nl,backendName:"cpu",kernelFunc:jX},qS=Ai(e=>Math.floor(e)),XX=dd(Po,qS),KX={kernelName:Po,backendName:"cpu",kernelFunc:XX};function XS(e,t,n,s,r,a,o,i,l){let u=Ue([s,a],n);for(let c=0;c<s;c++){let p=[],d=0;for(let h=0;h<r;h++){let f=e[c*r+h];d+=f*o[h],p.push(f)}if(d<0||d>=l/a)throw new Error(`Invalid indices: ${p} does not index into ${i}`);for(let h=0;h<a;h++)u.values[c*a+h]=t.get(...t.indexToLoc(d*a+h))}return u}function KS(e,t,n){let s=Ue(n,e.dtype);for(let r=0;r<s.size;++r){let o=s.indexToLoc(r).slice(),i=o[0],l=o[2],u=t.locToIndex([i,l]);o[2]=t.values[u];let c=e.locToIndex(o);0<=c&&c<e.values.length&&(s.values[r]=e.values[c])}return s}var ZS=pn((e,t)=>e>t?1:0),ZX=Rn(Dl,ZS,null,"bool"),YX={kernelName:Dl,backendName:"cpu",kernelFunc:ZX},YS=pn((e,t)=>e>=t?1:0),JX=Rn(Mo,YS,null,"bool"),QX={kernelName:Mo,backendName:"cpu",kernelFunc:JX},JS=pn((e,t)=>e<t?1:0),eK=Rn(Pl,JS,null,"bool"),tK={kernelName:Pl,backendName:"cpu",kernelFunc:eK},QS=pn((e,t)=>e<=t?1:0),nK=Rn(Fl,QS,null,"bool"),sK={kernelName:Fl,backendName:"cpu",kernelFunc:nK};function eI(e,t,n){let s=(t-e)/(n-1),r=v.makeZerosTypedArray(n,"float32");r[0]=e;for(let a=1;a<r.length;a++)r[a]=r[a-1]+s;return r}var tI=Ai(e=>Math.log(e)),rK=dd(Bo,tI),aK={kernelName:Bo,backendName:"cpu",kernelFunc:rK};function nI(e,t,n,s){let r=v.getTypedArrayFromDType(s,v.sizeFromShape(n));for(let a=0;a<r.length;++a){let o=a*t,i=e[o];for(let l=0;l<t;++l){let u=e[o+l];(Number.isNaN(u)||u>i)&&(i=u)}r[a]=i}return r}var sI=pn((e,t)=>Math.max(e,t)),oK=Rn(Vo,sI),iK={kernelName:Vo,backendName:"cpu",kernelFunc:oK},rI=pn((e,t)=>Math.min(e,t)),lK=Rn(jo,rI),uK={kernelName:jo,backendName:"cpu",kernelFunc:lK},Xx=pn((e,t)=>e*t),cK=Hx((e,t,n,s)=>({real:e*n-t*s,imag:e*s+t*n})),_2=Rn(Xo,Xx,cK),dK={kernelName:Xo,backendName:"cpu",kernelFunc:_2};function aI(e,t,n){let s=v.createScalarValue(-1,n);return Xx([],t,s,e,n)}function pK(e){let{inputs:t,backend:n}=e,{x:s}=t;Ne(s,"neg");let r=n.data.get(s.dataId).values,[a,o]=aI(r,s.shape,s.dtype);return n.makeTensorInfo(o,s.dtype,a)}var hK={kernelName:zl,backendName:"cpu",kernelFunc:pK},oI=pn((e,t)=>e!==t?1:0),fK=Rn(Ll,oI,null,"bool"),mK={kernelName:Ll,backendName:"cpu",kernelFunc:fK};function Kx(e,t,n,s,r){let a=t.length,o=v.sizeFromShape(t),i=v.computeStrides(t),l=v.computeStrides(r),u=v.getTypedArrayFromDType(n,v.sizeFromShape(r));for(let c=0;c<o;++c){let p=v.indexToLoc(c,a,i),d=new Array(p.length);for(let f=0;f<d.length;f++)d[f]=p[s[f]];let 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t=this.getRowPartitionTensor(e-1);switch(this.getRowPartitionTypeByDimension(e-1)){case dr.VALUE_ROWIDS:return yy.getMaxWidthValueRowID(t);case dr.ROW_SPLITS:return yy.getMaxWidthRowSplit(t);default:throw new Error(`Cannot handle partition type ${dr[this.getRowPartitionTypeByDimension(e-1)]}`)}}static getMaxWidthRowSplit(e){let t=e.length;if(t===0||t===1)return 0;let n=0;for(let s=0;s<t-1;++s){let r=e[s+1]-e[s];r>n&&(n=r)}return n}static getMaxWidthValueRowID(e){let t=e.length;if(t===0)return 0;let n=0,s=e[0],r=0;for(let a=1;a<t;++a){let o=e[a];o!==s&&(s=o,r=Math.max(a-n,r),n=a)}return Math.max(t-n,r)}tensorShapeFromTensor(e,t,n=!0){if(t.length===0){if(e[0]===-1)return[];throw new Error("The only valid scalar shape tensor is the fully unknown shape specified as -1.")}return D7(e,n)}calculateOutputSize(e){let t=this.valuesShape,n=this.defaultValueShape;T.validateDefaultValueShape(n,t);let s=this.tensorShapeFromTensor(this.shape,this.shapeShape),a=T.combineRaggedTensorToTensorShapes(this.raggedRank,s,t);a[0]<0&&(a[0]=e);for(let o=1;o<=this.raggedRank;++o)a[o]<0&&(a[o]=this.getMaxWidth(o));return a}calculateFirstParentOutputIndex(e,t,n){let s=Math.min(e,n),r=[],a=0;for(let o=0;o<s;++o,a+=t)r.push(a);for(let o=s;o<e;++o)r.push(-1);return v.assert(r.length===e,()=>"Final length of result must be equal to firstDimension."),r}calculateOutputIndexRowSplit(e,t,n,s){let r=e.length,a=[];for(let o=0;o<r-1;++o){let i=e[o+1]-e[o],l=Math.min(s,i),u=t[o];u===-1&&(l=0);for(let c=0;c<l;++c)a.push(u),u+=n;for(let c=0;c<i-l;++c)a.push(-1)}if(r>0&&a.length!==e[r-1])throw new Error("Invalid row split size.");return a}calculateOutputIndexValueRowID(e,t,n,s){let r=e.length,a=[];if(r===0)return[];let o=0,i=e[0];if(i>=t.length)throw new Error(`Got currentValueRowId=${i}, which is not less than ${t.length}`);let l=t[i];a.push(l);for(let u=1;u<r;++u){let c=e[u];if(c===i)l>=0&&(++o,o<s?l+=n:l=-1);else{if(o=0,i=c,c>=t.length)throw new Error(`Got nextValueRowId=${c} which is not less than ${t.length}`);l=t[c]}a.push(l)}if(a.length!==e.length)throw new Error("Invalid row ids.");return a}calculateOutputIndex(e,t,n,s){let r=this.getRowPartitionTensor(e),a=this.getRowPartitionTypeByDimension(e);switch(a){case dr.VALUE_ROWIDS:return this.calculateOutputIndexValueRowID(r,t,n,s);case dr.ROW_SPLITS:if(r.length-1>t.length)throw new Error(`Row partition size is greater than output size: ${r.length-1} > ${t.length}`);return this.calculateOutputIndexRowSplit(r,t,n,s);default:throw new Error(`Unsupported partition type: ${dr[a]}`)}}getFirstDimensionSize(){let e=this.rowPartitionValues[0];if(this.rowPartitionTypes.length===0)throw new Error("No row_partition_types given.");let t=this.rowPartitionTypes[0];switch(t){case dr.FIRST_DIM_SIZE:return e[0];case dr.VALUE_ROWIDS:throw new Error("Cannot handle VALUE_ROWIDS in first dimension.");case 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fl(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,size:o}=s;Ne(r,"slice");let[i,l]=jt.parseSliceParams(r,a,o);jt.assertParamsValid(r,i,l);let u=n.data.get(r.dataId).values,c=Um(u,i,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,c)}var kK={kernelName:Yl,backendName:"cpu",kernelFunc:fl};function dI(e,t,n,s,r,a,o){let i=t[0],l=a[0],u=new Array(l),c=new Array(i),p=t[1];if(l===0){if(i!==0)throw new Error(T.getSparseFillEmptyRowsIndicesDenseShapeMismatch(i));let g=v.getArrayFromDType(n,0),y=v.getArrayFromDType(r,0);return[g,[0,p],y,u,c]}let d=!0,h=0,f=new Array(l).fill(0);for(let g=0;g<i;++g){let y=e[g*p];if(y<0)throw new Error(T.getSparseFillEmptyRowsNegativeIndexErrorMessage(g,y));if(y>=l)throw new Error(T.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(g,y,l));++f[y],d=d&&y>=h,h=y}let m=!0;for(let g=0;g<l;++g){let y=f[g]===0;u[g]=y,m=m&&!y,f[g]=Math.max(f[g],1),g>0&&(f[g]+=f[g-1])}if(m&&d){let g=e,y=s;for(let x=0;x<i;++x)c[x]=x;return[g,[i,p],y,u,c]}else{let 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n9(e){if(Am==null){let t=Ur(e);Am=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,Am)}function s9(e){if(e===0)return 0;let t,n=Ur(e);return er(n,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:er(n,"EXT_disjoint_timer_query")?t=1:t=0,t}function er(e,t){return e.getExtension(t)!=null}function wy(e){try{if(Ur(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function r9(e){if(e===0)return!1;let t=Ur(e);if(e===1){if(!er(t,"OES_texture_float"))return!1}else if(!er(t,"EXT_color_buffer_float"))return!1;return ky(t)}function a9(e){if(e===0)return!1;let t=Ur(e);if(e===1){if(!er(t,"OES_texture_float")||!er(t,"WEBGL_color_buffer_float"))return!1}else{if(er(t,"EXT_color_buffer_float"))return ky(t);let s="EXT_color_buffer_half_float";if(er(t,s)){let r=t.getExtension(s);return rte(t,r)}return!1}return ky(t)}function ky(e){let t=ab(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 rte(e,t){let n=ab(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 o9(e){return e!==2?!1:Ur(e).fenceSync!=null}function hd(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=H();Pe.registerFlag("HAS_WEBGL",()=>Pe.getNumber("WEBGL_VERSION")>0);Pe.registerFlag("WEBGL_VERSION",()=>wy(2)?2:wy(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",()=>t9(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>n9(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=Pe.getNumber("WEBGL_VERSION");return e===0?0:s9(e)});Pe.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Pe.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!dh.isMobile());Pe.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>r9(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>Pe.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:Pe.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));Pe.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>a9(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_FENCE_API_ENABLED",()=>o9(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>Pe.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);Pe.registerFlag("WEBGL_DELETE_TEXTURE_THRESHOLD",()=>-1,e=>{if(e<0&&e!==-1)throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got ${e}.`)});Pe.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>dh.isMobile()?1:-1,e=>{if(e<0&&e!==-1)throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${e}.`)});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);Pe.registerFlag("WEBGL_EXP_CONV",()=>!1);Pe.registerFlag("SOFTWARE_WEBGL_ENABLED",()=>Pe.getBool("IS_TEST"));function hs(){let e,t,n,s,r,a,o,i,l,u;return H().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 Au(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 $2(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}; ${i};`}).join("")}function ate(e,t){let n=e.length,s=e.map(a=>`${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 ote(e,t,n="index"){let s=e.map((a,o)=>o),r=ate(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 ib(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 lb(){return`
  int getFlatIndex(ivec3 coords) {
    return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
  }
`}var i9=`
  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:l9}=T;function ite(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}=ub(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?`[${h.arrayIndex}]`:""};`)});let r=s.join(`
`),a=e.map(h=>lte(h,t,n.packedInputs,n.enableShapeUniforms)).join(`
`),o=t.texShape,i=hs(),l=dte(i),u,c,p=fte(i);return t.isPacked?(u=ute(t.logicalShape,o,n.enableShapeUniforms),c=hte(i)):(u=cte(t.logicalShape,o,n.enableShapeUniforms),c=pte(i)),n.packedInputs&&(p+=Ate),[p,l,c,r,u,a,n.userCode].join(`
`)}function fd(e,t=!1){let n=e.shapeInfo.logicalShape;switch(n.length){case 0:return Rte(e,t);case 1:return Dte(e,t);case 2:return Pte(e,t);case 3:return Ote(e,t);case 4:return zte(e,t);case 5:return Lte(e);case 6:return Bte(e);default:throw new Error(`${n.length}-D input sampling is not yet supported`)}}function u9(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return Ete(e);case 1:return _te(e,t);case 2:return $te(e,t);case 3:return Fte(e,t);default:return Mte(e,t)}}function lte(e,t,n=!1,s){let r="";n?r+=u9(e,s):r+=fd(e,s);let a=e.shapeInfo.logicalShape,o=t.logicalShape;return a.length<=o.length&&(n?r+=Wte(e,t):r+=Vte(e,t)),r}function ute(e,t,n){switch(e.length){case 0:return c9();case 1:return xte(e,t,n);case 2:return Tte(e,t,n);case 3:return vte(e,t,n);default:return kte(e,t,n)}}function cte(e,t,n){switch(e.length){case 0:return c9();case 1:return bte(e,t,n);case 2:return Nte(e,t,n);case 3:return wte(e,t,n);case 4:return Ste(e,t,n);case 5:return Ite(e,t);case 6:return Cte(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function dte(e){return`
    float sampleTexture(sampler2D textureSampler, vec2 uv) {
      return ${e.texture2D}(textureSampler, uv).r;
    }
  `}function pte(e){return`
    void setOutput(float val) {
      ${e.output} = vec4(val, 0, 0, 0);
    }
  `}function hte(e){return`
    void setOutput(vec4 val) {
      ${e.output} = val;
    }
  `}function fte(e){return`${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);
    }

    ${mte}
    ${gte}
    ${yte}
  `}var mte=`
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);
}
`,gte=`
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);
}
`,yte=`
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);
}
`,Ate=`
  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 c9(){return`
    int getOutputCoords() {
      return 0;
    }
  `}function xte(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 bte(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 vte(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 wte(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;
    ${$2(["r","c","d"],e)}
    return ivec3(r, c, d);
  }
`;let s=Au(["r","c","d"],e);return`
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      ${s}
      return ivec3(r, c, d);
    }
  `}function kte(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 Ste(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;
      ${$2(["r","c","d","d2"],e)}
      return ivec4(r, c, d, d2);
    }
  `;let s=Au(["r","c","d","d2"],e);return`
    ivec4 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      ${s}
      return ivec4(r, c, d, d2);
    }
  `}function Ite(e,t){let n=Au(["r","c","d","d2","d3"],e);return`
    ivec5 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
                             ${t[1]}));

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

      ${n}

      ivec5 outShape = ivec5(r, c, d, d2, d3);
      return outShape;
    }
  `}function Cte(e,t){let n=Au(["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 Tte(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 Nte(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 * ${e[1]};
      return ivec2(r, c);
    }
  `}function xu(e){return`offset${e}`}function Ete(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),s=hs();return`
    vec4 ${n}() {
      return ${s.texture2D}(${t}, halfCR);
    }
  `}function Rte(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=xu(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 _te(e,t){let n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),r=e.shapeInfo.texShape,a=hs();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 Dte(e,t){let n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return`
      float ${s}(int index) {
        ${md(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=xu(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 $te(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=hs();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 Pte(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=gd(e,l),h=["row","col"];return`
      ${fd(d,t)}
      float ${r}(int row, int col) {
        return ${r}(${yd(h,i)});
      }
    `}if(e.shapeInfo.isUniform)return`
      float ${r}(int row, int col) {
        int index = round(dot(vec2(row, col), vec2(${n[1]}, 1)));
        ${md(e)}
      }
    `;let u=a[0],c=a[1],p=xu(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 Fte(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=gd(e,d),m=["b","row","col"];return`
        ${u9(f,t)}
        vec4 ${r}(int b, int row, int col) {
          return ${r}(${yd(m,h)});
        }
      `}let i=hs();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 Ote(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=gd(e,u),g=["row","col","depth"];return`
        ${fd(m,t)}
        float ${r}(int row, int col, int depth) {
          return ${r}(${yd(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)));
        ${md(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=xu(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 Mte(e,t){let n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),r=hs();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 zte(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=gd(e,l),A=["row","col","depth","depth2"];return`
      ${fd(x,t)}
      float ${r}(int row, int col, int depth, int depth2) {
        return ${r}(${yd(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)));
        ${md(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=xu(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 Lte(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=gd(e,l),g=["row","col","depth","depth2","depth3"];return`
      ${fd(m)}
      float ${s}(int row, int col, int depth, int depth2, int depth3) {
        return ${s}(${yd(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;
        ${md(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=xu(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 Bte(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=gd(e,r),y=["row","col","depth","depth2","depth3","depth4"];return`
      ${fd(g)}
      float ${s}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        return ${s}(${yd(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)));
        ${md(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=xu(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 md(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 ${t}[i];
      }
    }
  `}function Wte(e,t){let n=e.name,s=n.charAt(0).toUpperCase()+n.slice(1),r="get"+s+"AtOutCoords",a=e.shapeInfo.logicalShape.length,o=t.logicalShape.length,i=l9(e.shapeInfo.logicalShape,t.logicalShape),l=kt(o),u=o-a,c,p=["x","y","z","w","u","v"];a===0?c="":o<2&&i.length>=1?c="coords = 0;":c=i.map(x=>`coords.${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 Vte(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=kt(l),c=l9(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 kt(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 ${e} is not yet supported`)}function ub(e,t,n){let{newShape:s,keptDims:r}=v.squeezeShape(t),a=t.length,o=e&&a===3&&t[0]===1,i=o?t.slice(1):s,l=!e&&a>1&&!v.arraysEqual(t,n)&&s.length<a||o;return{useSqueezeShape:l,uniformShape:l?i:t,keptDims:r}}function gd(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function yd(e,t){return t.map(n=>e[n]).join(", ")}function Ute(e,t,n,s){let r=n.map((c,p)=>{let d={logicalShape:c.shape,texShape:c.isUniform?null:c.texData.texShape,isUniform:c.isUniform,isPacked:c.isUniform?!1:c.texData.isPacked,flatOffset:null};return c.texData!=null&&c.texData.slice!=null&&c.texData.slice.flatOffset>0&&(d.flatOffset=c.texData.slice.flatOffset),{name:t.variableNames[p],shapeInfo:d}}),a=r.map(c=>c.shapeInfo),o={logicalShape:s.shape,texShape:s.texData.texShape,isUniform:!1,isPacked:s.texData.isPacked,flatOffset:null},i=ite(r,o,t),l=BI(e.gl,i),u=e.createProgram(l);return H().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:l,source:i,webGLProgram:u,inShapeInfos:a,outShapeInfo:o,uniformLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,inShapesLocations:null,inTexShapesLocations:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:Object.assign({program:t,fragmentShader:l,source:i,webGLProgram:u,inShapeInfos:a,outShapeInfo:o},d9(e,t,u))}function d9(e,t,n){let s={},r={},a={},o=[],i,l,u,c=null,p=null;p=e.getUniformLocation(n,"NAN",!1),H().getNumber("WEBGL_VERSION")===1&&(c=e.getUniformLocation(n,"INFINITY",!1));let d=!1;for(let h=0;h<t.variableNames.length;h++){let f=t.variableNames[h];s[f]=e.getUniformLocation(n,f,d),s[`offset${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 F7(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 ${l} must match`)})}function Gte(e,t,n,s,r){t.program.enableShapeUniforms||(F7(t.inShapeInfos,n),F7([t.outShapeInfo],[s]));let a=s.texData.texture,o=s.texData.texShape;s.texData.isPacked?e.setOutputPackedMatrixTexture(a.texture,o[0],o[1]):e.setOutputMatrixTexture(a.texture,o[0],o[1]),e.setProgram(t.webGLProgram),H().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((l,u)=>{let c=t.program.variableNames[u],p=t.uniformLocations[c],d=t.uniformLocations[`offset${c}`],h=t.inShapesLocations[`${c}Shape`],f=t.inTexShapesLocations[`${c}TexShape`];if(h){let{uniformShape:m}=ub(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 ${l.type} is not supported yet.`)}),e.executeProgram()}function Hte(e,t,n){let s="";t.concat(n).forEach(o=>{let i=o.texData!=null&&o.texData.slice!=null&&o.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!o.isUniform){let l=o.texData.texShape,{useSqueezeShape:u,uniformShape:c,keptDims:p}=ub(e.packedInputs,o.shape,l),d="",h="",f="";if(c.length===1&&e.packedInputs){let w=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];d=`${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]}_${w[w.length-1]===l[1]}`}let m=o.shape.length,g=c.length===2&&v.arraysEqual(o.shape,l),y=v.sizeFromShape(o.shape)===1,x=T.getBroadcastDims(o.shape,n.shape),A=!e.packedInputs&&m===n.shape.length&&v.arraysEqual(l,n.texData.texShape),b=e.packedInputs||c.length>2?"":`${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+`${H().getNumber("WEBGL_VERSION")}`,a}function fs(e){return H().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var jte=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=Op.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=hs();this.outputShape=e,this.enableShapeUniforms=fs(this.outputShape.length),this.userCode=`
      ivec3 outCoordsFromFlatIndex(int index) {
        ${this.enableShapeUniforms?$2(["r","c","d"],e):Au(["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;
      }
    `}},qte=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=Op.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=hs();this.outputShape=e,this.enableShapeUniforms=fs(this.outputShape.length),this.userCode=`
      ivec3 outCoordsFromFlatIndex(int index) {
        ${this.enableShapeUniforms?$2(["r","c","d"],e):Au(["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;
      }
    `}},Xte=class{constructor(e){this.variableNames=["A"],this.outTexUsage=Qs.DOWNLOAD;let t=hs();this.outputShape=e,this.userCode=`
      ${i9}

      void main() {
        float x = getAAtOutCoords();
        ${t.output} = encode_float(x);
      }
    `}},Kte=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Qs.DOWNLOAD;let t=hs();this.outputShape=e,this.userCode=`
      ${i9}

      void main() {
        ivec3 coords = getOutputCoords();
        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
        ${t.output} = encode_float(x);
      }
    `}},Zte=class{constructor(e,t=!1){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=hs();this.outputShape=e,this.enableShapeUniforms=fs(this.outputShape.length);let s="result";t&&(s="floor(result * 255. + 0.5)"),this.userCode=`
      ${this.enableShapeUniforms?lb():ib(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.);
      }
    `}},Yte=class{constructor(e,t=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=hs();this.outputShape=e,this.enableShapeUniforms=fs(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?lb():ib(e)}

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

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

          ${s}

          ${n.output} = ${r};
        }
    `}},p9={};qe(p9,{bindVertexProgramAttributeStreams:()=>v9,createBufferFromOutputTexture:()=>S9,createFloat16MatrixTexture:()=>y9,createFloat16PackedMatrixTexture:()=>b9,createFloat32MatrixTexture:()=>g9,createIndexBuffer:()=>m9,createPackedMatrixTexture:()=>x9,createUnsignedBytesMatrixTexture:()=>A9,createVertexBuffer:()=>f9,createVertexShader:()=>h9,downloadByteEncodedFloatMatrixFromOutputTexture:()=>C9,downloadFloat32MatrixFromBuffer:()=>I9,downloadMatrixFromPackedOutputTexture:()=>N9,downloadPackedMatrixFromBuffer:()=>T9,getInternalFormatForFloat16MatrixTexture:()=>db,getInternalFormatForFloat16PackedMatrixTexture:()=>fb,getInternalFormatForFloat32MatrixTexture:()=>cb,getInternalFormatForPackedMatrixTexture:()=>hb,getInternalFormatForUnsignedBytesMatrixTexture:()=>pb,uploadDenseMatrixToTexture:()=>w9,uploadPixelDataToTexture:()=>k9});function h9(e){let t=hs(),n=`${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 LI(e,n)}function f9(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 UI(e,t)}function m9(e){let t=new Uint16Array([0,1,2,2,1,3]);return GI(e,t)}function Hh(e,t,n,s,r,a){jI(t,n);let o=HI(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)),H().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 cb(e){return e.internalFormatFloat}function g9(e,t,n,s){let[r,a]=Gh(t,n);return Hh(e,r,a,cb(s),s.textureFormatFloat,e.FLOAT)}function db(e){return e.internalFormatHalfFloat}function y9(e,t,n,s){let[r,a]=Gh(t,n);return Hh(e,r,a,db(s),s.textureFormatFloat,s.textureTypeHalfFloat)}function pb(e){return e.downloadTextureFormat}function A9(e,t,n,s){let[r,a]=Gh(t,n);return Hh(e,r,a,pb(s),e.RGBA,e.UNSIGNED_BYTE)}function hb(e){return e.internalFormatPackedFloat}function x9(e,t,n,s){let[r,a]=pd(t,n);return Hh(e,r,a,hb(s),e.RGBA,e.FLOAT)}function fb(e){return e.internalFormatPackedHalfFloat}function b9(e,t,n,s){let[r,a]=pd(t,n);return Hh(e,r,a,fb(s),e.RGBA,s.textureTypeHalfFloat)}function v9(e,t,n){return Ie(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),by(e,t,"clipSpacePos",n,3,20,0)&&by(e,t,"uv",n,2,20,12)}function w9(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),H().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 k9(e,t,n){Ie(e,()=>e.bindTexture(e.TEXTURE_2D,t)),n.data instanceof Uint8Array?H().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)):H().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 S9(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 I9(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 C9(e,t,n,s){let[r,a]=Gh(t,n),o=4,i=new Uint8Array(qee(t*n,o));return Ie(e,()=>e.readPixels(0,0,r,a,s.downloadTextureFormat,e.UNSIGNED_BYTE,i)),new Float32Array(i.buffer)}function T9(e,t,n,s,r,a,o,i){let l=e,u=new Float32Array(Xee(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 N9(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 lc=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=H().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,D2(t,e)):this.gl=Ur(t);let n="WEBGL_color_buffer_float",s="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),H().getNumber("WEBGL_VERSION")===1){let r="OES_texture_float",a="OES_texture_half_float";if(this.textureFloatExtension=fp(this.gl,r),er(this.gl,a))this.textureHalfFloatExtension=fp(this.gl,a);else if(H().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(n),er(this.gl,s))this.colorBufferHalfFloatExtension=fp(this.gl,s);else if(H().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(n="EXT_color_buffer_float",er(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(er(this.gl,s))this.colorBufferHalfFloatExtension=this.gl.getExtension(s);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=f9(this.gl),this.indexBuffer=m9(this.gl),this.framebuffer=qI(this.gl),this.textureConfig=ab(this.gl,this.textureHalfFloatExtension)}get debug(){return H().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(),g9(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),y9(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),A9(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),k9(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,s){this.throwIfDisposed(),w9(this.gl,e,t,n,s,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),b9(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),x9(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(vy(this.gl,this.framebuffer),this.outputTexture=null),Ie(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>C9(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,s,r,a){return T9(this.gl,e,t,n,s,r,a,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return I9(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let s=S9(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(H().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 H().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,H().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>N9(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl;this.vertexShader==null&&(this.vertexShader=h9(t));let n=WI(t);return Ie(t,()=>t.attachShader(n,this.vertexShader)),Ie(t,()=>t.attachShader(n,e)),VI(t,n),this.debug&&fm(t,n),this.vertexAttrsAreBound||(this.setProgram(n),this.vertexAttrsAreBound=v9(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&&fm(this.gl,this.program),Ie(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?KI(this.gl,e,t):ZI(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(),YI(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[s,r]=pd(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&&fm(this.gl,this.program),mp(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=fp(this.gl,H().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(H().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(H().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,H().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,H().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=Jte(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(),mm(this.gl,e,this.framebuffer),this.debug&&mp(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(mm(this.gl,this.outputTexture,this.framebuffer),this.debug&&mp(this.gl)):vy(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;mm(s,e,this.framebuffer),this.debug&&mp(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 Jte(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{addImpl:Qte,bincountImpl:E9,bincountReduceImpl:ene,castImpl:tne,ceilImpl:nne,concatImpl:sne,equalImpl:rne,expImpl:ane,expm1Impl:one,floorImpl:ine,gatherNdImpl:lne,gatherV2Impl:une,greaterImpl:cne,greaterEqualImpl:dne,lessImpl:pne,lessEqualImpl:hne,linSpaceImpl:fne,logImpl:mne,maxImpl:gne,maximumImpl:yne,minimumImpl:Ane,multiplyImpl:xne,negImpl:bne,notEqualImpl:vne,prodImpl:wne,raggedTensorToTensorImpl:kne,rangeImpl:Sne,rsqrtImpl:Ine,scatterImpl:Cne,sigmoidImpl:Tne,simpleAbsImpl:R9,sliceImpl:Nne,sparseFillEmptyRowsImpl:Ene,sparseReshapeImpl:Rne,sparseSegmentReductionImpl:_9,sqrtImpl:_ne,stridedSliceImpl:Dne,stringNGramsImpl:$ne,stringSplitImpl:Pne,stringToHashBucketFastImpl:Fne,subImpl:One,tileImpl:Mne,topKImpl:zne,transposeImpl:mb,uniqueImpl:Lne}=Gx;function D9(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function us(e,t){return t===1?[e]:D9(e,t)}function Bne(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 Wne=class{constructor(e){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.enableShapeUniforms=fs(this.outputShape.length),this.rank===0)this.userCode=`
        void main() {
          setOutput(vec4(getA(), 0., 0., 0.));
        }
      `;else{let t=us("rc",this.rank),n=kt(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]})`}},$9=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=fs(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=`
      ${Vne(t,this.enableShapeUniforms)}
      ${this.enableShapeUniforms?lb():ib(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 Vne(e,t){return`
    ivec3 inputCoordsFromReshapedOutCoords(int index) {
      ${t?ote(["r","c","d"],"inputShape"):Au(["r","c","d"],e)}
      return ivec3(r, c, d);
    }
  `}var Une=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let s=M7(t,n),r=z7(e,s,n);r in this.freeTextures||(this.freeTextures[r]=[]),r in this.usedTextures||(this.usedTextures[r]=[]);let a=O7(e,s,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[r].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=a,this.log();let i=this.freeTextures[r].shift();return this.usedTextures[r].push(i),i}let o;return s===Fn.PACKED_2X2_FLOAT32?o=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):s===Fn.PACKED_2X2_FLOAT16?o=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):s===Fn.UNPACKED_FLOAT32?o=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):s===Fn.UNPACKED_FLOAT16?o=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):s===Fn.PACKED_4X1_UNSIGNED_BYTE&&(o=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[r].push(o),this.numUsedTextures++,this._numBytesAllocated+=a,this.log(),o}releaseTexture(e,t,n,s){if(this.freeTextures==null)return;let r=M7(n,s),a=z7(t,r,s);a in this.freeTextures||(this.freeTextures[a]=[]);let o=O7(t,r,this.gpgpu.gl,this.gpgpu.textureConfig,s),i=H().get("WEBGL_DELETE_TEXTURE_THRESHOLD");i!==-1&&this._numBytesAllocated>i?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=o):(this.freeTextures[a].push(e),this.numFreeTextures++,this._numBytesFree+=o),this.numUsedTextures--;let l=this.usedTextures[a],u=l.indexOf(e);if(u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(u,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${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 Gne(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 O7(e,t,n,s,r){let a=Hne(t,s),o;if(r){let[l,u]=pd(e[0],e[1]);o=l*u}else{let[l,u]=Gh(e[0],e[1]);o=l*u}let i=Gne(n,a);return o*i}function Hne(e,t){switch(e){case Fn.PACKED_2X2_FLOAT32:return hb(t);case Fn.PACKED_2X2_FLOAT16:return fb(t);case Fn.UNPACKED_FLOAT32:return cb(t);case Fn.UNPACKED_FLOAT16:return db(t);case Fn.PACKED_4X1_UNSIGNED_BYTE:return pb(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function jne(e){return H().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?Fn.PACKED_2X2_FLOAT32:Fn.UNPACKED_FLOAT32:e?Fn.PACKED_2X2_FLOAT16:Fn.UNPACKED_FLOAT16}function M7(e,t){if(e===Qs.UPLOAD)return Fn.PACKED_2X2_FLOAT32;if(e===Qs.RENDER||e==null)return jne(t);if(e===Qs.DOWNLOAD||e===Qs.PIXELS)return Fn.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function z7(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var Sa=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=fs(this.outputShape.length),this.userCode=`
      float unaryOperation(float x) {
        ${t}
      }

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

        setOutput(y);
      }
    `}},br="if (isnan(x)) return x;",qne="return x;",L7="return abs(x);",Xne="return (x >= 0.0) ? x : (exp(x) - 1.0);",Kne=br+`
  return (x < 0.0) ? 0.0 : x;
`,Zne=br+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,Yu="return x;",Yne="return 1.0 / (1.0 + exp(-1.0 * x));",Jne="return x;",Qne=`
  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;
`,ese=`
  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;
`,tse=`
  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;
`,nse="return 1.0 / (1.0 + exp(-1.0 * x));",el=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=fs(this.outputShape.length),this.userCode=`
      vec4 unaryOperation(vec4 x) {
        ${t}
      }

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

        setOutput(y);
      }
    `}},sse=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e,this.enableShapeUniforms=fs(this.outputShape.length);let t=e.length,n=us("rc",t),s=kt(t),r=Bne(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}));
      }
    `}},rse=Ar.whereImpl,ase=1e-7,ose=1e-4,lm={};function ise(e){return e in lm||(lm[e]={}),lm[e]}var lse=H().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),use=600;function cse(){return H().global.screen==null?1024:H().global.screen.height*H().global.screen.width*window.devicePixelRatio*use/1024/1024}var Ad=class extends Cc{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,!H().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let t;if(e!=null){if(e instanceof lc)t=e;else{let n=Ur(H().getNumber("WEBGL_VERSION"),e);t=new lc(n)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let n=Ur(H().getNumber("WEBGL_VERSION"));t=new lc(n),this.binaryCache=ise(H().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=t,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new Une(this.gpgpu),this.numMBBeforeWarning=cse(),this.texData=new Gp(this,Qt())}nextDataId(){return Ad.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}write(e,t,n){if((H().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||H().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(H().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 el(o,Yu):p=new Sa(o,Yu);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=T.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 el(s,Yu):h=new Sa(s,Yu);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(H().getBool("DEBUG")&&!H().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&H().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"&&H().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let h=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(h.texture.texture,...om(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=T.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)&&Qt().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 el(r,Yu):d=new Sa(r,Yu);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=Qt().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 Ue(e.shape,e.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return Ue(e.shape,e.dtype,t)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!MI(n))throw H().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 ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:s}=this.texData.get(e),r=v.sizeFromShape(t);if(H().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let p=this.decode(e),d=this.texData.get(p.dataId),h=this.gpgpu.downloadMatrixFromPackedTexture(d.texture.texture,...om(t)).subarray(0,r);return this.disposeIntermediateTensorInfo(p),h}let a=H().getBool("WEBGL_PACK")&&s===!0,o=a?gm(t):t,i=a?new Kte(o):new Xte(o),l=this.runWebGLProgram(i,[{shape:o,dtype:n,dataId:e}],"float32"),u=this.texData.get(l.dataId),c=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture.texture,u.texShape[0],u.texShape[1]).subarray(0,r);return this.disposeIntermediateTensorInfo(l),c}timerAvailable(){return H().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(e){let t=this.activeTimers,n=[],s=!1;this.programTimersStack==null?(this.programTimersStack=n,s=!0):this.activeTimers.push(n),this.activeTimers=n,e();let r=v.flatten(this.activeTimers.map(i=>i.query)).filter(i=>i!=null),a=v.flatten(this.activeTimers.map(i=>i.name)).filter(i=>i!=null);this.activeTimers=t,s&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(H().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let i=await Promise.all(r);o.kernelMs=v.sum(i),o.getExtraProfileInfo=()=>i.map((l,u)=>({name:a[u],ms:l})).map(l=>`${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 H().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return H().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(H().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=lse){return H().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){T.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return rse(e.shape,t)}packedUnaryOp(e,t,n){let s=new el(e.shape,t),r=this.compileAndRun(s,[e],n);return Qt().makeTensorFromTensorInfo(r)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let s=R9(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,s)}if(H().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,L7,e.dtype);let t=new Sa(e.shape,L7),n=this.compileAndRun(t,[e]);return Qt().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 Qt().makeTensorFromTensorInfo(this.makeTensorInfo(e,t,n),this)}unpackTensor(e){let t=new sse(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new Wne(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[ml(e.shape),...gl(e.shape)],s={dtype:e.dtype,shape:n,dataId:e.dataId},r=[ml(t),...gl(t)],a=new $9(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=gm(r),i;s?i=new qte(o):i=new jte(o);let l=!0,u=[t!=null?t:om(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===Op.DENSE){let g=a!=null?a:om(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)<=H().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&&!Mp(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=Hte(e,u,c),d=this.getAndSaveBinary(p,()=>Ute(this.gpgpu,e,u,c)),h=this.activeTimers!=null,f;h&&(f=this.startTimer()),H().get("ENGINE_COMPILE_ONLY")||Gte(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=H().get("WEBGL_FLUSH_THRESHOLD");if(m>0){let g=v.now();g-this.lastGlFlushTime>m&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=g)}if(!H().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||(H().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=Y(()=>{if(!H().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=H().getBool("DEBUG");H().set("DEBUG",!1);let t=this.abs(Te(1e-8)).dataSync()[0];if(H().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?ase:ose}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=e9(n,i),t.texShape=c),r!=null){let p=gm(n),d,h=c[1],f=c[0],m=r instanceof Uint8Array||r instanceof Uint8ClampedArray;(i||!m)&&([h,f]=pd(c[0],c[1])),i?d=new Yte(p,m):d=new Zte(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,H().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=dse(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 c5(),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?(ob(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}=d9(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}}};Ad.nextDataId=0;function dse(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 pse="3.20.0";function P9(){H().set("WEBGL_FORCE_F16_TEXTURES",!0)}dh.isBrowser()&&lu("webgl",()=>new Ad,2);var hse={forceHalfFloat:P9},F9=`
  if (isnan(a)) return a;
  if (isnan(b)) return b;
`,Ic=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=T.assertAndGetBroadcastShape(t,n),this.enableShapeUniforms=fs(this.outputShape.length),this.userCode=`
      float binaryOperation(float a, float b) {
        ${e}
      }

      void main() {
        float a = getAAtOutCoords();
        float b = getBAtOutCoords();
        setOutput(binaryOperation(a, b));
      }
    `}},P2=`
  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;
`,jh=class{constructor(e,t,n,s=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=T.assertAndGetBroadcastShape(t,n);let r=this.outputShape.length;this.enableShapeUniforms=fs(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=`
          ${kt(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) >= ${this.outputShape[0]} ? 0. : result.y;
            result.z = 0.;
            result.w = 0.;
          `;else{let i=us("coords",r);this.enableShapeUniforms?a+=`
            bool nextRowOutOfBounds =
              (${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 Vs(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 fse={kernelName:zo,backendName:"webgl",kernelFunc:Vs};function xi(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=Vs({inputs:{x:s},backend:n}),l=Vs({inputs:{x:r},backend:n});return o.complexTensorInfos={real:i,imag:l},a}var mse={kernelName:jp,backendName:"webgl",kernelFunc:xi},O9="return (a < 0.) ? b * a : a;",M9=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function gse(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{alpha:a}=s,o=n.makeTensorInfo([],"float32",v.createScalarValue(a,"float32")),i=H().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new jh(M9,r.shape,o.shape):new Ic(O9,r.shape,o.shape),l=n.runWebGLProgram(i,[r,o],"float32");return n.disposeIntermediateTensorInfo(o),l}var yse={kernelName:Lo,backendName:"webgl",kernelFunc:gse},z9="return (a < 0.) ? b * a : a;",L9=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function Ase(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t,a=H().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new jh(L9,s.shape,r.shape):new Ic(z9,s.shape,r.shape);return n.runWebGLProgram(a,[s,r],"float32")}var xse={kernelName:Yo,backendName:"webgl",kernelFunc:Ase},xd="if (isnan(x)) return x;",bse=`
  if (isnan(a)) return a;
  if (isnan(b)) return b;
`,vse=`
  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 ht({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=H().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return u?c=new el(o.shape,t):c=new Sa(o.shape,e),i.runWebGLProgram(c,[o],l)}}function Bn({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},C={dataId:w.dataId,dtype:w.dtype,shape:u.shape},E=new Ic(e,l.shape,u.shape);return c.runWebGLProgram(E,[k,C],Hn(b.dtype,w.dtype))}),x=xi({inputs:{real:g,imag:y},backend:c});return c.disposeIntermediateTensorInfo(g),c.disposeIntermediateTensorInfo(y),x}let p=a||Hn(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"?T.fromUint8ToStringArray(f):f,y=l.dtype==="string"?T.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=H().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,h;return d?h=new jh(t,l.shape,u.shape,n):h=new Ic(e,l.shape,u.shape),c.runWebGLProgram(h,[l,u],p)}}function zp(e,t=!1){if(e==="linear")return t?Jne:qne;if(e==="relu")return t?ese:Kne;if(e==="elu")return t?Qne:Xne;if(e==="relu6")return t?tse:Zne;if(e==="prelu")return t?L9:z9;if(e==="leakyrelu")return t?M9:O9;if(e==="sigmoid")return t?nse:Yne;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var B9=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=fs(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);
      }
    `}},B7={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},W7=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=T.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));
      }
    `}},V7="return a * b;";function gb(e){let{inputs:t,backend:n}=e,{a:s,b:r}=t,a=T.upcastType(s.dtype,r.dtype);if(s.dtype==="complex64"){let i=n.texData.get(s.dataId),l=n.texData.get(r.dataId),u=new W7(B7.REAL,s.shape,r.shape),c=new W7(B7.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=xi({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]=xne(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 H().getBool("WEBGL_PACK_BINARY_OPERATIONS")?o=new jh(V7,s.shape,r.shape):o=new Ic(V7,s.shape,r.shape),n.runWebGLProgram(o,[s,r],a)}var wse={kernelName:Xo,backendName:"webgl",kernelFunc:gb};function kse(e,t,n){let s=[ml(e.shape),...gl(e.shape)],r={dtype:e.dtype,shape:s,dataId:e.dataId},a=[ml(t),...gl(t)],o=new $9(a,s),i=!0,l=[s],u=n.runWebGLProgram(o,[r],e.dtype,l,i);return{dataId:u.dataId,shape:t,dtype:u.dtype}}function we(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{shape:a}=s,o=n,i=v.sizeFromShape(r.shape),l=v.inferFromImplicitShape(a,i),u=v.sizeFromShape(l);v.assert(i===u,()=>`The new shape (${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&&!Mp(r.shape,l)&&!(c.texture!==null&&Mp(c.shape,l))?kse(r,l,o):(o.incRef(r.dataId),{dataId:r.dataId,shape:l,dtype:r.dtype})}var Sse={kernelName:jl,backendName:"webgl",kernelFunc:we},U7=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);

          ${l}
        }
        setOutput(sumValue);
      }
    `}},Ise=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:s,inSize:r,outSize:a}=e;this.outputShape=[s,a];let o="0.0",i="";t==="prod"?o="1.0":t==="min"?(o="1.0 / 1e-20",i="min"):t==="max"&&(o="-1.0 / 1e-20",i="max");let l=`${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 Cse(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=T.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:s,outSize:Math.ceil(n/s)})}return t}function bu(e,t,n,s){let r=Cse(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 U7({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u},i):new U7({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u}):c=new Ise({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 Tse=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=kt(this.rank),r=Nse(t);this.userCode=`
    void main() {
      ${s} resRC = getOutputCoords();
      setOutput(getA(${r}));
    }
    `}};function Nse(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 Ese=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 ${this.rank} is not yet supported.`);let s=kt(this.rank),r=D9("rc",this.rank),a=new Array(this.rank);for(let u=0;u<t.length;u++)a[t[u]]=r[u];let o=`vec2(${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] = ${l};
        }
      }
      setOutput(result);
    }
    `}};function F2(e,t,n){let s=H().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Ese(e.shape,t):new Tse(e.shape,t);return n.runWebGLProgram(s,[e],e.dtype)}function Rse(e,t,n,s){let r=t,a=e.shape.length,o=v.parseAxisParam(r,e.shape),i=o,l=T.getAxesPermutation(i,a),u=l!=null,c=e;u&&(c=F2(e,l,s),i=T.getInnerMostAxes(i.length,a)),T.assertAxesAreInnerMostDims("sum",i,a);let[p,d]=T.computeOutAndReduceShapes(c.shape,i),h=p;n&&(h=T.expandShapeToKeepDim(p,o));let f=v.sizeFromShape(d),g=v.sizeFromShape(e.shape)/f,y=we({inputs:{x:c},attrs:{shape:[g,f]},backend:s}),x=ch(e.dtype),A=bu(y,x,"sum",s),b=we({inputs:{x:A},attrs:{shape:h},backend:s});return s.disposeIntermediateTensorInfo(y),s.disposeIntermediateTensorInfo(A),u&&s.disposeIntermediateTensorInfo(c),b}function O2(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return Rse(r,a,o,n)}var _se={kernelName:ii,backendName:"webgl",kernelFunc:O2};function cs(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{perm:a}=s,o=n,i=r.shape.length,l=new Array(i);for(let c=0;c<l.length;c++)l[c]=r.shape[a[c]];let u;if(o.shouldExecuteOnCPU([r])){let p=o.texData.get(r.dataId).values,d=mb(p,r.shape,r.dtype,a,l);u=o.makeTensorInfo(l,r.dtype);let h=o.texData.get(u.dataId);h.values=d}else u=F2(r,a,o);return u}var Dse={kernelName:na,backendName:"webgl",kernelFunc:cs},W9=1e3;function qm({a:e,b:t,transposeA:n,transposeB:s,backend:r,bias:a=null,preluActivationWeights:o=null,leakyreluAlpha:i=0,activation:l=null}){let u=e.shape.length,c=t.shape.length,p=n?e.shape[u-2]:e.shape[u-1],d=s?t.shape[c-1]:t.shape[c-2],h=n?e.shape[u-1]:e.shape[u-2],f=s?t.shape[c-2]:t.shape[c-1],m=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(m),x=v.sizeFromShape(g),b=uu.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,f]);v.assert(p===d,()=>`Error in matMul: inner shapes (${p}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${s} must match.`);let w=n?[y,p,h]:[y,h,p],k=s?[x,f,d]:[x,d,f],C=we({inputs:{x:e},backend:r,attrs:{shape:w}}),E=we({inputs:{x:t},backend:r,attrs:{shape:k}}),_=[C,E],$=Math.max(y,x),R=n?C.shape[1]:C.shape[2],P=a!=null,S=o!=null,M=l==="leakyrelu",L=l!=null?zp(l,!0):null,U=P||S||M||L!=null,K;if((h===1||f===1)&&R>W9&&U===!1){let Z=C,J=E;n&&(Z=cs({inputs:{x:C},backend:r,attrs:{perm:[0,2,1]}}),_.push(Z)),s&&(J=cs({inputs:{x:E},backend:r,attrs:{perm:[0,2,1]}}),_.push(J));let te=f!==1,le=f===1,ae=Z;te&&(ae=we({inputs:{x:Z},backend:r,attrs:{shape:[$,R,1]}}),_.push(ae));let pe=f===1?2:1,ce=J;le&&(ce=we({inputs:{x:J},backend:r,attrs:{shape:[$,1,R]}}),_.push(ce));let xe=gb({inputs:{a:ae,b:ce},backend:r});K=O2({inputs:{x:xe},backend:r,attrs:{axis:pe,keepDims:!0}}),_.push(xe)}else{let Z=Hn(e.dtype,t.dtype),J=new B9(w,k,[$,h,f],n,s,P,L,S,M),te=[C,E];if(a!=null&&te.push(a),S&&te.push(o),M){let le=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));te.push(le),_.push(le)}K=r.runWebGLProgram(J,te,Z)}let q=we({inputs:{x:K},backend:r,attrs:{shape:b}});_.push(K);for(let Z of _)r.disposeIntermediateTensorInfo(Z);return q}function $se(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=s;return qm({a:r,b:a,transposeA:l,transposeB:u,backend:n,bias:o,preluActivationWeights:i,leakyreluAlpha:p,activation:c})}var Pse={kernelName:ao,backendName:"webgl",kernelFunc:$se},G7="return abs(x);";function Fse(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=R9(a.values);return n.makeTensorInfo(s.shape,s.dtype,o)}let r;return H().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new el(s.shape,G7):r=new Sa(s.shape,G7),n.runWebGLProgram(r,[s],s.dtype)}var Ose={kernelName:xl,backendName:"webgl",kernelFunc:Fse},Mse=br+`
  if (abs(x) > 1.) {
    return NAN;
  }
  return acos(x);
`,zse=ht({opSnippet:Mse}),Lse={kernelName:Nc,backendName:"webgl",kernelFunc:zse},Bse=br+`
  if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,Wse=ht({opSnippet:Bse}),Vse={kernelName:Ec,backendName:"webgl",kernelFunc:Wse},H7="return a + b;",Use=Bn({opSnippet:H7,packedOpSnippet:H7,supportsComplex:!0,cpuKernelImpl:Qte}),Gse={kernelName:Da,backendName:"webgl",kernelFunc:Use},Hse=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 = ${s};
        setOutput(result);
      }
    `}},jse=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((r,a)=>`T${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 xm(e){let{inputs:t,backend:n}=e,s=t;if(s.length===1)return Vs({inputs:{x:s[0]},backend:n});if(s.length>H().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let l=Math.floor(s.length/2),u=xm({inputs:s.slice(0,l),backend:n}),c=xm({inputs:s.slice(l),backend:n});return xm({inputs:[u,c],backend:n})}let r=s.map(l=>l.dtype).reduce((l,u)=>Hn(l,u)),a=s.map(l=>l.shape),i=H().getBool("WEBGL_PACK")?new jse(s[0].shape,a):new Hse(s[0].shape,a);return n.runWebGLProgram(i,s,r)}var qse={kernelName:xo,backendName:"webgl",kernelFunc:xm};function Xse(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=T.getAxesPermutation(u,i),p=r;c!=null&&(p=cs({inputs:{x:r},backend:n,attrs:{perm:c}}),u=T.getInnerMostAxes(u.length,i)),T.assertAxesAreInnerMostDims("all",u,i);let[d,h]=T.computeOutAndReduceShapes(p.shape,u),f=v.sizeFromShape(h),m=we({inputs:{x:p},backend:n,attrs:{shape:[-1,f]}}),g=bu(m,m.dtype,"all",n),y;if(o){let x=T.expandShapeToKeepDim(d,l);y=we({inputs:{x:g},backend:n,attrs:{shape:x}})}else y=we({inputs:{x:g},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(p),y}var Kse={kernelName:Rc,backendName:"webgl",kernelFunc:Xse};function Zse(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=T.getAxesPermutation(u,i),p=r;c!=null&&(p=cs({inputs:{x:r},backend:n,attrs:{perm:c}}),u=T.getInnerMostAxes(u.length,i)),T.assertAxesAreInnerMostDims("any",u,i);let[d,h]=T.computeOutAndReduceShapes(p.shape,u),f=v.sizeFromShape(h),m=we({inputs:{x:p},backend:n,attrs:{shape:[-1,f]}}),g=bu(m,m.dtype,"any",n),y;if(o){let x=T.expandShapeToKeepDim(d,l);y=we({inputs:{x:g},backend:n,attrs:{shape:x}})}else y=we({inputs:{x:g},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(p),y}var Yse={kernelName:_c,backendName:"webgl",kernelFunc:Zse},Jse=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 ${o} bestValue) {
            bestValue = candidate;
            bestIndex = inIdx;
          }
        }
        setOutput(float(bestIndex));
      }
    `}},Qse=class{constructor(e,t,n,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${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=kt(i),u=us("coords",i),c,p;if(a===1){p=i+1;let C=kt(p);c=`
        ${C} sourceLocR = ${C}(${u.join()}, 0);
        ++${u[i-1]};
        ${C} sourceLocG = ${C}(${u.join()}, 0);
        ++${u[i-2]};
        ${C} sourceLocA = ${C}(${u.join()}, 0);
        --${u[i-1]};
        ${C} sourceLocB = ${C}(${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(C=>"int "+C),m=us("sourceLocR",p-1).concat("inIdx.r"),g=us("sourceLocG",p-1).concat("inIdx.g"),y=us("sourceLocB",p-1).concat("inIdx.b"),x=us("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 V9(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=T.computeOptimalWindowSize(a),i={windowSize:o,inSize:a,batchSize:r,outSize:Math.ceil(a/o)},l=new Jse(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=V9(e,t,n,c);return e.disposeIntermediateTensorInfo(c),p}function U9(e,t,n,s=null){let r=s!=null?s.shape:t.shape,a=r[r.length-1],o=T.computeOptimalWindowSize(a),i=new Qse(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=U9(e,t,n,u);return e.disposeIntermediateTensorInfo(u),c}return u}function G9(e,t,n,s){let r=[n];if(T.assertAxesAreInnerMostDims("arg"+s.charAt(0).toUpperCase()+s.slice(1),r,t.shape.length),!H().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]=T.computeOutAndReduceShapes(l.shape,r),p=v.sizeFromShape(c),d=we({inputs:{x:l},backend:e,attrs:{shape:[-1,p]}});a.push(d);let h=V9(e,d,s);a.push(h);let f=we({inputs:{x:h},backend:e,attrs:{shape:u}});return a.forEach(m=>e.disposeIntermediateTensorInfo(m)),f}return U9(e,t,s)}function ere(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=v.parseAxisParam(a,r.shape),i=T.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=cs({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=T.getInnerMostAxes(o.length,l.shape.length)),T.assertAxesAreInnerMostDims("argMax",[o[0]],l.shape.length);let c=G9(n,l,o[0],"max");return u.forEach(p=>n.disposeIntermediateTensorInfo(p)),c}var tre={kernelName:bo,backendName:"webgl",kernelFunc:ere};function nre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=v.parseAxisParam(a,r.shape),i=T.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=cs({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=T.getInnerMostAxes(o.length,l.shape.length)),T.assertAxesAreInnerMostDims("argMin",[o[0]],l.shape.length);let c=G9(n,l,o[0],"min");return u.forEach(p=>n.disposeIntermediateTensorInfo(p)),c}var sre={kernelName:Dc,backendName:"webgl",kernelFunc:nre},rre=br+`
  if (abs(x) > 1.) {
    return NAN;
  }
  return asin(x);
`,are=ht({opSnippet:rre}),ore={kernelName:$c,backendName:"webgl",kernelFunc:are},ire=br+"return log(x + sqrt(x * x + 1.0));",lre=ht({opSnippet:ire}),ure={kernelName:Pc,backendName:"webgl",kernelFunc:lre},cre=br+`
  return atan(x);
`,dre=ht({opSnippet:cre}),pre={kernelName:Fc,backendName:"webgl",kernelFunc:dre},hre=bse+`
  return atan(a, b);
`,fre=`
  vec4 result = atan(a, b);
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  `+vse+`
  return result;
`,mre=Bn({opSnippet:hre,packedOpSnippet:fre}),gre={kernelName:bl,backendName:"webgl",kernelFunc:mre},yre=br+`
  if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,Are=ht({opSnippet:yre}),xre={kernelName:Oc,backendName:"webgl",kernelFunc:Are},Lp=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) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let C=">=";this.userCode=`
        const ivec2 strides = ivec2(${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 ${C} 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});
      }
    `}},yb=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 _=">=";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 ${_} 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,C=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 + ${k};
            if (${C===1}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                initializationValue,
                initializationValue,
                initializationValue
              );

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

              ${E}
            } else if (${C===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 bre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;hd(r,"avgPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;v.assert(T.eitherStridesOrDilationsAreOne(o,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=T.computePool2DInfo(r.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Vs({inputs:{x:r},backend:n});let p=new Lp(c,"avg",!1);return n.runWebGLProgram(p,[r],"float32")}var vre={kernelName:vo,backendName:"webgl",kernelFunc:bre};function wre(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=T.computePool3DInfo(r.shape,a,o,c,i,l,u),d=new yb(p,"avg",!1);return n.runWebGLProgram(d,[r],"float32")}var kre={kernelName:Hp,backendName:"webgl",kernelFunc:wre},Sre=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);
      }
    `}},Ire=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 Cre(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=T.computePool3DInfo(o.shape,i,l,p,u,c),h=new Ire(d);return n.runWebGLProgram(h,[r],o.dtype)}var Tre={kernelName:s0,backendName:"webgl",kernelFunc:Cre};function Nre(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a;hd([r,a],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=s,c=T.computePool2DInfo(o.shape,i,l,1,u),p=new Sre(c);return n.runWebGLProgram(p,[r],o.dtype)}var Ere={kernelName:n0,backendName:"webgl",kernelFunc:Nre};function Rre(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;return qm({a:r,b:a,transposeA:o,transposeB:i,backend:n})}var _re={kernelName:wo,backendName:"webgl",kernelFunc:Rre},Dre=class{constructor(e,t,n,s,r,a){this.outputShape=[],this.variableNames=["x","mean","variance"],T.assertAndGetBroadcastShape(e,t),T.assertAndGetBroadcastShape(e,n);let o="0.0";s!=null&&(T.assertAndGetBroadcastShape(e,s),this.variableNames.push("offset"),o="getOffsetAtOutCoords()");let i="1.0";r!=null&&(T.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)));
      }
    `}},$re=class{constructor(e,t,n,s,r,a){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],T.assertAndGetBroadcastShape(e,t),T.assertAndGetBroadcastShape(e,n);let o="vec4(0.0)";s!=null&&(T.assertAndGetBroadcastShape(e,s),this.variableNames.push("offset"),o="getOffsetAtOutCoords()");let i="vec4(1.0)";r!=null&&(T.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);
      }
    `}},Pre=({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=H().getBool("WEBGL_PACK_NORMALIZATION")?new $re(s.shape,r.shape,a.shape,c,p,l):new Dre(s.shape,r.shape,a.shape,c,p,l);return t.runWebGLProgram(d,u,u[0].dtype)},Fre={kernelName:Oo,backendName:"webgl",kernelFunc:Pre},Ore=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=kt(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let n=Mre(this.rank),s,r=e.map((a,o)=>`sourceLoc.${Sy[o]} = start[${o}] + coords.${Sy[o]};`);s=`
        ${t} sourceLoc;
        ${t} coords = getOutputCoords();
        ${r.join(`
`)}
      `,this.userCode=`
      void main() {
        ${s}
        setOutput(getSource(${n}));
      }
    `}},Sy=["x","y","z","w","u","v"];function Mre(e){if(e===1)return"sourceLoc";if(e<=6)return Sy.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var zre=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=kt(this.rank),n=us("coords",this.rank),s=us("sourceLoc",this.rank),r=this.rank===1?"sourceLoc":`vec2(${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 Lre(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=jt.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 bd(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,size:o}=s,[i,l]=jt.parseSliceParams(r,a,o);if(jt.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=Nne(p.values,i,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,d)}let{isPacked:u}=n.texData.get(r.dataId),c=jt.isSliceContinous(r.shape,i,l);if(u||!c){let p=H().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new zre(l):new Ore(l),d=[i];return n.runWebGLProgram(p,[r],r.dtype,d)}return n.uploadToGPU(r.dataId),Lre(r,i,l,n)}var Bre={kernelName:Yl,backendName:"webgl",kernelFunc:bd},Wre=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=T.getReshaped(r.shape,a,i),u=T.getPermuted(l.length,a.length),c=T.getReshapedPermuted(r.shape,a,i),p=T.getSliceBeginCoords(o,a.length),d=T.getSliceSize(c,o,a.length),h=[],f=we({inputs:{x:r},backend:n,attrs:{shape:l}}),m=cs({inputs:{x:f},backend:n,attrs:{perm:u}}),g=we({inputs:{x:m},backend:n,attrs:{shape:c}}),y=bd({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},Vre={kernelName:vl,backendName:"webgl",kernelFunc:Wre};function Ure(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=E9(i,l,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,u)}var Gre={kernelName:r0,backendName:"webgl",kernelFunc:Ure};function Hre(e){let{inputs:t,backend:n}=e,{s0:s,s1:r}=t,a=n.readSync(s.dataId),o=n.readSync(r.dataId),i=T.assertAndGetBroadcastShape(Array.from(a),Array.from(o));return n.makeTensorInfo([i.length],"int32",Int32Array.from(i))}var jre={kernelName:a0,backendName:"webgl",kernelFunc:Hre},qre="return float(a != b);",H9=Bn({opSnippet:qre,cpuKernelImpl:vne,dtype:"bool"}),Xre={kernelName:Ll,backendName:"webgl",kernelFunc:H9};function qh(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.texData.get(s.dataId);return Vs({inputs:{x:r.complexTensorInfos.real},backend:n})}var Kre={kernelName:eh,backendName:"webgl",kernelFunc:qh},Zre="return float(int(x));";function Yre(e,t){let n=new Sa(e.shape,Zre),s=t.runWebGLProgram(n,[e],"int32");return{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}function Iy(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dtype:a}=s;if(a==="complex64"){if(r.dtype==="complex64")return Vs({inputs:{x:r},backend:n});let o=Gt(r.shape),i=Iy({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=xi({inputs:{real:i,imag:o},backend:n});return o.dispose(),n.disposeIntermediateTensorInfo(i),l}if(r.dtype==="complex64"){let o=qh({inputs:{input:r},backend:n}),i=Iy({inputs:{x:o},backend:n,attrs:{dtype:a}});return n.disposeIntermediateTensorInfo(o),i}if(!v.hasEncodingLoss(r.dtype,a)){let o=Vs({inputs:{x:r},backend:n});return{dataId:o.dataId,shape:o.shape,dtype:a}}if(n.shouldExecuteOnCPU([r])){let o=n.texData.get(r.dataId).values,[i,l,u]=tne(o,r.shape,r.dtype,a);return n.makeTensorInfo(i,l,u)}if(a==="int32")return Yre(r,n);if(a==="bool"){let o=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),l=H9({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 Jre={kernelName:ko,backendName:"webgl",kernelFunc:Iy},j7="return ceil(x);",Qre=ht({opSnippet:j7,packedOpSnippet:j7,cpuKernelImpl:nne}),eae={kernelName:So,backendName:"webgl",kernelFunc:Qre},tae=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));
      }
    `}},nae=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 sae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{clipValueMin:a,clipValueMax:o}=s,i;H().getBool("WEBGL_PACK_CLIP")?i=new nae(r.shape):i=new tae(r.shape);let l=[[a],[o]];return n.runWebGLProgram(i,[r],r.dtype,l)}var rae={kernelName:$a,backendName:"webgl",kernelFunc:sae},aae=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 q7(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function oae(e){let{inputs:t,backend:n}=e,{x:s}=t,r=n.texData.get(s.dataId),a=new aae(s.shape),o=[q7(s,r.complexTensorInfos.real),q7(s,r.complexTensorInfos.imag)];return n.runWebGLProgram(a,o,o[0].dtype)}var iae={kernelName:qp,backendName:"webgl",kernelFunc:oae},lae=class{constructor(e){this.outputShape=[],this.outputShape=T.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;

        ${n.join(`
        `)}
      }
    `}},uae=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=T.computeOutShape(e,t);let n=this.outputShape,s=n.length,r=kt(s),a=us("coords",s),o=["x","y","z","w","u","v"].slice(0,s);this.variableNames=e.map((f,m)=>`T${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}(${um(o,l,m)}),
            vec2(${um(u,l,m)}));
        }`}let d=i.length,h=i[i.length-1];p+=`
        return getChannel(
          getT${d}(${um(o,l,h)}),
          vec2(${um(u,l,h)}));`,this.userCode=`
      float getValue(${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 um(e,t,n){let s=e.indexOf(t);return e.map((a,o)=>o===s?`${a} - ${n}`:a).join()}function M2(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.texData.get(s.dataId);return Vs({inputs:{x:r.complexTensorInfos.imag},backend:n})}var cae={kernelName:Yp,backendName:"webgl",kernelFunc:M2};function gp(e,t,n){let s=e[0].dtype;if(s==="complex64"){let p=e.map(g=>qh({inputs:{input:g},backend:n})),d=e.map(g=>M2({inputs:{input:g},backend:n})),h=gp(p,t,n),f=gp(d,t,n),m=xi({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 we({inputs:{x},backend:n,attrs:{shape:[-1,A]}})}),d=p.map(x=>({vals:n.readSync(x.dataId),shape:x.shape})),h=T.computeOutShape(p.map(x=>x.shape),1),f=p[0].shape[0]===1,m=sne(d,h,s,f),g=T.computeOutShape(e.map(x=>x.shape),t),y=n.makeTensorInfo(g,s,m);return p.forEach(x=>n.disposeIntermediateTensorInfo(x)),y}let a=H().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(gp(f,t,n))}let d=gp(p,t,n);for(let h of p)n.disposeIntermediateTensorInfo(h);return d}if(H().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let p=new uae(e.map(d=>d.shape),t);return n.runWebGLProgram(p,e,s)}let{tensors2D:o,outShape:i}=dae(e,t,n),l=new lae(o.map(p=>p.shape)),u=n.runWebGLProgram(l,o,s);o.forEach(p=>n.disposeIntermediateTensorInfo(p));let c=we({inputs:{x:u},attrs:{shape:i},backend:n});return n.disposeIntermediateTensorInfo(u),c}function dae(e,t,n){let s=T.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>we({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:s}}function j9(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s,a=v.parseAxisParam(r,t[0].shape)[0],o=T.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 Vs({inputs:{x:i[0]},backend:n});let l=i.map(u=>u.shape);return T.assertParamsConsistent(l,a),gp(i,a,n)}var pae={kernelName:wl,backendName:"webgl",kernelFunc:j9},q9=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}
        ${b}
        setOutput(result);
      }
    `}},hae=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,s=e.padInfo.left,r=e.strideDepth,a=e.strideHeight,o=e.strideWidth,i=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.filterDepth,p=e.filterHeight,d=e.filterWidth,h=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
      const ivec3 strides = ivec3(${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, ${h} + 2, d2)
                );
                dotProd += dot(xValues, wValues);
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}},X9=class{constructor(e,t=!1,n=null,s=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=fs(this.outputShape.length);let a=e.padInfo.left,o=e.strideWidth,i=e.dilationWidth,l=e.filterHeight,u=e.filterWidth,c=u,p=`
       int xR; int xC; int xCOffset;
       vec4 wTexel; vec4 previous; vec4 final;`;for(let m=0;m<u;m++)p+=`
           vec4 xTexelC${m*2};
           int xTexelC${m*2}Ready;
           vec4 xTexelC${m*2+1};
           int xTexelC${m*2+1}Ready;
           vec4 xC${m};`;p+=`
     for (int r = 0; r < ${l}; r++) {
      for (int d1 = 0; d1 < ${e.inChannels}; d1 += 2) {
       `;for(let m=0;m<u;m++)p+=`
           xTexelC${m*2} = vec4(0.0);
           xTexelC${m*2}Ready = 0;
           xTexelC${m*2+1} = vec4(0.0);
           xTexelC${m*2+1}Ready = 0;
           xC${m} = vec4(0.0);`;p+=`
         xR = xRCorner + r * dilations[0];
         if (xR >=0 && xR < inDims[0]) {
       `;for(let m=0;m<(c+1)/2;m++){let g=m*2;if(p+=`
           xC = xCCorner + ${g*i};
           `,o===1){if(g<u&&(a%2===1?(p+=`
                 xCOffset = xC + 1;
                 if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g}Ready == 0) {
                   xTexelC${g} = 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${g}.zw = vec2(0.0);
                   }
                   xTexelC${g}Ready = 1;
                 }
               `,i===1&&g>0?p+=`
                 xC${g} = vec4(xTexelC${g-2}.zw, xTexelC${g}.xy);
                 `:p+=`
                   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${g} = vec4(previous.zw, xTexelC${g}.xy);
                   } else {
                     xC${g} = vec4(0.0, 0.0, xTexelC${g}.xy);
                   }
                   `):p+=`
                 if (xC >= 0 && xC < inDims[1] && xTexelC${g}Ready == 0) {
                   xTexelC${g} = getX(batch, xR, xC, d1);
                   if (xC + 1 >= inDims[1]) {
                     xTexelC${g}.zw = vec2(0.0);
                   }
                   xTexelC${g}Ready = 1;
                 }

                 xC${g} = xTexelC${g};
                 `,g+1<u)){let y=a%2===0?v.nearestLargerEven(i):i;i%2===0&&a%2===1||i%2!==0&&a%2!==1?(p+=`
                   xCOffset = xC + imod(pads[1], 2) + ${y};

                   if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
                     xTexelC${g+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${g+1}.zw = vec2(0.0);
                     }
                     xTexelC${g+1}Ready = 1;
                   }
                   `,i>1?p+=`
                     xCOffset -= 2;
                     if (xCOffset >= 0 && xCOffset < inDims[1]) {
                      previous = getX(batch, xR, xCOffset, d1);
                      xC${g+1} = vec4(previous.zw, xTexelC${g+1}.xy);
                     } else {
                      xC${g+1} = vec4(0.0, 0.0, xTexelC${g+1}.xy);
                     }
                     `:p+=`
                     xC${g+1} = vec4(xTexelC${g}.zw, xTexelC${g+1}.xy);
                     `):y===1?p+=`
                     xC${g+1} = xTexelC${g};
                     `:p+=`
                     xCOffset = xC + ${y};

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

                     xC${g+1} = xTexelC${g+1};
                     `}}else g<u&&(a%2===1?(p+=`
                 xCOffset = xC + 1 - strides[1];
                 if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g}Ready == 0) {
                   xTexelC${g} = 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${g}.zw = vec2(0.0);
                   }
                   xTexelC${g}Ready = 1;
                 }

                 if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${g+1}Ready == 0) {
                   xTexelC${g+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${g+1}.zw = vec2(0.0);
                   }
                   xTexelC${g+1}Ready = 1;
                 }

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

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

                 xC${g} = vec4(
                   xTexelC${g}.xy, xTexelC${g+1}.xy);
               `,g+1<u&&(p+=`
                   xC${g+1} = vec4(xTexelC${g}.zw, xTexelC${g+1}.zw);
                 `)));g<u&&(p+=`
             wTexel = getW(r, ${g}, d1, d2);
             dotProd += xC${g}.xxzz * vec4(wTexel.xy, wTexel.xy);
             if(d1 + 1 < ${e.inChannels}) {
               dotProd += xC${g}.yyww * vec4(wTexel.zw, wTexel.zw);
             }
           `,g+1<u&&(p+=`
               wTexel = getW(r, ${g+1}, d1, d2);
               dotProd += xC${g+1}.xxzz * vec4(wTexel.xy, wTexel.xy);
               if(d1 + 1 < ${e.inChannels}) {
                 dotProd += xC${g+1}.yyww * vec4(wTexel.zw, wTexel.zw);
               }
             `))}p+=`
     }
   `,p+=`
     }
   `,p+=`
     }
   `;let d="",h="";n&&(s?d=`vec4 activation(vec4 a) {
           vec4 b = getPreluActivationWeightsAtOutCoords();
           ${n}
         }`:r?d=`vec4 activation(vec4 a) {
           vec4 b = getLeakyreluAlphaAtOutCoords();
           ${n}
         }`:d=`vec4 activation(vec4 x) {
           ${n}
         }`,h="result = activation(result);");let f=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
       ${d}

       void main() {
         ivec4 coords = getOutputCoords();
         int batch = coords.x;
         ivec2 xRCCorner = coords.yz * strides - pads;
         int d2 = coords.w;
         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);

         ${p}

         vec4 result = dotProd - vec4(0.000000000000001);
         ${f}
         ${h}
         setOutput(result);
       }
     `}},fae=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=fs(this.outputShape.length);let{dataFormat:n}=t,s=hs(),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 Xm(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 K9({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=Xm(a.shape,h);b!=null&&(a=we({inputs:{x:a},backend:s,attrs:{shape:b}}),y.push(a))}if(r!=null){let b=Xm(r.shape,h);b!=null&&(r=we({inputs:{x:r},backend:s,attrs:{shape:b}}),y.push(r))}if(!((p===1||d===1)&&c>W9)&&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(Mp(u.shape,w.shape),()=>`packed reshape ${u.shape} to ${w.shape} isn't free`);let C=we({inputs:{x:t},backend:s,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(C);let E=qm({a:w,b:C,backend:s,transposeA:f,transposeB:m,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o}),_=s.texData.get(E.dataId);v.assert(_.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=k,_.shape=n.outShape,g=Vs({inputs:{x:E},backend:s}),g.shape=n.outShape,y.push(E)}else{let b=n.outHeight*n.outWidth,w=we({inputs:{x:e},backend:s,attrs:{shape:h?[n.batchSize,b,n.inChannels]:[n.batchSize,n.inChannels,b]}}),k=we({inputs:{x:t},backend:s,attrs:{shape:[1,n.inChannels,n.outChannels]}}),C=qm({a:h?w:k,b:h?k:w,transposeA:!h,transposeB:m,backend:s,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o});g=we({inputs:{x:C},backend:s,attrs:{shape:n.outShape}}),y.push(w),y.push(k),y.push(C)}for(let b of y)s.disposeIntermediateTensorInfo(b);return g}function Z9({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 q=Xm(a.shape,f);q!=null&&(a=we({inputs:{x:a},backend:s,attrs:{shape:q}}),b.push(a))}if(r!=null){let q=Xm(r.shape,f);q!=null&&(r=we({inputs:{x:r},backend:s,attrs:{shape:q}}),b.push(r))}let w=we({inputs:{x:t},backend:s,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});b.push(w);let k=new fae(y,n),C=[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",C),_=we({inputs:{x:E},backend:s,attrs:{shape:y}});b.push(E),b.push(_);let $=r!=null,R=a!=null,P=i==="leakyrelu",S=i?zp(i,!0):null,M=new B9(f?_.shape:w.shape,f?w.shape:_.shape,f?[n.batchSize,g,n.outChannels]:[n.batchSize,n.outChannels,g],x,A,$,S,R,P),L=f?[_,w]:[w,_];if(r&&L.push(r),R&&L.push(a),P){let q=s.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));L.push(q),b.push(q)}let U=s.runWebGLProgram(M,L,"float32"),K=we({inputs:{x:U},backend:s,attrs:{shape:n.outShape}});b.push(U);for(let q of b)s.disposeIntermediateTensorInfo(q);return K}function mae(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=T.convertConv2DDataFormat(l),d=T.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=K9({x:r,filter:a,convInfo:d,backend:n});else if(d.strideWidth<=2&&p==="channelsLast"&&H().getBool("WEBGL_EXP_CONV")){let m=new X9(d),g=[[d.padInfo.top,d.padInfo.left],[d.strideHeight,d.strideWidth],[d.dilationHeight,d.dilationWidth],[d.inHeight,d.inWidth]];h=n.runWebGLProgram(m,[r,a],"float32",g)}else if(H().getBool("WEBGL_CONV_IM2COL"))h=Z9({x:r,filter:a,convInfo:d,backend:n});else{let m=new q9(d);h=n.runWebGLProgram(m,[r,a],"float32")}let f=we({inputs:{x:h},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(h),f}var gae={kernelName:Io,backendName:"webgl",kernelFunc:mae},yae=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);
      }
    `}},Aae=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);
      }
    `}},xae=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);
      }
    `}},bae=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 < ${e.outChannels}; d2++) {
                float xValue = getDy(batch, idyF, idyR, idyC, d2);
                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function vae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,filterShape:c}=s,p=T.convertConv2DDataFormat(l),d=T.computeConv2DInfo(r.shape,c,o,1,i,u,!1,p),h=new yae(d);return n.runWebGLProgram(h,[r,a],"float32")}var wae={kernelName:o0,backendName:"webgl",kernelFunc:vae};function kae(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{inputShape:o,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=s,p=T.convertConv2DDataFormat(u),d=T.computeConv2DInfo(o,a.shape,i,1,l,c,!1,p),h=new Aae(d);return n.runWebGLProgram(h,[r,a],"float32")}var Sae={kernelName:Co,backendName:"webgl",kernelFunc:kae};function Iae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l}=s,u=T.computeConv3DInfo(r.shape,a.shape,o,l,i),c=new hae(u);return n.runWebGLProgram(c,[r,a],"float32")}var Cae={kernelName:Xp,backendName:"webgl",kernelFunc:Iae};function Tae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,filterShape:l}=s,u=T.computeConv3DInfo(r.shape,l,o,1,i),c=new xae(u);return n.runWebGLProgram(c,[r,a],"float32")}var Nae={kernelName:i0,backendName:"webgl",kernelFunc:Tae};function Eae(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{pad:o,strides:i,inputShape:l}=s,u=T.computeConv3DInfo(l,a.shape,i,1,o),c=new bae(u);return n.runWebGLProgram(c,[r,a],"float32")}var Rae={kernelName:l0,backendName:"webgl",kernelFunc:Eae},_ae=xd+`
  return cos(x);
`,Dae=ht({opSnippet:_ae}),$ae={kernelName:To,backendName:"webgl",kernelFunc:Dae},Pae=`
  float e2x = exp(-x);
  return (e2x + 1.0 / e2x) / 2.0;
`,Fae=ht({opSnippet:Pae}),Oae={kernelName:No,backendName:"webgl",kernelFunc:Fae},Mae=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);
        }
      }
    `}},zae=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 Mae(r.shape,a.shape,i,l,u);return n.runWebGLProgram(c,[r,a,o],"float32")},Lae={kernelName:Sl,backendName:"webgl",kernelFunc:zae},Bp;(function(e){e.Prod="*",e.Sum="+"})(Bp||(Bp={}));var X7=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===Bp.Prod?"1.0":"0.0",o=n?a:`getX(${K7(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() {
        ${kt(r)} coords = getOutputCoords();
        int end = ${Z7(r,"coords",this.op)};
        float val = ${o};
        int pow2 = int(pow(2.0, index));
        if (${l}) {
          int idx = ${u};
          ${Z7(r,"coords",this.op)} = idx;
          val ${this.op}= getX(${K7(r,"coords",this.op)});
        }
        setOutput(val);
      }
    `}};function K7(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 ${e} is not yet supported`)}function Z7(e,t,n){if(e===1)return`${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 ${e} is not yet supported`)}function Y9(e,t,n,s,r,a){let o=t.shape.length,i=T.getAxesPermutation([s],o),l=t;i!=null&&(l=cs({inputs:{x:t},backend:n,attrs:{perm:i}}));let u=T.getInnerMostAxes(1,o)[0];if(u!==o-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${s}`);let c=l.shape[u],p=Vs({inputs:{x:l},backend:n});for(let d=0;d<=Math.ceil(Math.log2(c))-1;d++){let h=new X7(e,l.shape,!1,a),f=[[d]],m=p;p=n.runWebGLProgram(h,[p],p.dtype,f),n.disposeIntermediateTensorInfo(m)}if(r){let d=new X7(e,l.shape,r,a),h=p;p=n.runWebGLProgram(d,[p],p.dtype),n.disposeIntermediateTensorInfo(h)}if(i!=null){let d=T.getUndoAxesPermutation(i),h=cs({inputs:{x:p},backend:n,attrs:{perm:d}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(l),h}return p}function Bae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;return Y9(Bp.Prod,r,n,a,o,i)}var Wae={kernelName:kl,backendName:"webgl",kernelFunc:Bae};function Vae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;return Y9(Bp.Sum,r,n,a,o,i)}var Uae={kernelName:Eo,backendName:"webgl",kernelFunc:Vae};function Gae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o,binaryOutput:i}=s;if(r.shape.length===1){let l=n.readSync(r.dataId),u=n.readSync(a.dataId),c=E9(l,u,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,c)}else if(r.shape.length===2){let l=n.bufferSync(r),u=n.bufferSync(a),c=ene(l,u,o,i);return n.makeTensorInfo(c.shape,a.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var Hae={kernelName:u0,backendName:"webgl",kernelFunc:Gae},jae=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 qae(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 jae(f,a,o);return n.runWebGLProgram(m,[r],r.dtype)}var Xae={kernelName:Il,backendName:"webgl",kernelFunc:qae},J9=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=fs(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}
        ${u}
        setOutput(result);
      }
    `}},Q9=class{constructor(e,t=!1,n=null,s=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=fs(this.outputShape.length);let a=e.outChannels/e.inChannels,o=e.padInfo.left,i=e.strideWidth,l=e.dilationWidth,u=e.filterHeight,c=e.filterWidth,p=c,d=`
      int xR; int xC; int xCOffset;
      vec4 wTexel; vec4 previous; vec4 final;`;for(let g=0;g<c;g++)d+=`
          vec4 xTexelC${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]) {
                     previous = getX(batch, xR, xCOffset, d1);
                     xC${y+1} = vec4(previous.zw, xTexelC${y+1}.xy);
                    } else {
                     xC${y+1} = vec4(0.0, 0.0, xTexelC${y+1}.xy);
                    }
                    `: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 Kae(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(T.eitherStridesOrDilationsAreOne(o,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${o} and dilations '${c}'`);let p=T.computeConv2DInfo(r.shape,a.shape,o,c,i,u,!0),d;H().getBool("WEBGL_PACK_DEPTHWISECONV")&&p.strideWidth<=2&&p.outChannels/p.inChannels===1?d=new Q9(p):d=new J9(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 Zae={kernelName:Ro,backendName:"webgl",kernelFunc:Kae},Yae=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);
      }
    `}},Jae=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 * ${i} + dm;
              float xValue = getDy(batch, idyR, idyC, d2);
              float wValue = getW(wRPerm, wCPerm, d1, dm);
              dotProd += xValue * wValue;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function Qae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,filterShape:c}=s,p=T.computeConv2DInfo(r.shape,c,o,i,l,u,!0),d=new Yae(p);return n.runWebGLProgram(d,[r,a],"float32")}var eoe={kernelName:c0,backendName:"webgl",kernelFunc:Qae};function toe(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=s,p=T.computeConv2DInfo(c,a.shape,o,i,l,u,!0),d=new Jae(p);return n.runWebGLProgram(d,[r,a],"float32")}var noe={kernelName:d0,backendName:"webgl",kernelFunc:toe},soe=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
      void main() {
          ivec2 coords = getOutputCoords();
          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
          setOutput(val);
      }
    `}};function roe(e){let{inputs:t,backend:n}=e,{x:s}=t,r=[...s.shape,...s.shape],a=v.sizeFromShape(s.shape),o=we({inputs:{x:s},backend:n,attrs:{shape:[a]}}),i=new soe(a),l=n.runWebGLProgram(i,[o],o.dtype),u=we({inputs:{x:l},backend:n,attrs:{shape:r}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(l),u}var aoe={kernelName:p0,backendName:"webgl",kernelFunc:roe},ooe=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:s,strideHeight:r,strideWidth:a,filterHeight:o,filterWidth:i,dilationHeight:l,dilationWidth:u}=e,{top:c,left:p}=s;this.userCode=`
      const ivec2 strides = ivec2(${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 ioe(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l}=s,u=T.computeDilation2DInfo(r.shape,a.shape,o,i,"NHWC",l),c,p=new ooe(u);c=n.runWebGLProgram(p,[r,a],"float32");let d=we({inputs:{x:c},backend:n,attrs:{shape:u.outShape}});return n.disposeIntermediateTensorInfo(c),d}var loe={kernelName:Kp,backendName:"webgl",kernelFunc:ioe};function uoe(e){let{inputs:t,backend:n,attrs:s}=e,{equation:r}=s,a=t,{allDims:o,summedDims:i,idDims:l}=T.decodeEinsumEquation(r,a.length);T.checkEinsumDimSizes(o.length,l,a);let{path:u,steps:c}=T.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}=T.getEinsumPermutation(h,l[g]),A;T.isIdentityPermutation(y)?A=a[g]:(A=cs({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=we({inputs:{x:A},backend:n,attrs:{shape:b}}),f.push(A)),d===null?d=A:(d=gb({inputs:{a:A,b:d},backend:n}),f.push(d))}m<p-1&&(u[m]>=0&&(d=O2({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 coe={kernelName:Zp,backendName:"webgl",kernelFunc:uoe},doe="return (x >= 0.0) ? x : (exp(x) - 1.0);",poe=`
  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;
`,hoe=ht({opSnippet:doe,packedOpSnippet:poe}),foe={kernelName:Do,backendName:"webgl",kernelFunc:hoe},moe="return (b >= 1.0) ? a : a * (b + 1.0);",goe=`
  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,yoe=e=>{let{inputs:t,backend:n}=e,{dy:s,y:r}=t,a=H().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new jh(goe,s.shape,r.shape):new Ic(moe,s.shape,r.shape);return n.runWebGLProgram(a,[s,r],s.dtype)},Aoe={kernelName:h0,backendName:"webgl",kernelFunc:yoe},xoe=`
  return vec4(equal(a, b));
`,boe="return float(a == b);",voe=Bn({opSnippet:boe,packedOpSnippet:xoe,dtype:"bool",cpuKernelImpl:rne}),woe={kernelName:Cl,backendName:"webgl",kernelFunc:voe},koe=`
  // Error function is calculated approximately with elementary function.
  // See "Handbook of Mathematical Functions with Formulas,
  // Graphs, and Mathematical Tables", Abramowitz and Stegun.
  float p = ${T.ERF_P};
  float a1 = ${T.ERF_A1};
  float a2 = ${T.ERF_A2};
  float a3 = ${T.ERF_A3};
  float a4 = ${T.ERF_A4};
  float a5 = ${T.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));
`,Soe=ht({opSnippet:koe}),Ioe={kernelName:Mc,backendName:"webgl",kernelFunc:Soe},Coe=xd+`
  return exp(x);
`,Toe=`
  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;
`,eC=ht({opSnippet:Coe,packedOpSnippet:Toe,cpuKernelImpl:ane,dtype:"float32"}),Noe={kernelName:$o,backendName:"webgl",kernelFunc:eC};function Cy(e){let{inputs:t,attrs:n,backend:s}=e,{dim:r}=n,{input:a}=t,o=a.shape.length,i=a.shape.slice(),l=r;return r<0&&(v.assert(-(o+1)<=r,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+r+1),i.splice(l,0,1),we({inputs:{x:a},backend:s,attrs:{shape:i}})}var Eoe={kernelName:Tl,backendName:"webgl",kernelFunc:Cy},Y7="return exp(x) - 1.0;",Roe=ht({opSnippet:Y7,packedOpSnippet:Y7,cpuKernelImpl:one}),_oe={kernelName:Nl,backendName:"webgl",kernelFunc:Roe},J7=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 tC(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=we({inputs:{x:e},backend:n,attrs:{shape:[o,a]}}),l=i.shape,u=new J7("real",l,t),c=new J7("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=xi({inputs:{real:d,imag:h},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h);let m=we({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(f),m}function Doe(e){let{inputs:t,backend:n}=e,{input:s}=t;return tC(s,!1,n)}var $oe={kernelName:f0,backendName:"webgl",kernelFunc:Doe},Poe=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 Xh(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 Poe(s,r),i=[[r]];return t.runWebGLProgram(o,[],a,i)}}var Foe={kernelName:zc,backendName:"webgl",kernelFunc:Xh},Ooe=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);
        }
    `}},Moe={kernelName:El,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,s=t,r=new Ooe(n.shape);return s.runWebGLProgram(r,[n],n.dtype)}},Q7="return floor(x);",zoe=ht({opSnippet:Q7,packedOpSnippet:Q7,cpuKernelImpl:ine}),Loe={kernelName:Po,backendName:"webgl",kernelFunc:zoe},Boe=`
  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;
  }
`,Woe=`
  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);
`,Voe=Bn({opSnippet:Boe,packedOpSnippet:Woe,dtype:"int32"}),Uoe={kernelName:Fo,backendName:"webgl",kernelFunc:Voe},Goe=class{constructor(e){this.variableNames=["A"];let t=hs(),[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));
      }
    `}},Hoe=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=hs(),[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);
          }
        }

        ${t.output} = result;
      }
    `}},joe={kernelName:Ip,backendName:"webgl",kernelFunc:qoe},Ju,E3=H().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");function qoe(e){let{inputs:t,backend:n,attrs:s}=e,{pixels:r}=t,{numChannels:a}=s,o=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,i=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,[l,u]=o?[r.videoWidth,r.videoHeight]:[r.width,r.height],c=[u,l],p=[u,l,a];if(i||o){let m=H().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(Ju==null||m!==E3)&&(E3=m,Ju=document.createElement("canvas").getContext("2d",{willReadFrequently:E3})),Ju.canvas.width=l,Ju.canvas.height=u,Ju.drawImage(r,0,0,l,u),r=Ju.canvas}let d=n.makeTensorInfo(c,"int32");n.texData.get(d.dataId).usage=Qs.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),r);let h=H().getBool("WEBGL_PACK")?new Hoe(p):new Goe(p),f=n.runWebGLProgram(h,[d],"int32");return n.disposeData(d.dataId),f}function Xoe(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=s,m=T.convertConv2DDataFormat(c),g=T.computeConv2DInfo(r.shape,a.shape,l,p,u,d,!1,m),y,x=[],A=o!=null,b=i!=null,w=h==="leakyrelu",k=()=>{let E=[r,a],_=($,R)=>{if(R==="NCHW"&&$.shape.length===1&&$.shape[0]!==1){let P=we({inputs:{x:$},backend:n,attrs:{shape:[$.shape[0],1,1]}});return x.push(P),P}return $};if(A&&E.push(_(o,c)),b&&E.push(_(i,c)),w){let $=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));E.push($),x.push($)}return E};if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))y=K9({x:r,filter:a,convInfo:g,backend:n,bias:o,activation:h,preluActivationWeights:i,leakyreluAlpha:f});else if(g.strideWidth<=2&&m==="channelsLast"&&H().getBool("WEBGL_EXP_CONV")){let E=h?zp(h,!0):null,_=new X9(g,A,E,b,w),$=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],R=k();y=n.runWebGLProgram(_,R,"float32",$)}else if(H().getBool("WEBGL_CONV_IM2COL"))y=Z9({x:r,filter:a,convInfo:g,backend:n,bias:o,activation:h,preluActivationWeights:i,leakyreluAlpha:f});else{let E=h?zp(h,!1):null,_=new q9(g,A,E,b,w),$=k();y=n.runWebGLProgram(_,$,"float32")}let C=we({inputs:{x:y},backend:n,attrs:{shape:g.outShape}});return x.push(y),x.forEach(E=>n.disposeIntermediateTensorInfo(E)),C}var Koe={kernelName:oo,backendName:"webgl",kernelFunc:Xoe};function Zoe(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(T.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let g=T.computeConv2DInfo(r.shape,a.shape,l,m,u,p,!0),y=H().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,x=d?zp(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 $=n.makeTensorInfo([],"float32",v.createScalarValue(h,"float32"));A.push($),f.push($)}let C;y?C=new Q9(g,b,x,w,k):C=new J9(g,b,x,w,k);let E=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],_=n.runWebGLProgram(C,A,"float32",E);return f.forEach($=>n.disposeIntermediateTensorInfo($)),_}var Yoe={kernelName:io,backendName:"webgl",kernelFunc:Zoe},Joe=class{constructor(e,t,n,s){this.sliceDim=e,this.strides=t,this.paramsShape=s,this.variableNames=["x","indices"],this.outputShape=n;let r=kt(t.length),a=kt(n.length),o=this.sliceDim>1?"strides[j]":"strides",i=kt(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 Qoe(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]=T.prepareAndValidate(s,r),d=we({inputs:{x:r},backend:n,attrs:{shape:[u,o]}}),h=we({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=lne(y,x,s.dtype,u,o,c,p,s.shape,i);return n.makeTensorInfo(l,s.dtype,A.values)}let f=new Joe(o,p,[u,c],s.shape),m=n.runWebGLProgram(f,[h,d],h.dtype),g=we({inputs:{x:m},backend:n,attrs:{shape:l}});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(m),g}var eie={kernelName:_l,backendName:"webgl",kernelFunc:Qoe},tie=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=kt(this.rank),s=nie(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 nie(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 nC(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(H().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, ${A-1}]`)}}let u=T.segment_util.collectGatherOpShapeInfo(r,a,l,i),c=v.sizeFromShape(a.shape),p=[],d=we({inputs:{x:r},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=we({inputs:{x:a},backend:n,attrs:{shape:[u.batchSize,c/u.batchSize]}});p.push(d),p.push(h);let f=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([r,a])||r.dtype==="string"){let x=n.bufferSync(h),A=n.bufferSync(d),b=une(A,x,f);return p.forEach(w=>n.disposeIntermediateTensorInfo(w)),n.makeTensorInfo(u.outputShape,b.dtype,b.values)}let m=new tie(d.shape,f),g=n.runWebGLProgram(m,[d,h],d.dtype);p.push(g);let y=we({inputs:{x:g},backend:n,attrs:{shape:u.outputShape}});return p.forEach(x=>n.disposeIntermediateTensorInfo(x)),y}var sie={kernelName:Rl,backendName:"webgl",kernelFunc:nC},rie="return float(a > b);",aie=`
  return vec4(greaterThan(a, b));
`,oie=Bn({opSnippet:rie,packedOpSnippet:aie,cpuKernelImpl:cne,dtype:"bool"}),iie={kernelName:Dl,backendName:"webgl",kernelFunc:oie},lie="return float(a >= b);",uie=`
  return vec4(greaterThanEqual(a, b));
`,cie=Bn({opSnippet:lie,packedOpSnippet:uie,dtype:"bool",cpuKernelImpl:dne}),die={kernelName:Mo,backendName:"webgl",kernelFunc:cie};function pie(e){let{inputs:t,backend:n}=e,{input:s}=t;return tC(s,!0,n)}var hie={kernelName:m0,backendName:"webgl",kernelFunc:pie},fie="return float(!isnan(x) && !isinf(x));",mie=ht({opSnippet:fie,dtype:"bool"}),gie={kernelName:Lc,backendName:"webgl",kernelFunc:mie},yie="return float(isinf(x));",Aie=ht({opSnippet:yie,dtype:"bool"}),xie={kernelName:Bc,backendName:"webgl",kernelFunc:Aie},bie="return float(isnan(x));",vie=ht({opSnippet:bie,dtype:"bool"}),wie={kernelName:$l,backendName:"webgl",kernelFunc:vie},kie="return float(a < b);",Sie=`
  return vec4(lessThan(a, b));
`,Iie=Bn({opSnippet:kie,packedOpSnippet:Sie,cpuKernelImpl:pne,dtype:"bool"}),Cie={kernelName:Pl,backendName:"webgl",kernelFunc:Iie},Tie="return float(a <= b);",Nie=`
  return vec4(lessThanEqual(a, b));
`,Eie=Bn({opSnippet:Tie,packedOpSnippet:Nie,cpuKernelImpl:hne,dtype:"bool"}),Rie={kernelName:Fl,backendName:"webgl",kernelFunc:Eie};function _ie(e){let{backend:t,attrs:n}=e,{start:s,stop:r,num:a}=n,o=fne(s,r,a);return t.makeTensorInfo([o.length],"float32",o)}var Die={kernelName:g0,backendName:"webgl",kernelFunc:_ie},$ie=xd+`
  return x < 0.0 ? 0./0. : log(x);
`,Pie=`
  vec4 result = log(x);
  bvec4 isNaN = isnan(x);
  result.r = isNaN.r ? x.r : (x.r < 0.0 ? 0./0. : result.r);
  result.g = isNaN.g ? x.g : (x.g < 0.0 ? 0./0. : result.g);
  result.b = isNaN.b ? x.b : (x.b < 0.0 ? 0./0. : result.b);
  result.a = isNaN.a ? x.a : (x.a < 0.0 ? 0./0. : result.a);
  return result;
`,Fie=ht({opSnippet:$ie,packedOpSnippet:Pie,cpuKernelImpl:mne}),Oie={kernelName:Bo,backendName:"webgl",kernelFunc:Fie},Mie=xd+`
  return log(1.0 + x);
`,zie=ht({opSnippet:Mie}),Lie={kernelName:Wc,backendName:"webgl",kernelFunc:zie},Bie="return float(a >= 1.0 && b >= 1.0);",Wie=`
  return vec4(
    vec4(greaterThanEqual(a, vec4(1.0))) *
    vec4(greaterThanEqual(b, vec4(1.0))));
`,Vie=Bn({opSnippet:Bie,packedOpSnippet:Wie,dtype:"bool"}),Uie={kernelName:Ol,backendName:"webgl",kernelFunc:Vie},Gie="return float(!(x >= 1.0));",Hie=ht({opSnippet:Gie}),jie={kernelName:Ml,backendName:"webgl",kernelFunc:Hie},qie="return float(a >= 1.0 || b >= 1.0);",Xie=`
  return min(
    vec4(greaterThanEqual(a, vec4(1.0))) +
    vec4(greaterThanEqual(b, vec4(1.0))),
    vec4(1.0));
`,Kie=Bn({opSnippet:qie,packedOpSnippet:Xie,dtype:"bool"}),Zie={kernelName:Vc,backendName:"webgl",kernelFunc:Kie},Yie=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 * ${i};
        setOutput(val);
      }
    `}},Jie=class{constructor(e,t,n,s,r){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let a=t,o=e[3]-1;this.outputShape=e;let i,l=`float(${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);
      }
    `}},Qie=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{depthRadius:a,bias:o,alpha:i,beta:l}=s,u=H().getBool("WEBGL_PACK_NORMALIZATION")?new Jie(r.shape,a,o,i,l):new Yie(r.shape,a,o,i,l);return n.runWebGLProgram(u,[r],r.dtype)},ele={kernelName:Jp,backendName:"webgl",kernelFunc:Qie},tle=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);
      }
    `}},nle=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 tle(r.shape,i,l,u,c);return n.runWebGLProgram(p,[r,a,o],r.dtype)},sle={kernelName:y0,backendName:"webgl",kernelFunc:nle};function rle(e,t,n,s){let r=v.sizeFromShape(t),o=v.sizeFromShape(e.shape)/r,i=we({inputs:{x:e},attrs:{shape:[o,r]},backend:s}),l=bu(i,e.dtype,"max",s),u=we({inputs:{x:l},attrs:{shape:n},backend:s});return s.disposeIntermediateTensorInfo(i),s.disposeIntermediateTensorInfo(l),u}function sC(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=T.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 C=0;C<b.length;C++)b[C]=r.shape[c[C]];let w=mb(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=F2(r,c,n);u=T.getInnerMostAxes(u.length,i)}T.assertAxesAreInnerMostDims("max",u,i);let[f,m]=T.computeOutAndReduceShapes(h.shape,u),g=f;o&&(g=T.expandShapeToKeepDim(f,l));let y;if(d){let A=n.texData.get(h.dataId).values,b=gne(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=rle(h,m,g,n);return p&&n.disposeIntermediateTensorInfo(h),y}var ale={kernelName:Wo,backendName:"webgl",kernelFunc:sC},ole=F9+`
  return max(a, b);
`,ile=`
  vec4 result = vec4(max(a, b));
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  `+P2+`
  return result;
`,lle=Bn({opSnippet:ole,packedOpSnippet:ile,cpuKernelImpl:yne}),ule={kernelName:Vo,backendName:"webgl",kernelFunc:lle};function cle(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;hd(r,"maxPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;v.assert(T.eitherStridesOrDilationsAreOne(o,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=T.computePool2DInfo(r.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Vs({inputs:{x:r},backend:n});let p=new Lp(c,"max",!1);return n.runWebGLProgram(p,[r],r.dtype)}var dle={kernelName:Uo,backendName:"webgl",kernelFunc:cle};function ple(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=T.computePool3DInfo(r.shape,a,o,c,i,u,l),d=new yb(p,"max",!1);return n.runWebGLProgram(d,[r],r.dtype)}var hle={kernelName:Qp,backendName:"webgl",kernelFunc:ple},fle=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);
      }
    `}},mle=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 gle(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=T.computePool3DInfo(o.shape,i,l,p,u,c),h=new yb(d,"max",!0),f=n.runWebGLProgram(h,[o],o.dtype),m=new mle(d),g=n.runWebGLProgram(m,[r,f],o.dtype);return n.disposeIntermediateTensorInfo(f),g}var yle={kernelName:x0,backendName:"webgl",kernelFunc:gle};function Ale(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a,output:o}=t,i=a;hd([a,o],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:p}=s,d=T.computePool2DInfo(i.shape,l,u,1,c,p),h=!0,f=new Lp(d,"max",h),m=n.runWebGLProgram(f,[i],i.dtype),g=new fle(d),y=n.runWebGLProgram(g,[r,m],i.dtype);return n.disposeIntermediateTensorInfo(m),y}var xle={kernelName:A0,backendName:"webgl",kernelFunc:Ale};function ble(e,t,n,s){let r=new Lp(n,"max",!1),a=s.runWebGLProgram(r,[e],"float32");r=new Lp(n,"max",!0,!0,t);let o=s.runWebGLProgram(r,[e],"float32");return[a,o]}var vle={kernelName:b0,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(T.eitherStridesOrDilationsAreOne(a,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${u}'`);let c=T.computePool2DInfo(s.shape,r,a,u,o),[p,d]=ble(s,i,c,l);return[p,d]}};function wle(e,t,n,s){let r=v.sizeFromShape(t),o=v.sizeFromShape(e.shape)/r,i=we({inputs:{x:e},attrs:{shape:[o,r]},backend:s}),l=bu(i,"float32","mean",s),u=we({inputs:{x:l},attrs:{shape:n},backend:s});return s.disposeIntermediateTensorInfo(i),s.disposeIntermediateTensorInfo(l),u}var kle={kernelName:Go,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=T.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=mb(b,s.shape,s.dtype,c,w);f=o.makeTensorInfo(w,s.dtype);let C=o.texData.get(f.dataId);C.values=k}else f=F2(s,c,o);h.push(f),u=T.getInnerMostAxes(u.length,i)}T.assertAxesAreInnerMostDims("sum",u,i);let[m,g]=T.computeOutAndReduceShapes(f.shape,u),y=m;r&&(y=T.expandShapeToKeepDim(m,l));let x=wle(f,g,y,o);for(let A of h)o.disposeIntermediateTensorInfo(A);return x}};function Sle(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=T.getAxesPermutation(u,i),p=r;c!=null&&(p=cs({inputs:{x:r},backend:n,attrs:{perm:c}}),u=T.getInnerMostAxes(u.length,r.shape.length)),T.assertAxesAreInnerMostDims("min",u,i);let[d,h]=T.computeOutAndReduceShapes(p.shape,u),f=v.sizeFromShape(h),m=we({inputs:{x:p},backend:n,attrs:{shape:[-1,f]}}),g=bu(m,m.dtype,"min",n),y;if(o){let x=T.expandShapeToKeepDim(d,l);y=we({inputs:{x:g},backend:n,attrs:{shape:x}})}else y=we({inputs:{x:g},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(p),y}var Ile={kernelName:Ho,backendName:"webgl",kernelFunc:Sle},Cle=F9+`
  return min(a, b);
`,Tle=`
  vec4 result = vec4(min(a, b));
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  `+P2+`
  return result;
`,Nle=Bn({opSnippet:Cle,packedOpSnippet:Tle,cpuKernelImpl:Ane}),Ele={kernelName:jo,backendName:"webgl",kernelFunc:Nle},Rle=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=kt(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}));
      }
    `}},_le=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=kt(s),a=t.map(h=>h[0]).join(","),o=t.map((h,f)=>h[0]+e[f]).join(","),i=us("rc",s),l=us("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.);
        ${d}
        setOutput(result);
      }
    `}},Dle=({inputs:e,backend:t,attrs:n})=>{let{x:s}=e,{paddings:r,mode:a}=n,o=H().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new _le(s.shape,r,a):new Rle(s.shape,r,a);return t.runWebGLProgram(o,[s],s.dtype)},$le={kernelName:qo,backendName:"webgl",kernelFunc:Dle},Ple=`if (b == 0.0) return NAN;
  return mod(a, b);`,Fle=`
  vec4 result = mod(a, b);
  vec4 isNaN = vec4(equal(b, vec4(0.0)));
  `+P2+`
  return result;
`,Ole=Bn({opSnippet:Ple,packedOpSnippet:Fle}),Mle={kernelName:Uc,backendName:"webgl",kernelFunc:Ole},zle=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}));
      }
    `}},Lle=`
if (a == b) {
  return 1.0;
};
return a / b;`,Ble=`
  // 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;
`,rC=Bn({opSnippet:Lle,packedOpSnippet:Ble,checkOutOfBounds:!0}),Wle={kernelName:_o,backendName:"webgl",kernelFunc:rC},e6="return a - b;",aC=Bn({opSnippet:e6,packedOpSnippet:e6,supportsComplex:!0,cpuKernelImpl:One}),Vle={kernelName:ci,backendName:"webgl",kernelFunc:aC};function oC(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{dim:a}=s,o=v.parseAxisParam([a],r.shape),i=sC({inputs:{x:r},backend:n,attrs:{reductionIndices:o,keepDims:!1}}),l=T.expandShapeToKeepDim(i.shape,o),u=we({inputs:{x:i},backend:n,attrs:{shape:l}}),c=aC({inputs:{a:r,b:u},backend:n}),p=eC({inputs:{x:c},backend:n}),d=O2({inputs:{x:p},backend:n,attrs:{axis:o,keepDims:!1}}),h=we({inputs:{x:d},backend:n,attrs:{shape:l}}),f=rC({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 Ule={kernelName:li,backendName:"webgl",kernelFunc:oC};function Gle(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{numSamples:a,seed:o,normalized:i}=s,l=i?r:oC({inputs:{logits:r},backend:n,attrs:{dim:r.shape.length-1}}),u=l.shape[0],c=l.shape[1],p=new zle(u,c,a),d=[[o]],h=n.runWebGLProgram(p,[l],"int32",d);return i||n.disposeIntermediateTensorInfo(l),h}var Hle={kernelName:v0,backendName:"webgl",kernelFunc:Gle},jle=br+`
  return -x;
`,qle=`
  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 Xle(e){let{inputs:t,backend:n}=e,{x:s}=t;if(n.shouldExecuteOnCPU([s])){let a=n.texData.get(s.dataId),[o,i]=bne(a.values,s.shape,s.dtype);return n.makeTensorInfo(i,s.dtype,o)}let r;return H().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new el(s.shape,qle):r=new Sa(s.shape,jle),n.runWebGLProgram(r,[s],s.dtype)}var Kle={kernelName:zl,backendName:"webgl",kernelFunc:Xle},Zle=Ar.nonMaxSuppressionV3Impl;function Yle(e){T.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}=Zle(u,c,o,i,l);return n.makeTensorInfo([p.length],"int32",new Int32Array(p))}var Jle={kernelName:Bl,backendName:"webgl",kernelFunc:Yle},Qle=Ar.nonMaxSuppressionV4Impl;function eue(e){T.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}=Qle(c,p,o,i,l,u);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([h]))]}var tue={kernelName:Gc,backendName:"webgl",kernelFunc:eue},nue=Ar.nonMaxSuppressionV5Impl;function sue(e){T.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}=nue(c,p,d,h,f,m);return[n.makeTensorInfo([g.length],"int32",new Int32Array(g)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var rue={kernelName:Wl,backendName:"webgl",kernelFunc:sue},aue=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)));
      }
    `}},oue=e=>{let{inputs:t,backend:n,attrs:s}=e,{indices:r}=t,{dtype:a,depth:o,onValue:i,offValue:l}=s,u=v.sizeFromShape(r.shape),c=new aue(u,o,i,l),p=we({inputs:{x:r},backend:n,attrs:{shape:[u]}}),d=n.runWebGLProgram(c,[p],a);n.disposeIntermediateTensorInfo(p);let h=[...r.shape,o],f=we({inputs:{x:d},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(d),f},iue={kernelName:Ul,backendName:"webgl",kernelFunc:oue};function Km(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="complex64"){let r=qh({inputs:{input:s},backend:n}),a=Km({inputs:{x:r},backend:n}),o=M2({inputs:{input:s},backend:n}),i=Km({inputs:{x:o},backend:n}),l=xi({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return Xh({attrs:{shape:s.shape,dtype:s.dtype,value:s.dtype==="string"?"":0},backend:n})}var lue={kernelName:ou,backendName:"webgl",kernelFunc:Km};function iC(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=qh({inputs:{input:s},backend:n}),a=iC({inputs:{x:r},backend:n}),o=M2({inputs:{input:s},backend:n}),i=Km({inputs:{x:o},backend:n}),l=xi({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return Xh({attrs:{shape:s.shape,dtype:s.dtype,value:1},backend:n})}var uue={kernelName:Vl,backendName:"webgl",kernelFunc:iC};function cue(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return Cy({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=Cy({inputs:{input:c},backend:n,attrs:{dim:r}});return i.push(p),p}),u=j9({inputs:l,backend:n,attrs:{axis:r}});return i.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var due={kernelName:Gl,backendName:"webgl",kernelFunc:cue},pue=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=kt(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}));
        }
      }
    `}},hue=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=kt(s),a=t.map(f=>f[0]).join(","),o=t.map((f,m)=>f[0]+e[m]).join(","),i=us("rc",s),l=us("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);
      }
    `}},lC=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 Xh({backend:n,attrs:{shape:u,value:o,dtype:r.dtype}})}let i=H().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new hue(r.shape,a,o):new pue(r.shape,a,o),l=[[o]];return n.runWebGLProgram(i,[r],r.dtype,l)},fue={kernelName:Ko,backendName:"webgl",kernelFunc:lC},mue=`
  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);
`,gue=`
  // 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));
  `+P2+`
  return result;
`,yue=Bn({opSnippet:mue,packedOpSnippet:gue}),Aue={kernelName:Zo,backendName:"webgl",kernelFunc:yue};function xue(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=T.getAxesPermutation(c,i),d=r;p!=null&&(d=cs({inputs:{x:r},backend:n,attrs:{perm:p}}),c=T.getInnerMostAxes(c.length,i),l.push(d)),T.assertAxesAreInnerMostDims("prod",c,i);let h;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:g,outDtype:y}=wne(d.shape,d.dtype,f,c);h=n.makeTensorInfo(g,y,m)}else{let[f,m]=T.computeOutAndReduceShapes(d.shape,c),g=v.sizeFromShape(m),y=we({inputs:{x:d},backend:n,attrs:{shape:[-1,g]}}),x=ch(r.dtype),A=bu(y,x,"prod",n);h=we({inputs:{x:A},backend:n,attrs:{shape:f}}),l.push(y),l.push(A)}if(o){l.push(h);let f=T.expandShapeToKeepDim(h.shape,u);h=we({inputs:{x:h},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),h}var bue={kernelName:Jo,backendName:"webgl",kernelFunc:xue};function vue(e){let{inputs:t,backend:n,attrs:s}=e,{shape:r,values:a,defaultValue:o,rowPartitionTensors:i}=t,{rowPartitionTypes:l}=s,u=n.readSync(r.dataId),c=n.readSync(a.dataId),p=n.readSync(o.dataId),d=i.map(g=>n.readSync(g.dataId)),h=i.map(g=>g.shape),[f,m]=kne(u,r.shape,c,a.shape,a.dtype,p,o.shape,d,h,l);return n.makeTensorInfo(f,a.dtype,m)}var wue={kernelName:w0,backendName:"webgl",kernelFunc:vue},uC=e=>{let{backend:t,attrs:n}=e,{start:s,stop:r,step:a,dtype:o}=n,i=Sne(s,r,a,o);return t.makeTensorInfo([i.length],o,i)},kue={kernelName:Hc,backendName:"webgl",kernelFunc:uC},Sue="return 1.0 / x;",Iue=ht({opSnippet:Sue}),Cue={kernelName:Hl,backendName:"webgl",kernelFunc:Iue},Tue=br+`
  return (x < 0.0) ? 0.0 : x;
`,Nue=`
  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;
`,Eue=ht({opSnippet:Tue,packedOpSnippet:Nue}),Rue={kernelName:Qo,backendName:"webgl",kernelFunc:Eue},_ue=br+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,Due=`
  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;
`,$ue=ht({opSnippet:_ue,packedOpSnippet:Due}),Pue={kernelName:ni,backendName:"webgl",kernelFunc:$ue},Fue=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);
      }
    `}},Oue=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 Mue(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,c=H().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Oue(r.shape,l,u,a,o):new Fue(r.shape,l,u,a,o);return n.runWebGLProgram(c,[r],"float32")}var zue={kernelName:ti,backendName:"webgl",kernelFunc:Mue},Lue=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 Bue(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s,i=new Lue(a.shape,r.shape,o);return n.runWebGLProgram(i,[a],a.dtype)}var Wue={kernelName:S0,backendName:"webgl",kernelFunc:Bue},Vue=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);
      }
    `}},Uue=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 Gue(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,c=H().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Uue(r.shape,l,u,a,o):new Vue(r.shape,l,u,a,o);return n.runWebGLProgram(c,[r],r.dtype)}var Hue={kernelName:ei,backendName:"webgl",kernelFunc:Gue},jue=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 que(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s,i=new jue(a.shape,r.shape,o);return n.runWebGLProgram(i,[a],a.dtype)}var Xue={kernelName:k0,backendName:"webgl",kernelFunc:que},Kue=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=kt(n);this.userCode=`
      void main() {
        ${a} coords = getOutputCoords();
        setOutput(getX(${r}));
      }
    `}},Zue=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-${n} tensor is not yet supported`);this.outputShape=e;let s=us("rc",n),r=`${s[n-1]} + 1 < ${this.outputShape[n-1]}`,a=`${s[n-2]} + 1 < ${this.outputShape[n-2]}`,o=kt(n);n===1?this.userCode=`
        void main(){
          int rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = getChannel(getX(${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 Yue(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 Vs({inputs:{x:r},backend:n});let l=H().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Zue(r.shape,i):new Kue(r.shape,i);return n.runWebGLProgram(l,[r],r.dtype)}var Jue={kernelName:ql,backendName:"webgl",kernelFunc:Yue},Que=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 < ${n}) {
            outputValue = getImage(coords[0], coordY, coordX, coords[3]);
          }
          setOutput(outputValue);
        }
    `}},ece={kernelName:iu,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:s}=e,{radians:r,fillValue:a,center:o}=t,i=n,l=new Que(s.shape,a),[u,c]=T.getImageCenter(o,s.shape[1],s.shape[2]),p=[[u,c,Math.sin(r),Math.cos(r)]];return i.runWebGLProgram(l,[s],s.dtype,p)}},tce=`
  // OpenGL ES does not support round function.
  // The algorithm is based on banker's rounding.
  float base = floor(x);
  if ((x - base) < 0.5) {
    return floor(x);
  } else if ((x - base) > 0.5) {
    return ceil(x);
  } else {
    if (mod(base, 2.0) == 0.0) {
      return base;
    } else {
      return base + 1.0;
    }
  }
`,nce=ht({opSnippet:tce}),sce={kernelName:Xl,backendName:"webgl",kernelFunc:nce},rce="return inversesqrt(x);",ace=ht({opSnippet:rce,cpuKernelImpl:Ine}),oce={kernelName:si,backendName:"webgl",kernelFunc:ace},cC=class{constructor(e,t,n,s,r,a,o=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=a;let i=kt(r.length),l=kt(a.length),u="";n===1?u="i":n===2&&(u="i, j");let c=`getIndices(${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 ice(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}=T.calculateShapes(a,r,o),d=[p/u,u];if(p===0)return n.makeTensorInfo(o,r.dtype);let h=we({inputs:{x:r},backend:n,attrs:{shape:[l,i]}}),f=we({inputs:{x:a},backend:n,attrs:{shape:[l,u]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),g=new cC(l,i,h.shape.length,f.shape.length,c,d),y=n.runWebGLProgram(g,[f,h,m],f.dtype),x=we({inputs:{x:y},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),x}var lce={kernelName:Kl,backendName:"webgl",kernelFunc:ice},uce=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=H().getNumber("WEBGL_VERSION")===2?r:a,i=s==="left"?"<":"<=";this.userCode=`
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         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 cce(e){let{inputs:t,backend:n,attrs:s}=e,{sortedSequence:r,values:a}=t,{side:o}=s,i=new uce(r.shape[0],r.shape[1],a.shape[1],o),l=[[r.shape[1]]];return n.runWebGLProgram(i,[r,a],"int32",l)}var dce={kernelName:I0,backendName:"webgl",kernelFunc:cce},pce=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=kt(n);this.userCode=`
      void main() {
        ${a} resRC = getOutputCoords();
        float cVal = getC(${s});
        if (cVal >= 1.0) {
          setOutput(getA(${r}));
        } else {
          setOutput(getB(${r}));
        }
      }
    `}};function hce(e){let{inputs:t,backend:n}=e,{condition:s,t:r,e:a}=t,o=new pce(s.shape.length,r.shape,r.shape.length);return n.runWebGLProgram(o,[s,r,a],Hn(r.dtype,a.dtype))}var fce={kernelName:Zl,backendName:"webgl",kernelFunc:hce},mce=`
  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
  // see: https://arxiv.org/abs/1706.02515
  float scaleAlpha = ${T.SELU_SCALEALPHA};
  float scale = ${T.SELU_SCALE};
  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,gce=ht({opSnippet:mce}),yce={kernelName:jc,backendName:"webgl",kernelFunc:gce},Ace=xd+`
  return 1.0 / (1.0 + exp(-1.0 * x));
`,xce=`
  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;
`,bce=ht({opSnippet:Ace,packedOpSnippet:xce,cpuKernelImpl:Tne}),vce={kernelName:ai,backendName:"webgl",kernelFunc:bce},wce=`
  if (isnan(x)) { return 0.0; }
  return sign(x);
`,kce=ht({opSnippet:wce}),Sce={kernelName:qc,backendName:"webgl",kernelFunc:kce},Ice=xd+`
  return sin(x);
`,Cce=ht({opSnippet:Ice}),Tce={kernelName:ri,backendName:"webgl",kernelFunc:Cce},Nce=`
  float e2x = exp(x);
  return (e2x - 1.0 / e2x) / 2.0;
`,Ece=ht({opSnippet:Nce}),Rce={kernelName:Jl,backendName:"webgl",kernelFunc:Ece},_ce=`
  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;
`,Dce=ht({opSnippet:_ce}),$ce={kernelName:Xc,backendName:"webgl",kernelFunc:Dce},Pce=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=lC({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),p=T.getReshaped(c.shape,a,i,!1),d=T.getPermuted(p.length,a.length,!1),h=T.getReshapedPermuted(c.shape,a,i,!1),f=we({inputs:{x:c},backend:n,attrs:{shape:p}}),m=cs({inputs:{x:f},backend:n,attrs:{perm:d}}),g=we({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},Fce={kernelName:Ql,backendName:"webgl",kernelFunc:Pce};function Oce(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]=Ene(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 Mce={kernelName:th,backendName:"webgl",kernelFunc:Oce};function zce(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]=Rne(i,s.shape,s.dtype,o,l);return[n.makeTensorInfo(c,s.dtype,u),n.makeTensorInfo([p.length],a.dtype,new Int32Array(p))]}var Lce={kernelName:Kc,backendName:"webgl",kernelFunc:zce};function Bce(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]=_9(o,s.shape,s.dtype,i,l,!0);return n.makeTensorInfo(c,s.dtype,u)}var Wce={kernelName:nh,backendName:"webgl",kernelFunc:Bce};function Vce(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
             ${a.shape}`);let o=n.readSync(s.dataId),i=n.readSync(r.dataId),l=n.readSync(a.dataId),[u,c]=_9(o,s.shape,s.dtype,i,l);return n.makeTensorInfo(c,s.dtype,u)}var Uce={kernelName:sh,backendName:"webgl",kernelFunc:Vce};function Gce(e){let{inputs:t,backend:n,attrs:s}=e,{sparseIndices:r,sparseValues:a,defaultValue:o}=t,{outputShape:i}=s,{sliceRank:l,numUpdates:u,sliceSize:c,strides:p,outputSize:d}=T.calculateShapes(a,r,i),h=!1;if(a.dtype==="string"){let y=n.bufferSync(r),x=n.bufferSync(a),A=v.decodeString(n.readSync(o.dataId)[0]),b=Cne(y,x,i,d,c,u,l,p,A,h);return n.makeTensorInfo(i,b.dtype,b.values)}let f=new cC(u,l,r.shape.length,a.shape.length,p,[d,1],h),m=n.runWebGLProgram(f,[a,r,o],a.dtype),g=we({inputs:{x:m},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(m),g}var Hce={kernelName:rh,backendName:"webgl",kernelFunc:Gce};function jce(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{numOrSizeSplits:a,axis:o}=s,i=v.parseAxisParam(o,r.shape)[0],l=T.prepareSplitSize(r,a,i),u=r.shape.length,c=new Array(u).fill(0),p=r.shape.slice();return l.map(d=>{let h=[...p];h[i]=d;let f=bd({inputs:{x:r},backend:n,attrs:{begin:c,size:h}});return c[i]+=d,f})}var qce={kernelName:eu,backendName:"webgl",kernelFunc:jce},t6="return sqrt(x);",Xce=ht({opSnippet:t6,packedOpSnippet:t6,cpuKernelImpl:_ne}),Kce={kernelName:oi,backendName:"webgl",kernelFunc:Xce},Zce="return x * x;",Yce=ht({opSnippet:Zce}),Jce={kernelName:Zc,backendName:"webgl",kernelFunc:Yce},n6="return (a - b) * (a - b);",Qce=Bn({opSnippet:n6,packedOpSnippet:n6}),ede={kernelName:ui,backendName:"webgl",kernelFunc:Qce};function tde({inputs:e,attrs:t,backend:n}){let{x:s}=e,r=br+`
    return x > 0.0 ? 1.0 : float(${t.alpha});
  `,a=new Sa(s.shape,r);return n.runWebGLProgram(a,[s],s.dtype)}var nde={kernelName:pi,backendName:"webgl",kernelFunc:tde},sde=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let s=n.length,r=kt(n.length),a=kt(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 rde(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}=jt.sliceInfo(r.shape,a,o,i,l,u,c,p,d),w;if(m)w=we({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: ${r.shape.length}`);let C=jt.computeOutShape(x,A,b),E=bd({inputs:{x:r},backend:n,attrs:{begin:x,size:C}});w=we({inputs:{x:E},backend:n,attrs:{shape:f}}),n.disposeIntermediateTensorInfo(E)}else if(n.shouldExecuteOnCPU([r])){let E=n.readSync(r.dataId),_=Ue(r.shape,r.dtype,E),$=Dne(h,_,b,x);w=n.makeTensorInfo(f,r.dtype,$.values)}else{let E=new sde(x,b,h);w=n.runWebGLProgram(E,[r],r.dtype)}let k=we({inputs:{x:w},backend:n,attrs:{shape:f}});return n.disposeIntermediateTensorInfo(w),k}var ade={kernelName:tu,backendName:"webgl",kernelFunc:rde};function ode(e){let{inputs:t,backend:n,attrs:s}=e,{separator:r,nGramWidths:a,leftPad:o,rightPad:i,padWidth:l,preserveShortSequences:u}=s,{data:c,dataSplits:p}=t,d=n.readSync(c.dataId),h=n.readSync(p.dataId),[f,m]=$ne(d,h,r,a,o,i,l,u);return[n.makeTensorInfo([f.length],"string",f),n.makeTensorInfo(p.shape,"int32",m)]}var ide={kernelName:Yc,backendName:"webgl",kernelFunc:ode};function lde(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]=Pne(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 ude={kernelName:ah,backendName:"webgl",kernelFunc:lde};function cde(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=Fne(o,r);return n.makeTensorInfo(a.shape,"int32",i)}var dde={kernelName:oh,backendName:"webgl",kernelFunc:cde},pde="return tan(x);",hde=ht({opSnippet:pde}),fde={kernelName:nu,backendName:"webgl",kernelFunc:hde},mde=`
  float e2x = exp(-2.0 * abs(x));
  return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,gde=ht({opSnippet:mde}),yde={kernelName:di,backendName:"webgl",kernelFunc:gde},Ade=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=kt(this.rank),r=xde(e);this.userCode=`
      void main() {
        ${s} resRC = getOutputCoords();
        setOutput(getA(${r}));
      }
    `}};function xde(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 dC(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=Ue(r.shape,r.dtype,u),p=Mne(c,a);return n.makeTensorInfo(p.shape,p.dtype,p.values)}let o=new Ade(r.shape,a);return n.runWebGLProgram(o,[r],r.dtype)}var bde={kernelName:Pa,backendName:"webgl",kernelFunc:dC},vde=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));
         }
       }
     `}},wde=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 Gi(e,t){t!==null&&e.disposeIntermediateTensorInfo(t)}function s6(e){let t=1;for(;t<e;)t*=2;return t}function kde(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{k:a,sorted:o}=s,i=H().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),l=H().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),u=r.shape,c=u[u.length-1];if(n.shouldExecuteOnCPU([r])||c<i||a>l){let $=n.readSync(r.dataId),[R,P]=zne($,u,r.dtype,a,o);return[n.makeTensorInfo(R.shape,R.dtype,R.values),n.makeTensorInfo(P.shape,P.dtype,P.values)]}if(a===0)return u[u.length-1]=0,[n.makeTensorInfo(u,r.dtype,[]),n.makeTensorInfo(u,"int32",[])];if(c===1)return[r,Xh({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=we({inputs:{x:h},attrs:{shape:[m,c]},backend:n});d&&Gi(n,h);let y=s6(a),x=s6(c),A=null,b=()=>A===null?[g,g]:[g,A],w=($,R,P)=>{let S=b(),M=new vde(P),U=[[c],[A===null?1:0],[Number.NEGATIVE_INFINITY],[$],[R]],K=A;A=n.runWebGLProgram(M,S,"int32",U),Gi(n,K)};for(let $=1;$<y;$*=2){let R=$*2;for(let P=$;P>=1;P/=2)w(R,P,[m,x])}for(let $=x;$>y;$/=2){let R=b(),P=new wde([m,$/2]),M=[[c],[A===null?1:0],[y]],L=A;A=n.runWebGLProgram(P,R,"int32",M),Gi(n,L);let U=y/2,K=U*2;for(let q=U;q>=1;q/=2)w(K,q,A.shape)}let k=A;A=bd({inputs:{x:A},backend:n,attrs:{begin:0,size:[m,a]}}),Gi(n,k);let C=nC({inputs:{x:g,indices:A},backend:n,attrs:{axis:1,batchDims:1}});Gi(n,g);let E=u.slice(0,-1);E.push(a),k=A,A=we({inputs:{x:A},attrs:{shape:E},backend:n}),Gi(n,k);let _=C;return C=we({inputs:{x:C},attrs:{shape:E},backend:n}),Gi(n,_),[C,A]}var Sde={kernelName:su,backendName:"webgl",kernelFunc:kde},Ide=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 Cde(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 Ide(p,d,o,i,l,g);return n.runWebGLProgram(y,[r,a],"float32")}var Tde={kernelName:ru,backendName:"webgl",kernelFunc:Cde};function Nde(e){let{inputs:t,attrs:n,backend:s}=e,{axis:r}=n,{x:a}=t;hd(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}=Lne(o,r,a.shape,a.dtype);return[s.makeTensorInfo(l,a.dtype,i),s.makeTensorInfo([u.length],"int32",u)]}var Ede={kernelName:C0,backendName:"webgl",kernelFunc:Nde};function Rde(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=bd({inputs:{x:o},backend:n,attrs:{begin:d,size:h}}),y=we({inputs:{x:g},backend:n,attrs:{shape:u}});f[m]=y,p.push(g)}return p.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var _de={kernelName:au,backendName:"webgl",kernelFunc:Rde},Dde=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 $de(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,segmentIds:a}=t,{numSegments:o}=s,i=r.shape.length,l=[],u=0,c=T.getAxesPermutation([u],i),p=r;c!=null&&(p=cs({inputs:{x:r},backend:n,attrs:{perm:c}}),l.push(p),u=T.getInnerMostAxes(1,i)[0]);let d=T.segment_util.computeOutShape(p.shape,u,o),h=v.sizeFromShape([p.shape[u]]),f=we({inputs:{x:p},backend:n,attrs:{shape:[-1,h]}});l.push(f);let m=ch(r.dtype),g=(b,w,k,C,E)=>{let _=b.shape[0],$=b.shape[1],R=T.segment_util.segOpComputeOptimalWindowSize($,E),P={windowSize:R,inSize:$,batchSize:_,numSegments:E},S=new Dde(P,w),M=n.compileAndRun(S,[b,k],C);if(l.push(M),M.shape[1]===E)return M;let L=uC({backend:n,attrs:{start:0,stop:E,step:1,dtype:"float32"}}),U=dC({inputs:{x:L},backend:n,attrs:{reps:[$/R]}});return l.push(L),l.push(U),g(M,w,U,C,E)},y=g(f,"unsortedSegmentSum",a,m,o),x=we({inputs:{x:y},backend:n,attrs:{shape:d}}),A=x;if(c!=null){l.push(x);let b=T.getUndoAxesPermutation(c);A=cs({inputs:{x:A},backend:n,attrs:{perm:b}})}return l.forEach(b=>n.disposeIntermediateTensorInfo(b)),A}var Pde={kernelName:ih,backendName:"webgl",kernelFunc:$de},Fde=[Pse,Ose,Lse,Vse,Gse,qse,Kse,Yse,tre,sre,ore,ure,pre,gre,xre,vre,kre,Tre,Ere,_re,Fre,Vre,Gre,jre,Jre,eae,rae,mse,iae,pae,gae,wae,Sae,Cae,Nae,Rae,$ae,Oae,Lae,Wae,Uae,Hae,Xae,Zae,eoe,noe,aoe,loe,coe,foe,Aoe,woe,Ioe,Noe,Eoe,_oe,$oe,Foe,Moe,Loe,Uoe,joe,Koe,Yoe,eie,sie,iie,die,fse,hie,cae,gie,xie,wie,yse,Cie,Rie,Die,Oie,Lie,Uie,jie,Zie,ele,sle,ale,ule,dle,hle,yle,xle,vle,kle,Ile,Ele,$le,Mle,Hle,wse,Kle,Jle,tue,rue,Xre,iue,uue,due,fue,Aue,xse,bue,wue,kue,Kre,Wle,Cue,Rue,Pue,Sse,zue,Wue,Hue,Xue,Jue,ece,sce,oce,lce,dce,fce,yce,vce,Sce,Tce,Rce,Bre,Ule,$ce,Fce,Mce,Lce,Wce,Uce,Hce,qce,Kce,Jce,ede,nde,ade,ide,ude,dde,Vle,_se,fde,yde,bde,Sde,Tde,Dse,Ede,_de,Pde,lue];for(let e of Fde)rr(e);var Kt;(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"})(Kt||(Kt={}));var Wp;(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"})(Wp||(Wp={}));var pC;function Ode(e){pC=e.wasm.cwrap(ao,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function Mde(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 ${E.shape.length}.`);f=E.id}let m=i==null?0:n.dataIdMap.get(i.dataId).id,g=Wp[c];if(g==null)throw new Error(`${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=uu.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),C=new Uint8Array(new Int32Array(a.shape).buffer);return pC(d,k,r.shape.length,h,C,a.shape.length,l,u,g,f,m,p||0,w),b}var zde={kernelName:ao,backendName:"wasm",setupFunc:Ode,kernelFunc:Mde};function _n(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,Kt[i.dtype],c),u}return{kernelName:e,backendName:"wasm",setupFunc:s,kernelFunc:r}}var Lde=_n(xl);function Wn(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=T.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,Kt[u.dtype],x))(),m}return{kernelName:e,backendName:"wasm",setupFunc:r,kernelFunc:a}}var Bde=!0,Wde=Wn(Da,Bde),hC;function Vde(e){hC=e.wasm.cwrap(xo,null,["array","number","number","number"])}function Ude(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 hC(a,r.length,Kt[s.dtype],o),s}var Gde={kernelName:xo,backendName:"wasm",setupFunc:Vde,kernelFunc:Ude};function z2(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 Hde={kernelName:zo,backendName:"wasm",kernelFunc:z2},fC;function jde(e){fC=e.wasm.cwrap(na,null,["number","array","number","number","number","array","number"])}function go(e){let{inputs:t,backend:n,attrs:s}=e,[r,a]=Xde(t.x.shape,s.perm),o=!0;for(let f=0;f<a.length;f++)a[f]!==f&&(o=!1);let i=qde(t.x.shape,s.perm),l={dataId:t.x.dataId,shape:r,dtype:t.x.dtype};if(o){let f=z2({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 fC(c,h,l.shape.length,Kt[l.dtype],p,d,a.length),u}function qde(e,t){let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];return n}function Xde(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 Kde={kernelName:na,backendName:"wasm",kernelFunc:go,setupFunc:jde};function bi(e,t,n){let s=e.shape,r=e.shape.length,a=v.parseAxisParam(t,s),o=a,i=T.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=T.getInnerMostAxes(o.length,r),l=go({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 mC;function Zde(e){mC=e.wasm.cwrap(Rc,null,["number, number, number"])}function Yde(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}=bi(o,r,t);if(h){let A=t.dataIdMap.get(c.dataId).id;u=c,l=A}let 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ope(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=T.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:'${c.dataFormat}'. 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gpe(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s,i=a.reduce((y,x)=>y*x),l=T.getReshaped(r.shape,a,i),u=T.getPermuted(l.length,a.length),c=T.getReshapedPermuted(r.shape,a,i),p=T.getSliceBeginCoords(o,a.length),d=T.getSliceSize(c,o,a.length),h=vs({inputs:{x:r},backend:n,attrs:{shape:l}}),f=go({inputs:{x:h},backend:n,attrs:{perm:u}}),m=vs({inputs:{x:f},backend:n,attrs:{shape:c}}),g=yl({inputs:{x:m},backend:n,attrs:{begin:p,size:d}});return n.disposeData(h.dataId),n.disposeData(f.dataId),n.disposeData(h.dataId),g}var ype={kernelName:vl,backendName:"wasm",kernelFunc:gpe};function vd(e){let{inputs:{x:t},attrs:{dtype:n},backend:s}=e,r=s.makeOutput(t.shape,n),a=s.typedArrayFromHeap(t);return s.typedArrayFromHeap(r).set(a),r}var Ape={kernelName:ko,backendName:"wasm",kernelFunc:vd},xpe=_n(So),bC;function bpe(e){bC=e.wasm.cwrap($a,null,["number","number","number","number"])}function 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x.stringBytes=T.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 kpe={kernelName:wl,backendName:"wasm",kernelFunc:vC},wC;function Spe(e){wC=e.wasm.cwrap(Io,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Ipe(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=T.convertConv2DDataFormat(d),f=T.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,C=f.strideHeight,E=f.strideWidth,_=f.inChannels,$=f.outChannels,R=f.padInfo.type==="SAME"?1:0;if(f.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${f.dataFormat}'. 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Npe(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=T.convertConv2DDataFormat(l),h=T.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:C,strideWidth:E}=h,_=m-1-h.padInfo.top,$=g-1-h.padInfo.left,R=h.dataFormat==="channelsLast",P=v.computeStrides(h.inShape),S=v.computeStrides(r.shape),[M,L,U]=v.computeStrides(a.shape),K=P[0],q=R?P[1]:P[2],Z=R?P[2]:1,J=R?1:P[1],te=S[0],le=R?S[1]:S[2],ae=R?S[2]:1,pe=R?1:S[1],ce=t.makeOutput(h.inShape,"float32"),xe=t.dataIdMap.get(ce.dataId).id,ie=t.dataIdMap.get(r.dataId).id,_e=t.dataIdMap.get(a.dataId).id;return kC(ie,_e,f,m,g,x,A,y,w,k,b,C,E,_,$,M,L,U,K,q,Z,J,te,le,ae,pe,xe),ce}var Epe={kernelName:Co,backendName:"wasm",setupFunc:Tpe,kernelFunc:Npe},Rpe=_n(To),_pe=_n(No),Ty;(function(e){e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest"})(Ty||(Ty={}));var SC;function Dpe(e){SC=e.wasm.cwrap(Sl,null,["number","number","number","number","array","number","number","number","number","number"])}function $pe(e){let{backend:t,inputs:n,attrs:s}=e,{method:r,extrapolationValue:a,cropSize:o}=s,{image:i,boxes:l,boxInd:u}=n,c=l.shape[0],[p,d]=o,h=[c,p,d,i.shape[3]],f=t.dataIdMap.get(i.dataId),m;i.dtype!=="float32"&&(m=vd({backend:t,inputs:{x:i},attrs:{dtype:"float32"}}),f=t.dataIdMap.get(m.dataId));let g=f.id,y=t.dataIdMap.get(l.dataId).id,x=t.dataIdMap.get(u.dataId).id,A=t.makeOutput(h,"float32"),b=t.dataIdMap.get(A.dataId).id,w=new Uint8Array(new Int32Array(i.shape).buffer);return SC(g,y,x,c,w,p,d,Ty[r],a,b),m!=null&&t.disposeData(m.dataId),A}var Ppe={kernelName:Sl,backendName:"wasm",setupFunc:Dpe,kernelFunc:$pe},IC;function Fpe(e){IC=e.wasm.cwrap(kl,null,["number","number","number","number","number","number"])}function Ope(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=T.getAxesPermutation([a],l),c=r;u!==null&&(c=go({inputs:{x:r},attrs:{perm:u},backend:n}));let p=T.getInnerMostAxes(1,l)[0];T.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;IC(f,o?1:0,i?1:0,h,m,Kt[r.dtype]);let g=d;if(u!==null){let y=T.getUndoAxesPermutation(u);g=go({inputs:{x:d},attrs:{perm:y},backend:n}),n.disposeData(c.dataId),n.disposeData(d.dataId)}return g}var Mpe={kernelName:kl,backendName:"wasm",setupFunc:Fpe,kernelFunc:Ope},CC;function zpe(e){CC=e.wasm.cwrap(Eo,null,["number","number","number","number","number","number"])}function Lpe(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=T.getAxesPermutation([a],l),c=r;u!==null&&(c=go({inputs:{x:r},attrs:{perm:u},backend:n}));let p=T.getInnerMostAxes(1,l)[0];T.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;CC(f,o?1:0,i?1:0,h,m,Kt[r.dtype]);let g=d;if(u!==null){let y=T.getUndoAxesPermutation(u);g=go({inputs:{x:d},attrs:{perm:y},backend:n}),n.disposeData(c.dataId),n.disposeData(d.dataId)}return g}var Bpe={kernelName:Eo,backendName:"wasm",setupFunc:zpe,kernelFunc:Lpe},TC;function Wpe(e){TC=e.wasm.cwrap(Il,null,["number","number","number","array","number","array","array","number","number"])}function Vpe(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 TC(y,a,o==="NHWC"?1:0,x,r.shape.length-1,A,b,f.length,w),m}var Upe={kernelName:Il,backendName:"wasm",setupFunc:Wpe,kernelFunc:Vpe},NC;function Gpe(e){NC=e.wasm.cwrap(Ro,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Hpe(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=T.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,C=h.strideWidth,E=h.inChannels,_=h.outChannels,$=h.padInfo.type==="SAME"?1:0;if(h.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${h.dataFormat}'. 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b=T.expandShapeToKeepDim(A.shape,d);A.shape=b}return u.dtype!=="float32"&&t.disposeData(x.dataId),A}var Khe={kernelName:Go,backendName:"wasm",setupFunc:qhe,kernelFunc:Xhe},BC;function Zhe(e){BC=e.wasm.cwrap(Ho,null,["number","number","number","number"])}function Yhe(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,i=t.dataIdMap.get(o.dataId).id,l=i,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=bi(o,r,t);if(h){let A=t.dataIdMap.get(c.dataId).id;A!==i&&(u=c,l=A)}let f=u.shape.length;T.assertAxesAreInnerMostDims("min",p,f);let[m,g]=T.computeOutAndReduceShapes(u.shape,p),y=v.sizeFromShape(g),x=t.makeOutput(m,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;BC(l,Kt[o.dtype],y,A)}if(h&&t.disposeData(c.dataId),a){let A=T.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var Jhe={kernelName:Ho,backendName:"wasm",setupFunc:Zhe,kernelFunc:Yhe},Qhe=!1,efe=Wn(jo,Qhe),Ey;(function(e){e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric"})(Ey||(Ey={}));var WC;function tfe(e){WC=e.wasm.cwrap(qo,null,["number","array","number","number","array","array","number","number"])}function nfe(e){let{inputs:{x:t},backend:n,attrs:{paddings:s,mode:r}}=e,a=s.map((f,m)=>f[0]+t.shape[m]+f[1]),o=n.dataIdMap.get(t.dataId).id,i=n.makeOutput(a,t.dtype),l=n.dataIdMap.get(i.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),c=s.map(f=>f[0]),p=s.map(f=>f[1]),d=new Uint8Array(new Int32Array(c).buffer),h=new Uint8Array(new Int32Array(p).buffer);return WC(o,u,t.shape.length,Kt[t.dtype],d,h,Ey[r],l),i}var sfe={kernelName:qo,backendName:"wasm",kernelFunc:nfe,setupFunc:tfe},rfe=!0,afe=Wn(Xo,rfe),ofe=_n(zl);function Ab(e,t){let n=new Int32Array(e.wasm.HEAPU8.buffer,t,4),s=n[0],r=n[1],a=n[2],o=n[3];return e.wasm._free(t),{pSelectedIndices:s,selectedSize:r,pSelectedScores:a,pValidOutputs:o}}var VC;function ife(e){VC=e.wasm.cwrap(Bl,"number",["number","number","number","number","number"])}function lfe(e){let{backend:t,inputs:n,attrs:s}=e,{iouThreshold:r,maxOutputSize:a,scoreThreshold:o}=s,{boxes:i,scores:l}=n,u=t.dataIdMap.get(i.dataId).id,c=t.dataIdMap.get(l.dataId).id,p=VC(u,c,a,r,o),{pSelectedIndices:d,selectedSize:h,pSelectedScores:f,pValidOutputs:m}=Ab(t,p);return t.wasm._free(f),t.wasm._free(m),t.makeOutput([h],"int32",d)}var ufe={kernelName:Bl,backendName:"wasm",setupFunc:ife,kernelFunc:lfe},UC;function cfe(e){UC=e.wasm.cwrap(Gc,"number",["number","number","number","number","number","bool"])}function dfe(e){let{backend:t,inputs:n,attrs:s}=e,{iouThreshold:r,maxOutputSize:a,scoreThreshold:o,padToMaxOutputSize:i}=s,{boxes:l,scores:u}=n,c=t.dataIdMap.get(l.dataId).id,p=t.dataIdMap.get(u.dataId).id,d=UC(c,p,a,r,o,i),{pSelectedIndices:h,selectedSize:f,pSelectedScores:m,pValidOutputs:g}=Ab(t,d);t.wasm._free(m);let y=t.makeOutput([f],"int32",h),x=t.makeOutput([],"int32",g);return[y,x]}var pfe={kernelName:Gc,backendName:"wasm",setupFunc:cfe,kernelFunc:dfe},GC;function hfe(e){GC=e.wasm.cwrap(Wl,"number",["number","number","number","number","number","number"])}function ffe(e){let{backend:t,inputs:n,attrs:s}=e,{iouThreshold:r,maxOutputSize:a,scoreThreshold:o,softNmsSigma:i}=s,{boxes:l,scores:u}=n,c=t.dataIdMap.get(l.dataId).id,p=t.dataIdMap.get(u.dataId).id,d=GC(c,p,a,r,o,i),{pSelectedIndices:h,selectedSize:f,pSelectedScores:m,pValidOutputs:g}=Ab(t,d);t.wasm._free(g);let y=t.makeOutput([f],"int32",h),x=t.makeOutput([f],"float32",m);return[y,x]}var mfe={kernelName:Wl,backendName:"wasm",setupFunc:hfe,kernelFunc:ffe},gfe=!1,yfe=Wn(Ll,gfe,"bool"),HC;function Afe(e){HC=e.wasm.cwrap(Ul,null,["number","number","number","number","number"])}function xfe(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r}=t,{dtype:a,depth:o,onValue:i,offValue:l}=s,u=n.makeOutput([...r.shape,o],a),c=n.dataIdMap.get(u.dataId).id,d=n.dataIdMap.get(r.dataId).id;return HC(d,o,i,l,c),u}var bfe={kernelName:Ul,backendName:"wasm",setupFunc:Afe,kernelFunc:xfe};function vfe(e){let{inputs:{x:t},backend:n}=e,s=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(s).fill(1),s}var wfe={kernelName:Vl,backendName:"wasm",kernelFunc:vfe};function kfe(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return Ny({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 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Int32Array(v.computeStrides(g)).buffer),A=t.makeOutput(g,r.dtype),b=t.dataIdMap.get(A.dataId).id,k=t.dataIdMap.get(r.dataId).id,E=t.dataIdMap.get(a.dataId).id,_=o==="nearest"?1:2,$;switch(i){case"constant":$=1;break;case"reflect":$=2;break;case"wrap":$=3;break;case"nearest":$=4;break;default:$=1;break}return fT(k,E,a.shape[0]>1,c,f,m,h,d,p,y,r.shape.length-1,x,g.length-1,_,$,l,b),A}var a0e={kernelName:ru,backendName:"wasm",setupFunc:s0e,kernelFunc:r0e};function o0e(e){let{inputs:t,backend:n,attrs:s}=e,{value:r}=t,{axis:a}=s;a<0&&(a+=r.shape.length);let o=r.shape[a],i=r.shape.length,l=new Array(i-1),u=0;for(let h=0;h<i;h++)h!==a&&(l[u++]=r.shape[h]);let c=new Array(o),p=new Array(i).fill(0),d=r.shape.slice();d[a]=1;for(let h=0;h<c.length;h++)p[a]=h,c[h]=yl({inputs:{x:r},attrs:{begin:p,size:d},backend:n});return c.map(({dataId:h,dtype:f})=>({dataId:h,dtype:f,shape:l}))}var i0e={kernelName:au,backendName:"wasm",kernelFunc:o0e};function l0e(e){let{inputs:{x:t},backend:n}=e,s=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(s).fill(0),s}var u0e={kernelName:ou,backendName:"wasm",kernelFunc:l0e},c0e=[zde,Lde,Wde,Gde,Jde,tpe,rpe,ipe,dpe,ype,Ape,xpe,wpe,kpe,Cpe,Epe,Rpe,_pe,Ppe,Mpe,Bpe,Upe,jpe,qpe,Kpe,Zpe,Ype,Jpe,the,nhe,rhe,ihe,che,hhe,ghe,xhe,vhe,khe,Hde,Che,Nhe,Rhe,_he,$he,Phe,Ohe,zhe,Whe,Uhe,jhe,Khe,Jhe,efe,sfe,afe,ofe,ufe,pfe,mfe,yfe,bfe,wfe,Sfe,qC,Nfe,_fe,Pfe,Ofe,zfe,Lfe,Bfe,lpe,Ufe,jfe,Kfe,Jfe,Qfe,eme,sme,ome,ume,cme,mpe,hme,mme,Ame,vme,kme,Ime,Tme,Nme,Eme,_me,Pme,Mme,Lme,Wme,Ume,Hme,Xme,Kme,Zme,Qme,n0e,a0e,Kde,i0e,u0e];for(let e of c0e)rr(e);var Ry=H();Ry.registerFlag("WASM_HAS_SIMD_SUPPORT",async()=>WebAssembly.validate(new Uint8Array([0,97,115,109,1,0,0,0,1,4,1,96,0,0,3,2,1,0,10,9,1,7,0,65,0,253,15,26,11])));Ry.registerFlag("WASM_HAS_MULTITHREAD_SUPPORT",async()=>{if(Ry.get("IS_NODE"))return!1;try{return new MessageChannel().port1.postMessage(new SharedArrayBuffer(1)),WebAssembly.validate(new Uint8Array([0,97,115,109,1,0,0,0,1,4,1,96,0,0,3,2,1,0,5,4,1,3,1,1,10,11,1,9,0,65,0,254,16,2,0,26,11]))}catch(e){return!1}});var r6=yo(tD()),d0e=yo(nD()),a6=yo(sD()),o6=r6.default||r6,p0e=a6.default||a6,mT=class extends Cc{constructor(e){super(),this.wasm=e,this.dataIdNextNumber=1,this.wasm.tfjs.initWithThreadsCount(gT),_y=this.wasm.tfjs.getThreadsCount(),this.dataIdMap=new Gp(this,Qt())}write(e,t,n){let s={id:this.dataIdNextNumber++};return this.move(s,e,t,n,1),s}numDataIds(){return this.dataIdMap.numDataIds()}async time(e){let t=v.now();return e(),{kernelMs:v.now()-t}}move(e,t,n,s,r){let a=this.dataIdNextNumber++;if(s==="string"){let u=t;this.dataIdMap.set(e,{id:a,stringBytes:u,shape:n,dtype:s,memoryOffset:null,refCount:r});return}let o=v.sizeFromShape(n),i=o*v.bytesPerElement(s),l=this.wasm._malloc(i);this.dataIdMap.set(e,{id:a,memoryOffset:l,shape:n,dtype:s,refCount:r}),this.wasm.tfjs.registerTensor(a,o,l),t!=null&&this.wasm.HEAPU8.set(new Uint8Array(t.buffer,t.byteOffset,i),l)}async read(e){return this.readSync(e)}readSync(e,t,n){let{memoryOffset:s,dtype:r,shape:a,stringBytes:o}=this.dataIdMap.get(e);if(r==="string")return(t==null||t===0)&&(n==null||n>=o.length)?o:o.slice(t,n);t=t||0,n=n||v.sizeFromShape(a);let i=v.bytesPerElement(r),l=this.wasm.HEAPU8.slice(s+t*i,s+n*i);return m0e(l.buffer,r)}disposeData(e,t=!1){if(this.dataIdMap.has(e)){let n=this.dataIdMap.get(e);if(n.refCount--,!t&&n.refCount>0)return!1;this.wasm._free(n.memoryOffset),this.wasm.tfjs.disposeData(n.id),this.dataIdMap.delete(e)}return!0}refCount(e){return this.dataIdMap.has(e)?this.dataIdMap.get(e).refCount:0}incRef(e){let t=this.dataIdMap.get(e);t!=null&&t.refCount++}floatPrecision(){return 32}getMemoryOffset(e){return this.dataIdMap.get(e).memoryOffset}dispose(){this.wasm.tfjs.dispose(),"PThread"in this.wasm&&this.wasm.PThread.terminateAllThreads(),this.wasm=null}memory(){return{unreliable:!1}}makeOutput(e,t,n){let s;if(n==null)s=this.write(null,e,t);else{let r=this.dataIdNextNumber++;s={id:r},this.dataIdMap.set(s,{id:r,memoryOffset:n,shape:e,dtype:t,refCount:1});let a=v.sizeFromShape(e);this.wasm.tfjs.registerTensor(r,a,n)}return{dataId:s,shape:e,dtype:t}}typedArrayFromHeap({shape:e,dtype:t,dataId:n}){let s=this.wasm.HEAPU8.buffer,{memoryOffset:r}=this.dataIdMap.get(n),a=v.sizeFromShape(e);switch(t){case"float32":return new Float32Array(s,r,a);case"int32":return new Int32Array(s,r,a);case"bool":return new Uint8Array(s,r,a);default:throw new Error(`Unknown dtype ${t}`)}}};function h0e(e){return(t,n)=>(v.fetch(e,{credentials:"same-origin"}).then(s=>{s.ok||t.env.a(`failed to load wasm binary file at '${e}'`),s.arrayBuffer().then(r=>{WebAssembly.instantiate(r,t).then(a=>{n(a.instance,a.module)})})}),{})}function i6(e,t,n){if(Zm!=null)return Zm;let s="tfjs-backend-wasm.wasm";return e&&t?s="tfjs-backend-wasm-threaded-simd.wasm":e&&(s="tfjs-backend-wasm-simd.wasm"),vp!=null&&vp[s]!=null?vp[s]:n+s}async function f0e(){let[e,t]=await Promise.all([H().getAsync("WASM_HAS_SIMD_SUPPORT"),H().getAsync("WASM_HAS_MULTITHREAD_SUPPORT")]);return new Promise((n,s)=>{let r={};r.locateFile=(i,l)=>{if(i.endsWith(".worker.js")){let u=d0e.wasmWorkerContents.replace(/\n/g,"\\n"),c=new Blob([u],{type:"application/javascript"});return URL.createObjectURL(c)}return i.endsWith(".wasm")?i6(e,t,yp!=null?yp:l):l+i},xb&&(r.instantiateWasm=h0e(i6(e,t,yp!=null?yp:"")));let a=!1;r.onAbort=()=>{if(a||wp)return;wp=!0,s({message:"Make sure the server can serve the `.wasm` file relative to the bundled js file. For more details see https://github.com/tensorflow/tfjs/blob/master/tfjs-backend-wasm/README.md#using-bundlers"})};let o;t&&e&&Zm==null?(r.mainScriptUrlOrBlob=new Blob(["var WasmBackendModuleThreadedSimd = "+o6.toString()],{type:"text/javascript"}),o=o6(r)):o=p0e(r),o.then(i=>{a=!0,wp=!1;let l=null;i.tfjs={init:i.cwrap("init",null,[]),initWithThreadsCount:i.cwrap("init_with_threads_count",null,["number"]),getThreadsCount:i.cwrap("get_threads_count","number",[]),registerTensor:i.cwrap("register_tensor",null,["number","number","number"]),disposeData:i.cwrap("dispose_data",l,["number"]),dispose:i.cwrap("dispose",l,[])},n({wasm:i})}).catch(s)})}function m0e(e,t){switch(t){case"float32":return new Float32Array(e);case"int32":return new Int32Array(e);case"bool":return new Uint8Array(e);default:throw new Error(`Unknown dtype ${t}`)}}var g0e=["tfjs-backend-wasm.wasm","tfjs-backend-wasm-simd.wasm","tfjs-backend-wasm-threaded-simd.wasm"],Zm=null,yp=null,vp={},wp=!1,xb=!1;function y0e(e,t=!1){if(Qy("setWasmPath has been deprecated in favor of setWasmPaths and will be removed in a future release."),wp)throw new Error("The WASM backend was already initialized. Make sure you call `setWasmPath()` before you call `tf.setBackend()` or `tf.ready()`");Zm=e,xb=t}function L2(e,t=!1){if(wp)throw new Error("The WASM backend was already initialized. Make sure you call `setWasmPaths()` before you call `tf.setBackend()` or `tf.ready()`");if(typeof e=="string")yp=e;else{vp=e;let n=g0e.filter(s=>vp[s]==null);if(n.length>0)throw new Error(`There were no entries found for the following binaries: ${n.join(",")}. Please either call setWasmPaths with a map providing a path for each binary, or with a string indicating the directory where all the binaries can be found.`)}xb=t}var gT=-1,_y=-1;function A0e(e){gT=e}function x0e(){if(_y===-1)throw new Error("WASM backend not initialized.");return _y}var b0e="3.20.0",v0e=2;lu("wasm",async()=>{let{wasm:e}=await f0e();return new mT(e)},v0e);var vi=H();vi.registerFlag("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE",()=>15);vi.registerFlag("WEBGPU_CPU_FORWARD",()=>!0);vi.registerFlag("WEBGPU_MATMUL_PROGRAM_TYPE",()=>-1);vi.registerFlag("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE",()=>!1);vi.registerFlag("WEBGPU_USE_LOW_POWER_GPU",()=>!1);vi.registerFlag("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e3);vi.registerFlag("WEBGPU_USE_PROFILE_TOOL",()=>!1);vi.registerFlag("WEBGPU_IMPORT_EXTERNAL_TEXTURE",()=>!0);var w0e=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=l6(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=l6(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 l6(e,t){return`${e}_${t}`}var k0e=class{constructor(e){this.device=e,this.numUsedTextures=0,this.numFreeTextures=0,this.freeTextures=new Map,this.usedTextures=new Map,this.numBytesUsed=0,this.numBytesAllocated=0}acquireTexture(e,t,n,s){let r=c6(n),a=e*t*r,o=u6(e,t,n,s);if(this.freeTextures.has(o)||this.freeTextures.set(o,[]),this.usedTextures.has(o)||this.usedTextures.set(o,[]),this.numBytesUsed+=a,this.numUsedTextures++,this.freeTextures.get(o).length>0){this.numFreeTextures--;let l=this.freeTextures.get(o).shift();return this.usedTextures.get(o).push(l),l}this.numBytesAllocated+=a;let i=this.device.createTexture({size:[e,t],format:n,usage:s});return this.usedTextures.get(o).push(i),i}releaseTexture(e,t,n,s,r){if(this.freeTextures.size===0)return;let a=u6(t,n,s,r);this.freeTextures.has(a)||this.freeTextures.set(a,[]),this.freeTextures.get(a).push(e),this.numFreeTextures++,this.numUsedTextures--;let o=this.usedTextures.get(a),i=o.indexOf(e);if(i<0)throw new Error("Cannot release a texture that was never provided by this texture manager");o.splice(i,1);let l=c6(s),u=t*n*l;this.numBytesUsed-=u}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){this.freeTextures.forEach((e,t)=>{e.forEach(n=>{n.destroy()})}),this.usedTextures.forEach((e,t)=>{e.forEach(n=>{n.destroy()})}),this.freeTextures=new Map,this.usedTextures=new Map,this.numUsedTextures=0,this.numFreeTextures=0,this.numBytesUsed=0,this.numBytesAllocated=0}};function u6(e,t,n,s){return`${e}_${t}_${n}_${s}`}function c6(e){if(e==="rgba8unorm")return 16;throw new Error(`${e} is not supported!`)}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 I0e=(e,t,n,s)=>{let r={dtype:s.dtype,shape:s.shape},a=C0e(n,r,t),o=e.createShaderModule({code:a,label:t.constructor.name});return e.createComputePipeline({compute:{module:o,entryPoint:"_start"},label:t.constructor.name,layout:"auto"})};function Mn(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 Ca(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 nt(...e){let t;switch(e.length){case 0:t=`
        ${Vp()}
        fn _start(@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;
          main();
        }

        fn main()
      `;break;case 1:t=`
        ${Vp()}
        fn _start(@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;
          main(getGlobalIndex());
        }

        fn main(${e[0]} : i32)
      `;break;default:throw Error("Unreachable")}return t}function Vp(){return`
  @compute @workgroup_size(workGroupSizeX, workGroupSizeY, workGroupSizeZ)
`}function C0e(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 {
        ${yT(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<${kp(t.dtype,n.isVec4)}>;
        @group(0) @binding(2) var<uniform> uniforms: Uniform;
      `),[d6,s.join(`
`),p6(t.shape),n.getUserCode()].join(`
`);let r="struct Uniforms { NAN : f32, ";n.variableNames.forEach((d,h)=>{let f=Mn(e[h].shape.length);r+=`${d.charAt(0).toLowerCase()+d.slice(1)}Shape : ${f}, `}),r+=`outShape : ${Mn(t.shape.length)}, `;let o=t.shape.length-1;r+=`
         outShapeStrides: ${Mn(o)}, `,n.size&&(r+="size : i32, "),n.uniforms&&(r+=n.uniforms),r+="};",r=P0e(r),s.push(r),n.atomic?s.push(`
      @group(0) @binding(0) var<storage, read_write> result: array<atomic<i32>>;
    `):s.push(`
      @group(0) @binding(0) var<storage, read_write> result: array<${kp(t.dtype,n.isVec4)}>;
    `),n.variableNames.forEach((d,h)=>{s.push(`
      @group(0) @binding(${1+h}) var<storage, read> ${d}: array<${n.variableTypes?n.variableTypes[h]:kp(e[h].dtype,n.isVec4)}>;
        `)}),r!==""&&s.push(`
      @group(0) @binding(${1+n.variableNames.length}) var<uniform> uniforms: Uniforms;
      `);let l=_0e(t.shape,n.dispatchLayout),u=[d6,s.join(`
`),p6(t.shape),l,D0e(t.shape.length)];n.atomic||u.push($0e(t.shape,t.dtype,n.isVec4));let c=e.map((d,h)=>R0e(d,t.shape,n.variableTypes?n.variableTypes[h]==="vec4<f32>":n.isVec4,n.dispatchLayout.x.length===t.shape.length)).join(`
`);return u.push(c),u.push(n.getUserCode()),u.join(`
`)}function T0e(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=>T.getBroadcastDims(c.shape,s.shape)),i=n.map(c=>v.arraysEqual(c.shape,s.shape)).join("_"),l=o.map(c=>c.join("_")).join(";"),u=yT(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 d6=`
  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 modulo: i32 = a % b;
    if (sign < 0. && modulo != 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 p6(e){let t=e.length;if(t<=1)return"fn getCoordsFromIndex(index : i32) -> i32 { return index; }";let n=v.computeStrides(e),s=Mn(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 ${r[i]} = index2 / uniforms.outShapeStrides.${Ca(i)}`,u=i===n.length-1?`let ${r[i+1]} = index2 - ${r[i]} * uniforms.outShapeStrides.${Ca(i)}`:`index2 = index2 - ${r[i]} * uniforms.outShapeStrides.${Ca(i)}`;return`${l}; ${u};`}).join(""),`
    fn getCoordsFromIndex(index : i32) -> ${s} {
      ${a}
      return ${s}(${r.join(",")});
    }
  `}function N0e(e,t){let n=e.name,s=e.shape.length,r=Mn(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 E0e(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=Mn(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=T.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.${Ca(g+p)} = 0;`).join(`
`);let h="";if(l<2&&i>0)h="coords";else if(l>1){let g=Mn(i),y=e.shape.map((x,A)=>`coords.${Ca(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 R0e(e,t,n,s){let r=N0e(e,n);return e.shape.length<=t.length&&(r+=E0e(e,t,n,s)),r}function _0e(e,t){let{x:n,y:s=[],z:r=[]}=t,a=e.length;if(n.length===a)return`fn getOutputCoords() -> ${Mn(a)}{
    let globalIndex = getGlobalIndex();
    return getCoordsFromIndex(globalIndex);
  }
  `;let o="",i=[n,s,r],l=0;for(let d=0;d<i.length;d++){let h=i[d];if(h.length!==0)if(l+=h.length,h.length===1)o+=`let d${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=Mn(l),p=`fn getOutputCoords() -> ${c} {
  ${o}
`;return u.length===0?p+=`return ${c}(0); }`:p+=`return ${c}(${u.join(",")}); }`,p}function D0e(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 yT(e){return e.dispatch[1]===1&&e.dispatch[2]===1}function kp(e,t){return e==="float32"?t?"vec4<f32>":"f32":e==="int32"||e==="bool"?t?"vec4<i32>":"i32":e}function $0e(e,t,n){let s=e.length,r=kp(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] = ${r}(value);
    }`,s>=2){let o=["d0","d1","d2","d3","d4","d5"].slice(0,s),i=Mn(s);n?a+=`
      fn setOutputAtCoords(${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}(${o.join(", ")}));
        setOutputAtIndexI32(flatIndex, value);
      }
    `}return a}function P0e(e){let t=/(\w+)\s*:\s*vec(5|6)/g;e=e.replace(t,s=>"@align(16) "+s);let n=/vec(5|6)\s*,\s*(\w+)/g;return e=e.replace(n,(s,r,a)=>`vec${r}, @align(16) ${a}`),e}var AT={};qe(AT,{ArrayBufferToTypedArray:()=>vT,GPUBytesPerElement:()=>bT,MatMulProgramType:()=>$r,computeDispatch:()=>je,computeWorkGroupInfoForMatMul:()=>xT,computeWorkGroupSizeForConv2d:()=>bb,computeWorkPerThreadForConv2d:()=>vb,flatDispatchLayout:()=>lt,isWebGPUSupported:()=>wb,tilesFitEvenlyIntoShape:()=>F0e});var al=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 je(e,t,n=[1,1,1],s=[1,1,1]){let[r,a,o]=[Math.ceil(al(e.x.map(i=>t[i]))/(n[0]*s[0])),e.y?Math.ceil(al(e.y.map(i=>t[i]))/(n[1]*s[1])):1,e.z?Math.ceil(al(e.z.map(i=>t[i]))/(n[2]*s[2])):1];return[r,a,o]}function xT(e,t,n,s=!1){let r=[8,8,1],a=[4,4,1];return s||(e<=8&&(a[1]=1),t<=16&&n<=16&&(r[0]=4)),{workGroupSize:r,elementsPerThread:a}}function bb(e,t,n=!1){if(n)return[8,8,1];let s=al(e.x.map(a=>t[a])),r=al(e.y.map(a=>t[a]));return s<=4?[4,16,1]:r<=4?[16,4,1]:[16,16,1]}function vb(e,t,n=!1){if(n)return[4,4,1];let s=al(e.x.map(a=>t[a])),r=al(e.y.map(a=>t[a]));return s<=4?[1,2,1]:r<=4?[2,1,1]:[2,2,1]}function lt(e){return{x:e.map((t,n)=>n)}}function bT(e){if(e==="float32"||e==="int32"||e==="bool"||e==="string")return 4;if(e==="complex64")return 8;throw new Error(`Unknown dtype ${e}`)}function vT(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 wb(){return(typeof window!="undefined"||typeof WorkerGlobalScope!="undefined")&&!!navigator.gpu}var $r;(function(e){e[e.MatMulReduceProgram=0]="MatMulReduceProgram",e[e.MatMulSplitKProgram=1]="MatMulSplitKProgram",e[e.MatMulSmallOutputSizeProgram=2]="MatMulSmallOutputSizeProgram",e[e.MatMulPackedProgram=3]="MatMulPackedProgram",e[e.MatMulMax=4]="MatMulMax"})($r||($r={}));var O0e=H().getNumber("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD"),M0e=(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]},B2=class extends Cc{constructor(e){if(super(),this.commandQueueOwnedIds=new WeakSet,this.dispatchNumberInEncoder=0,this.disposed=!1,this.downloadWaitMs=0,this.tensorDataPendingDisposal=[],this.stagingPendingDisposal=[],this.uniformPendingDisposal=[],this.uploadWaitMs=0,!wb())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=e.features.has("timestamp-query"),this.bufferManager=new w0e(this.device),this.textureManager=new k0e(this.device),this.tensorMap=new Gp(this,Qt()),this.supportTimeQuery&&(this.querySet=this.device.createQuerySet({type:"timestamp",count:2})),H().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 B2.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),H().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=T.mergeRealAndImagArrays(a,o)}else{let r=t.resourceInfo,a=await this.getBufferData(r.buffer,r.size);s=vT(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=Qt().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 Ue(e.shape,e.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return Ue(e.shape,e.dtype,t)}async time(e){this.supportTimeQuery||console.warn("This device doesn't support timestamp-query extension. Start Chrome browser with flag --disable-dawn-features=disallow_unsafe_apis then try again. Otherwise, zero will be shown for the kernel time when profiling mode is enabled. Using performance.now is not workable for webgpu since it doesn't support synchronous data read from GPU.");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=bT(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=M0e(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=T0e(e,o,i,r),u;l in this.pipelineCache?u=this.pipelineCache[l]:(u=I0e(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),H().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=O0e){return H().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)}};B2.nextDataId=0;wb()&&lu("webgpu",async()=>{H().set("CHECK_COMPUTATION_FOR_ERRORS",!1);let e={powerPreference:H().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"]);let a=await t.requestDevice(s);return new B2(a)},3);var Ye;(function(e){e[e.MUL=0]="MUL",e[e.ADD=1]="ADD",e[e.ATAN2=2]="ATAN2",e[e.SUB=3]="SUB",e[e.DIV=4]="DIV",e[e.EQUAL=5]="EQUAL",e[e.GREATER=6]="GREATER",e[e.GREATER_EQUAL=7]="GREATER_EQUAL",e[e.LESS=8]="LESS",e[e.LESS_EQUAL=9]="LESS_EQUAL",e[e.LOGICAL_AND=10]="LOGICAL_AND",e[e.NOT_EQUAL=11]="NOT_EQUAL",e[e.SQUARED_DIFFERENCE=12]="SQUARED_DIFFERENCE",e[e.INT_DIV=13]="INT_DIV",e[e.POW=14]="POW",e[e.PRELU=15]="PRELU",e[e.MAX=16]="MAX",e[e.MIN=17]="MIN",e[e.COMPLEX_MULTIPLY_REAL=18]="COMPLEX_MULTIPLY_REAL",e[e.COMPLEX_MULTIPLY_IMAG=19]="COMPLEX_MULTIPLY_IMAG"})(Ye||(Ye={}));var z0e=`
  if (isnan(a)) { return a; }
  if (isnan(b)) { return b; }
  `,wT=`
  if (isNaN.r) {
    resultTemp.r = valueForNaN;
  }
  if (isNaN.g) {
    resultTemp.g = valueForNaN;
  }
  if (isNaN.b) {
    resultTemp.b = valueForNaN;
  }
  if (isNaN.a) {
    resultTemp.a = valueForNaN;
  }
  `,kT=`
  let isNaN = isnanVec4(a) | isnanVec4(b);
  ${wT}
  `,L0e="return a + b;",B0e="return areal * breal - aimag * bimag;",W0e="return areal * bimag + aimag * breal;",V0e="return a / b;",U0e="return a * b;",G0e="return (a - b) * (a - b);",H0e="return a - b;",j0e="return f32(a == b);",q0e="return vec4<f32>(a == b);",X0e="return f32(a > b);",K0e="return vec4<f32>(a > b);",Z0e="return f32(a >= b);",Y0e="return vec4<f32>(a >= b);",J0e="return f32(a < b);",Q0e="return vec4<f32>(a < b);",e2e="return f32(a <= b);",t2e="return vec4<f32>(a <= b);",n2e="return f32(f32(a) >= 1.0 && f32(b) >= 1.0);",s2e=`return (vec4<f32>(a >= vec4<f32>(1.0)) *
  vec4<f32>(b >= vec4<f32>(1.0)));`,r2e=`
  let s = sign(a) * sign(b);
  let ia = i32(round(a));
  let ib = i32(round(b));
  return f32(idiv(ia, ib, s));
  `,a2e=`
  let ia = vec4<i32>(round(a));
  let ib = vec4<i32>(round(b));
  let cond = ib != vec4<i32>(0);
  var resultTemp = vec4<i32>(0);
  let s = sign(a) * sign(b);

  // Windows (D3D) wants guaranteed non-zero int division at compile-time.
  if (cond[0]) {
    resultTemp[0] = idiv(ia[0], ib[0], s[0]);
  }
  if (cond[1]) {
    resultTemp[1] = idiv(ia[1], ib[1], s[1]);
  }
  if (cond[2]) {
    resultTemp[2] = idiv(ia[2], ib[2], s[2]);
  }
  if (cond[3]) {
    resultTemp[3] = idiv(ia[3], ib[3], s[3]);
  }
  return vec4<f32>(resultTemp);
  `,o2e=`
  if (isnan(a) || isnan(b)) {
    return 1.0;
  }
  return f32(a != b);
`,i2e=`
  var resultTemp = vec4<f32>(a != b);
  let valueForNaN = 1.0;
  ${kT}

  return resultTemp;
`,l2e=`
  if(a < 0.0 && floor(b) < b) {
    return uniforms.NAN;
  }
  if (b == 0.0) {
    return 1.0;
  }
  if (round(abs(b) % 2.0) != 1.0) {
    return pow(abs(a), b);
  }
  return sign(a) * pow(abs(a), b);
  `,u2e=`
  let isModRound1Bool = vec4<i32>(round(abs(b) % vec4<f32>(2.0))) == vec4<i32>(1);
  let isModRound1 = vec4<f32>(isModRound1Bool);
  let multiplier = sign(a) * isModRound1 + (vec4<f32>(1.0) - isModRound1);
  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;
  let valueForNaN = uniforms.NAN;
  ${wT}
  return resultTemp;
  `,c2e="if (a < 0.0) { return b * a; }  return a;",d2e=`
  let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));
  return (aLessThanZero * (b * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);
  `;function R3(e,t,n="uniforms.NAN"){let s=t?kT:z0e;return t?`
    let valueForNaN = ${n};
    var resultTemp = vec4<f32>(${e}(a, b));
    `+s+`
    return resultTemp;
  `:s+`
    return ${e}(a, b);
  `}function Ym(e,t){switch(e){case Ye.MUL:return U0e;case Ye.ADD:return L0e;case Ye.ATAN2:return R3("atan2",t);case Ye.SUB:return H0e;case Ye.DIV:return V0e;case Ye.EQUAL:return t?q0e:j0e;case Ye.GREATER:return t?K0e:X0e;case Ye.GREATER_EQUAL:return t?Y0e:Z0e;case Ye.LESS:return t?Q0e:J0e;case Ye.LESS_EQUAL:return t?t2e:e2e;case Ye.LOGICAL_AND:return t?s2e:n2e;case Ye.NOT_EQUAL:return t?i2e:o2e;case Ye.SQUARED_DIFFERENCE:return G0e;case Ye.INT_DIV:return t?a2e:r2e;case Ye.PRELU:return t?d2e:c2e;case Ye.MAX:return R3("max",t);case Ye.MIN:return R3("min",t);case Ye.POW:return t?u2e:l2e;case Ye.COMPLEX_MULTIPLY_REAL:return B0e;case Ye.COMPLEX_MULTIPLY_IMAG:return W0e;default:throw new Error(`BinaryType ${e} is not implemented!`)}}var Oe;(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.IS_NAN=8]="IS_NAN",e[e.LINEAR=9]="LINEAR",e[e.LOG=10]="LOG",e[e.LOGICAL_NOT=11]="LOGICAL_NOT",e[e.NEG=12]="NEG",e[e.RELU=13]="RELU",e[e.RELU6=14]="RELU6",e[e.LEAKYRELU=15]="LEAKYRELU",e[e.RECIPROCAL=16]="RECIPROCAL",e[e.RSQRT=17]="RSQRT",e[e.SIN=18]="SIN",e[e.SINH=19]="SINH",e[e.SIGMOID=20]="SIGMOID",e[e.SQRT=21]="SQRT",e[e.SQUARE=22]="SQUARE",e[e.TANH=23]="TANH",e[e.TO_INT=24]="TO_INT"})(Oe||(Oe={}));var p2e="return abs(a);",h2e="return ceil(a);",f2e="return cos(a);",m2e=`
  let e2x = exp(-a);
  return (e2x + 1.0 / e2x) / 2.0;
`,g2e="return exp(a) - 1.0;",y2e="if (a >= 0.0) { return a; }  return (exp(a) - 1.0);",A2e=`
  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;
`,x2e="return exp(a);",b2e="return floor(a);",v2e="return f32(isnan(a));",w2e="return a;",k2e=`if (a < 0.0) { return 1.0/0.0; }
  return log(a);`,S2e="return f32(!(a >= 1.0));",I2e="return -a;",C2e="if (a < 0.0) { return uniforms.alpha * a; } return a;",T2e=`
  let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));
  return (aLessThanZero * (uniforms.alpha * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);
`,N2e="return 1.0 / a;",E2e="return select(a, 0.0, a < 0.0);",R2e="return clamp(a, 0.0, 6.0);",_2e="return clamp(a, vec4<f32>(0.0, 0.0, 0.0, 0.0), vec4<f32>(6.0, 6.0, 6.0, 6.0));",D2e=`
  return select(a, vec4<f32>(0.0), a < vec4<f32>(0.0));
`,$2e="return 1.0/sqrt(a);",P2e="return 1.0 / (1.0 + exp(-1.0 * a));",F2e="return sin(a);",O2e=`
  let e2x = exp(a);
  return (e2x - 1.0 / e2x) / 2.0;
`,M2e="return sqrt(a);",z2e="return a * a;",L2e=`
  let e2x = exp(-2.0 * abs(a));
  return sign(a) * (1.0 - e2x) / (1.0 + e2x);
`,B2e="return f32(i32((a)));";function qi(e,t){switch(e){case Oe.ABS:return p2e;case Oe.COS:return f2e;case Oe.COSH:return m2e;case Oe.CEIL:return h2e;case Oe.ELU:return t?A2e:y2e;case Oe.EXP:return x2e;case Oe.EXPM1:return g2e;case Oe.FLOOR:return b2e;case Oe.IS_NAN:return v2e;case Oe.LINEAR:return w2e;case Oe.LOG:return k2e;case Oe.LOGICAL_NOT:return S2e;case Oe.NEG:return I2e;case Oe.LEAKYRELU:return t?T2e:C2e;case Oe.RECIPROCAL:return N2e;case Oe.RELU:return t?D2e:E2e;case Oe.RELU6:return t?_2e:R2e;case Oe.RSQRT:return $2e;case Oe.SIGMOID:return P2e;case Oe.SIN:return F2e;case Oe.SINH:return O2e;case Oe.SQRT:return M2e;case Oe.SQUARE:return z2e;case Oe.TANH:return L2e;case Oe.TO_INT:return B2e;default:throw new Error(`BinaryType ${e} is not implemented!`)}}var Jt=e=>{switch(e){case 1:return"f32";case 2:return"vec2<f32>";case 3:return"vec3<f32>";case 4:return"vec4<f32>";default:throw new Error(`${e}-component is not supported.`)}};function wi(e,t=!1,n=!1,s=3){if(e===null)return"";let r="";if(e==="linear")r=qi(Oe.LINEAR);else if(e==="relu")r=qi(Oe.RELU,n);else if(e==="elu")r=qi(Oe.ELU,n);else if(e==="relu6")r=qi(Oe.RELU6,n);else if(e==="prelu")r=Ym(Ye.PRELU,n);else if(e==="sigmoid")r=qi(Oe.SIGMOID,n);else if(e==="leakyrelu")r=qi(Oe.LEAKYRELU,n);else throw new Error(`Activation ${e} has not been implemented for the WebGPU backend.`);let o=Jt(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 wd(e,t){return`
      ${e?"value = value + getBiasByOutputCoords(coords);":""}
      ${t?"value = activation(value, coords);":""}
      `}function ST(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) -> ${Jt(i)} {
    var value = ${Jt(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) -> ${Jt(i)} {
    let col = colIn * ${i};
    let batch = ${t?"0":"batchIn"};
    let batchBSize = uniforms.bShape[1] * uniforms.bShape[2];
    var value = ${Jt(i)}(0.0);
    ${u}
    return value;
  }
  `}function kb(e,t,n,s,r,a,o=!1,i=!1,l=!1,u=1){return`
  ${ST(n,s,r,a,o,i,l,u)}
  fn mm_write(batch: i32, row: i32, colIn: i32, valueIn: ${Jt(u)}) {
    let col = colIn * ${u};
    ${o&&i?"":"if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)"}
    {
      var value = valueIn;
      let coords = vec3<i32>(batch, row, col);
      ${wd(e,t)}
      setOutputAtCoords(coords[0], coords[1], coords[2], value);
    }
  }
  `}var W2e=e=>e?`
        mm_Asub[inputRow][inputCol] = mm_readA(batch,
          kStart + inputRow,
          globalRowStart / InnerElementSize + inputCol);
        `:`
        mm_Asub[inputRow][inputCol] = mm_readA(batch,
          globalRow + innerRow,
          kStart / InnerElementSize + inputCol);
        `,V2e=(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] = BCached0 * ACached0[i] + acc[i];
          acc[i] = BCached1 * ACached1[i] + acc[i];
          acc[i] = BCached2 * ACached2[i] + acc[i];
          ${t===3?"":"acc[i] = BCached3 * ACached3[i] + acc[i];"}
        }`:`
        for (var i = 0; i < RowPerThread; i = i + 1) {
          let ACached = mm_Asub[tileRow + i][k];
          acc[i] = BCached0 * ACached.x + acc[i];
          acc[i] = BCached1 * ACached.y + acc[i];
          acc[i] = BCached2 * ACached.z + acc[i];
          ${t===3?"":"acc[i] = BCached3 * ACached.w + acc[i];"}
        }`;function W2(e,t,n=!1,s=32,r=!1,a=32,o=!1){let i=t[1]*e[1],l=t[0]*e[0],u=n?i:s,c=n?s:i,p=u/t[0],d=s/t[1];return v.assert((n&&p===4&&e[1]===4||!n&&(p===3||p===4))&&u%t[0]===0&&s%t[1]===0&&e[0]===4,()=>`If transposeA ${n} is true, innerElementSize ${p} and workPerThread[1] ${e[1]} must be 4.
          Otherwise, innerElementSize ${p} must be 3 or 4.
      tileAWidth ${u} must be divisible by workGroupSize[0]${t[0]}. tileInner ${s} must be divisible by workGroupSize[1] ${t[1]}. ColPerThread ${e[0]} must be 4.`),`
  var<workgroup> mm_Asub : array<array<vec${p}<f32>, ${u/p}>, ${c}>;
  var<workgroup> mm_Bsub : array<array<vec4<f32>, ${l/e[0]}>, ${s}>;

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

  @compute @workgroup_size(workGroupSizeX, workGroupSizeY, workGroupSizeZ)
  fn _start(@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 = ${o?"0":"localRow * RowPerThread"};
    let tileCol = i32(localId.x);

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

    let numTiles = ${r?`${Math.ceil(a/s)}`:"(uniforms.dimInner - 1) / TileInner + 1"};
    var kStart = ${r?`i32(globalId.z) * ${a}`:"0"};

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

    // Loop over shared dimension.
    let tileRowB = localRow * ${d};
    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;
            ${W2e(n)}
        }

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

        // Compute acc values for a single thread.
        for (var k = 0; k < TileInner / InnerElementSize; k = k + 1) {
            let BCached0 = mm_Bsub[k * InnerElementSize][tileCol];
            let BCached1 = mm_Bsub[k * InnerElementSize + 1][tileCol];
            let BCached2 = mm_Bsub[k * InnerElementSize + 2][tileCol];
            ${p===3?"":"let BCached3 = mm_Bsub[k * InnerElementSize + 3][tileCol];"}

            ${V2e(n,p)}
        }

        workgroupBarrier();
    }

    for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {
        mm_write(batch, globalRow + innerRow, globalCol, acc[innerRow]);
    }
  }`}var U2e=e=>e?`
        mm_Asub[inputRow][inputCol] = mm_readA(batch,
          kStart + inputRow,
          globalRowStart + inputCol);
        `:`
        mm_Asub[inputRow][inputCol] = mm_readA(batch,
          globalRowStart + inputRow,
          kStart + inputCol);
        `,G2e=e=>e?"let ACached = mm_Asub[k][tileRow + innerRow];":"let ACached = mm_Asub[tileRow + innerRow][k];";function V2(e,t,n=!1,s=32,r=!1,a=32){let o=e[1]*t[1],i=e[0]*t[0],l=n?o:s,u=n?s:o;v.assert(u%t[1]===0&&l%t[0]===0&&s%t[1]===0,()=>`tileAHight ${u} must be divisible by workGroupSize[1]${t[1]}, tileAWidth ${l} must be divisible by workGroupSize[0]${t[0]}, tileInner ${s} must be divisible by workGroupSize[1]${t[1]}`);let c=u/t[1],p=l/t[0],d=s/t[1];return`
    var<workgroup> mm_Asub : array<array<f32, ${l}>, ${u}>;
    var<workgroup> mm_Bsub : array<array<f32, ${i}>, ${s}>;
    const RowPerThread = ${e[1]};
    const ColPerThread = ${e[0]};
    const TileInner = ${s};

    @compute @workgroup_size(workGroupSizeX, workGroupSizeY, workGroupSizeZ)
    fn _start(@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 = ${r?"0":"i32(globalId.z)"};
      let globalRowStart = i32(workgroupId.y) * ${o};

      let numTiles = ${r?`${Math.ceil(a/s)}`:"(uniforms.dimInner - 1) / TileInner + 1"};
      var kStart = ${r?`i32(globalId.z) * ${a}`:"0"};

      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) * ${c};
      let tileColA = i32(localId.x) * ${p};
      let tileRowB = i32(localId.y) * ${d};
      // 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 < ${c}; innerRow = innerRow + 1) {
          for (var innerCol = 0; innerCol < ${p}; innerCol = innerCol + 1) {
            let inputRow = tileRowA + innerRow;
            let inputCol = tileColA + innerCol;
            ${U2e(n)}
          }
        }

        // Load one tile of B into local memory.
        for (var innerRow = 0; innerRow < ${d}; 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,
              kStart + inputRow,
              globalCol + innerCol);
          }
        }
        kStart = kStart + TileInner;
        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) {
            ${G2e(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 H2e=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 j2e(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]}>;

    ${nt()} {
      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>(${H2e(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 q2e=class{constructor(e,t,n,s,r=!1,a=!1,o=null,i=null,l=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=t,this.dispatchLayout={x:[2],y:[1],z:[0]};let u=r?e[1]:e[2];if(this.isVec4=(u%4===0&&!r||t[1]%4===0&&r)&&t[2]%4===0&&!a,this.isVectorA=t[1]===1&&!r,!this.isVec4&&this.isVectorA)this.elementsPerThread=[1,1,1],this.workGroupSize=[32,1,1];else{let d=xT(t[1],u,t[2],r);this.workGroupSize=d.workGroupSize,this.elementsPerThread=d.elementsPerThread}this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize,this.elementsPerThread);let c=o!=null,p=l!=null;c&&this.variableNames.push("bias"),p&&this.variableNames.push("preluActivationWeights"),this.transposeA=r,this.transposeB=a,this.addBias=c,this.activation=i,this.hasPreluActivationWeights=p,this.batchAEqualOne=n,this.batchBEqualOne=s,[this.fitAOuter,this.fitBOuter,this.fitInner]=this.getShapeFit(t[1],t[2],u),this.shaderKey=`matMulPacked_${this.elementsPerThread}_${r}_${a}_${this.activation}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.isVectorA}_${this.batchAEqualOne}_${this.batchBEqualOne}`}getShapeFit(e,t,n){let s=this.workGroupSize[1]*this.elementsPerThread[1],r=this.workGroupSize[0]*this.elementsPerThread[0];!this.isVec4&&this.isVectorA?this.tileInner=this.workGroupSize[0]*4:this.tileInner=r;let a=e%s===0,o=t%r===0,i=n%this.tileInner===0;return[a,o,i]}getUserCode(){return`
      ${wi(this.activation,this.hasPreluActivationWeights,this.isVec4)}
      ${kb(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,!1,this.transposeB,this.fitAOuter,this.fitBOuter,this.fitInner,this.isVec4?4:1)}
      ${this.isVec4?W2(this.elementsPerThread,this.workGroupSize,this.transposeA,this.tileInner,!1,null,this.isVectorA):this.isVectorA?j2e(this.workGroupSize,this.transposeA):V2(this.elementsPerThread,this.workGroupSize,this.transposeA,this.tileInner)}
    `}};function X2e(){return`
    var<workgroup> sumValues : array<f32, workGroupSizeX>;
    ${nt()} {
      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 K2e=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=je(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`
      ${wi(this.activation,this.hasPreluActivationWeights)}
      ${kb(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,this.transposeA,this.transposeB)}
      ${X2e()}
    `}};function Z2e(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.
  ${nt()} {
    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 Y2e=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`
      ${wi(this.activation,this.hasPreluActivationWeights)}
      ${kb(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,this.transposeA,this.transposeB)}
      ${Z2e(this.workGroupSize)}
    `}},J2e=class{constructor(e,t,n,s,r=!1,a=!1){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workGroupSize=[8,8,1],this.atomic=!0,this.isVec4=!1,this.splitedDimInner=128,v.assert(e[0]===1,()=>"MatMulSplitKProgram only supports batch = 1."),this.outputShape=e,this.dispatchLayout={x:[2],y:[1],z:[0,3]},this.isVec4=(r&&this.outputShape[1]%4===0||!r&&t%4===0)&&this.outputShape[2]%4===0,this.elementsPerThread=[4,4,this.splitedDimInner],this.isVec4||(this.outputShape[1]<16&&(this.elementsPerThread[1]=1),this.outputShape[2]<16&&(this.elementsPerThread[0]=1)),this.dispatch=je(this.dispatchLayout,[this.outputShape[0],this.outputShape[1],this.outputShape[2],t],this.workGroupSize,this.elementsPerThread),this.transposeA=r,this.transposeB=a,this.batchAEqualOne=n,this.batchBEqualOne=s,this.shaderKey=`matMulSplitK_${r}_${a}_${n}_${s}_${this.elementsPerThread}_${this.isVec4}`}getUserCode(){let e=s=>`
      for (var i = 0; i < ${s}; i = i + 1)
      {
        var oldValue = atomicLoad(&(result[flatIndex + i]));
        var exchanged = false;
        for (; !exchanged;) {
          let newValueF32 = bitcast<f32>(oldValue) + ${s>1?"value[i]":"value"};
          let newValue = bitcast<i32>(newValueF32);
          let res = atomicCompareExchangeWeak(&(result[flatIndex + i]), oldValue, newValue);
          oldValue = res.old_value;
          exchanged = res.exchanged;
        }
      }
      `,t=this.isVec4?4:1;return`
      ${ST(this.batchAEqualOne,this.batchBEqualOne,!1,this.transposeB,!1,!1,!1,t)}
      fn mm_write(batch: i32, row : i32, colIn : i32, value : ${Jt(t)}) {
        let col = colIn * ${t};
        if (row < uniforms.dimAOuter && col < uniforms.dimBOuter) {
          let coords = vec3<i32>(batch, row, col);
          let flatIndex = getOutputIndexFromCoords(coords);
          // The problem is that we should initialize output to zero before using.
          // Otherwise, the original value will be added to the result.
          ${e(t)}
        }
      }
      ${this.isVec4?W2(this.elementsPerThread,this.workGroupSize,this.transposeA,32,!0,this.splitedDimInner):V2(this.elementsPerThread,this.workGroupSize,this.transposeA,32,!0,this.splitedDimInner)}
    `}},Q2e=class{constructor(e,t=null,n=null,s=null){this.uniforms="",this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),this.addBias=t!=null,this.hasPreluActivationWeights=s!=null,this.activation=n,this.addBias&&this.variableNames.push("bias"),this.hasPreluActivationWeights&&this.variableNames.push("preluActivationWeights"),this.shaderKey=`biasActivation_${n}`}getUserCode(){return`
    ${wi(this.activation,this.hasPreluActivationWeights)}
    ${nt("index")} {
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        var value = getXByOutputIndex(index);
        ${wd(this.addBias,this.activation)}
        setOutputAtIndex(index, value);
      }
    }
    `}},e1e=class{constructor(e){this.variableNames=[],this.outputShape=[],this.uniforms="value : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="fill"}getUserCode(){return`
    ${nt("index")} {
      if (index < uniforms.size) {
        setOutputAtIndex(index, uniforms.value);
      }
    }
  `}};function vu(e){let{backend:t,attrs:n}=e,{shape:s,value:r}=n,{dtype:a}=n;if(a=a||v.inferDtype(r),a==="string"){let o=v.getArrayFromDType(a,v.sizeFromShape(s));return o.fill(r),t.makeTensorInfo(s,a,o)}else{let o=new e1e(s),i=[{type:"float32",data:[r]}];return t.runWebGPUProgram(o,[],a,i)}}var t1e={kernelName:zc,backendName:"webgpu",kernelFunc:vu};function He(e){let{inputs:t,attrs:n}=e,{x:s}=t,{shape:r}=n,a=v.sizeFromShape(s.shape),o=v.inferFromImplicitShape(r,a),i=v.sizeFromShape(o);return v.assert(a===i,()=>`The new shape (${o}) has ${i} elements and the old shape (${s.shape}) has ${a} elements. The new shape and old shape must have the same number of elements.`),e.backend.incRef(s.dataId),{dataId:s.dataId,shape:o,dtype:s.dtype}}var n1e={kernelName:jl,backendName:"webgpu",kernelFunc:He};function Sb({a:e,b:t,transposeA:n,transposeB:s,backend:r,bias:a=null,preluActivationWeights:o=null,leakyreluAlpha:i=0,activation:l=null}){let u=e.shape.length,c=t.shape.length,p=n?e.shape[u-2]:e.shape[u-1],d=s?t.shape[c-1]:t.shape[c-2],h=n?e.shape[u-1]:e.shape[u-2],f=s?t.shape[c-2]:t.shape[c-1],m=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(m),x=v.sizeFromShape(g),b=uu.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,f]);v.assert(p===d,()=>`Error in matMul: inner shapes (${p}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${s} must match.`);let w=n?[y,p,h]:[y,h,p],k=s?[x,f,d]:[x,d,f],C=He({inputs:{x:e},backend:r,attrs:{shape:w}}),E=He({inputs:{x:t},backend:r,attrs:{shape:k}}),_=[C,E],$=Math.max(y,x),R=y===1,P=x===1,S=[C,E],M=[{type:"int32",data:[h]},{type:"int32",data:[f]},{type:"int32",data:[p]}],L,U,K=[$,h,f],q=H().get("WEBGPU_MATMUL_PROGRAM_TYPE");switch(q<0&&(h*f<=128?q=$r.MatMulReduceProgram:$===1&&h<=128&&f<=48&&d>=2e3?q=$r.MatMulSplitKProgram:h<=16&&(f<=512||d>=2*f)||f<=16&&(h<=512||p>=2*h)?q=$r.MatMulSmallOutputSizeProgram:q=$r.MatMulPackedProgram),q){case $r.MatMulReduceProgram:L=new K2e(K,R,P,n,s,a,l,o);break;case $r.MatMulSplitKProgram:{if(U=vu({backend:r,attrs:{shape:K,value:0,dtype:e.dtype}}),L=new J2e(K,d,R,P,n,s),a||l){U=r.runWebGPUProgram(L,S,e.dtype,M,U);let J=new Q2e(U.shape,a,l,o),te=null,le=[U];a&&le.push(a),o&&le.push(o),l==="leakyrelu"&&(te=[{type:"float32",data:[i]}],J.uniforms+=" alpha : f32,");let ae=r.runWebGPUProgram(J,le,U.dtype,te);_.push(U);let pe=He({inputs:{x:ae},backend:r,attrs:{shape:b}});_.push(ae);for(let ce of _)r.disposeData(ce.dataId);return pe}break}case $r.MatMulSmallOutputSizeProgram:L=new Y2e(w,k,K,n,s,a,l,o);break;case $r.MatMulPackedProgram:L=new q2e(w,K,R,P,n,s,a,l,o);break;default:throw new Error(`Unsupported MatMulProgramType ${q}.`)}a&&S.push(a),o&&S.push(o),l==="leakyrelu"&&(M.push({type:"float32",data:[i]}),L.uniforms+=" alpha : f32,"),U=r.runWebGPUProgram(L,S,e.dtype,M,U);let Z=He({inputs:{x:U},backend:r,attrs:{shape:b}});_.push(U);for(let J of _)r.disposeData(J.dataId);return Z}function s1e(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=s;return Sb({a:r,b:a,transposeA:l,transposeB:u,backend:n,bias:o,preluActivationWeights:i,leakyreluAlpha:p,activation:c})}var r1e={kernelName:ao,backendName:"webgpu",kernelFunc:s1e},h6=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.workGroupSize=[128,1,1],this.size=!0,this.outputShape=T.assertAndGetBroadcastShape(t,n),this.dispatchLayout=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`binaryOpComplex_${e}`,this.op=e}getUserCode(){return`
      fn binaryOpComplex(
          areal : f32, aimag : f32, breal : f32, bimag : f32) -> f32 {
        ${Ym(this.op,!1)}
      }

      ${nt("index")} {
        if(index < uniforms.size) {
          let areal = getARealByOutputIndex(index);
          let aimag = getAImagByOutputIndex(index);
          let breal = getBRealByOutputIndex(index);
          let bimag = getBImagByOutputIndex(index);
          setOutputAtIndex(index, binaryOpComplex(areal, aimag, breal, bimag));
        }
      }
    `}},Dy=class{constructor(e,t,n){this.size=!0,this.variableNames=["A","B"],this.outputShape=T.assertAndGetBroadcastShape(t,n),this.dispatchLayout=lt(this.outputShape),this.op=e,this.useSharedMemoryWithA=t.length===1&&n.length>1&&t[0]<1024,this.useSharedMemoryWithB=n.length===1&&t.length>1&&n[0]<1024,this.useSharedMemoryWithA||this.useSharedMemoryWithB?(this.isVec4=!1,this.lastDimensionSize=this.useSharedMemoryWithB?n[0]:t[0],this.shaderKey=`binary_${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}_${e}`,this.workGroupSize=[128,1,1]),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1])}getUserCode(){let e;if(this.type==="shared"){let t=this.lastDimensionSize>1?`coords[${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 {
          ${Ym(this.op,this.isVec4)}
        }
        var<workgroup> sharedBuf : array<f32, ${this.lastDimensionSize}>;
        ${nt("index")} {
          // 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=Ym(this.op,this.isVec4);e=`
       fn binaryOperation(a : ${t}, b : ${t}) -> ${t} {
         ${n}
       }
       ${nt("index")} {
         if (index < uniforms.size) {
           let a = getAByOutputIndex(index);
           let b = getBByOutputIndex(index);
           setOutputAtIndex(index, binaryOperation(a, b));
         }
       }
       `}return e}};function sr(e){let{inputs:t}=e,{x:n}=t;return e.backend.incRef(n.dataId),{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}var a1e={kernelName:zo,backendName:"webgpu",kernelFunc:sr};function kd(e){let{inputs:t,backend:n}=e,{real:s,imag:r}=t,a=n.makeTensorInfo(s.shape,"complex64"),o=n.tensorMap.get(a.dataId),i=sr({inputs:{x:s},backend:n}),l=sr({inputs:{x:r},backend:n});return o.complexTensorInfos={real:i,imag:l},a}var o1e={kernelName:jp,backendName:"webgpu",kernelFunc:kd},Kh=class{constructor(e,t){this.variableNames=["A"],this.size=!0;let n=128;this.workGroupSize=[n,1,1],this.outputShape=e,this.dispatchLayout=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),this.op=t,this.shaderKey=`unary_${t}`}getUserCode(){return`
      fn unaryOperation(a : f32) -> f32 {
        ${qi(this.op,!1)}
      }
      ${nt("index")} {
        if (index < uniforms.size) {
          let a = getAByOutputIndex(index);
          setOutputAtIndex(index, unaryOperation(a));
        }
      }
      `}};function kn({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 Kh(a.shape,e);return o.runWebGPUProgram(l,[a],i)}}function qn({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 Dy(e,o.shape,i.shape);return l.runWebGPUProgram(w,[A,b],Hn(y.dtype,x.dtype))});else{let g=new h6(Ye.COMPLEX_MULTIPLY_REAL,o.shape,i.shape),y=new h6(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=kd({inputs:{real:h,imag:f},backend:l});return l.disposeData(h.dataId),l.disposeData(f.dataId),m}let u=s||Hn(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"?T.fromUint8ToStringArray(p):p,f=o.dtype==="string"?T.fromUint8ToStringArray(d):d,[m,g]=t(o.shape,i.shape,h,f,u);return l.makeTensorInfo(g,u,m)}let c=new Dy(e,o.shape,i.shape);return l.runWebGPUProgram(c,[o,i],u)}}var{addImpl:i1e,castImpl:l1e,ceilImpl:u1e,concatImpl:c1e,equalImpl:d1e,expImpl:p1e,expm1Impl:h1e,floorImpl:f1e,gatherNdImpl:m1e,gatherV2Impl:g1e,greaterEqualImpl:y1e,greaterImpl:A1e,lessEqualImpl:x1e,lessImpl:b1e,logImpl:v1e,maxImpl:w1e,maximumImpl:k1e,minimumImpl:S1e,multiplyImpl:I1e,negImpl:C1e,notEqualImpl:T1e,prodImpl:N1e,rangeImpl:E1e,rsqrtImpl:R1e,scatterImpl:_1e,simpleAbsImpl:D1e,sliceImpl:$1e,stridedSliceImpl:P1e,stringNGramsImpl:F1e,subImpl:O1e,tileImpl:M1e,topKImpl:z1e,transposeImpl:L1e,uniqueImpl:r4e}=Gx,B1e=kn({opType:Oe.ABS,cpuKernelImpl:D1e}),W1e={kernelName:xl,backendName:"webgpu",kernelFunc:B1e},V1e=qn({opType:Ye.ADD,cpuKernelImpl:i1e,supportsComplex:!0}),U1e={kernelName:Da,backendName:"webgpu",kernelFunc:V1e},G1e=class{constructor(e){this.workPerThread=4,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e[0],this.variableNames=e.map((t,n)=>`T${n}`),this.dispatchLayout=lt(this.outputShape),this.dispatch=je(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`
      ${nt("index")} {
        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, ${t});
          }
        }
      }
    `}};function H1e(e){let{inputs:t,backend:n}=e,s=t;if(s.length===1)return sr({inputs:{x:s[0]},backend:n});let r=s.map(i=>i.dtype).reduce((i,l)=>Hn(i,l)),a=s.map(i=>i.shape),o=new G1e(a);return n.runWebGPUProgram(o,s,r)}var j1e={kernelName:xo,backendName:"webgpu",kernelFunc:H1e},IT=class{constructor(e,t,n){this.workGroupSize=[64,1,1],this.variableNames=["x"],this.uniforms="infinityValue : f32,",this.size=!0;let s=[t];this.op=n==="min"?"<":">";let[r,a]=T.computeOutAndReduceShapes(e,s);this.outputShape=r.length===0?[1]:r,this.dispatchLayout=lt(this.outputShape),v.sizeFromShape(a)<32||v.sizeFromShape(r)>1e3?(this.type="plain",this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize)):(this.type="shared",this.dispatch=je(this.dispatchLayout,this.outputShape,[1,1,1])),this.inputShape=e,this.shaderKey=`argMinMax_${this.op}_${this.type}`}getUserCode(){let e=()=>this.inputShape.length===1?"uniforms.xShape":`uniforms.xShape.${Ca(this.inputShape.length-1)}`,t=()=>{let n="";if(this.outputShape.length===1)this.inputShape.length!==1&&(n+="outputCoords,");else for(let s=0;s<this.outputShape.length;s++)n+=`outputCoords.${Ca(s)},`;return n};return this.type==="shared"?`
      fn DIV_CEIL(a : u32, b : u32) -> u32 {
        return ((a - 1u) / b + 1u);
      }

      ${`
      var<workgroup> xBestIndices : array<i32, ${this.workGroupSize[0]}>;
      var<workgroup> xBestValues : array<f32, ${this.workGroupSize[0]}>;
    `}

      ${nt("index")} {
        let outputIndex = index / i32(workGroupSizeX);
        let reduceLength = ${e()};

        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(${t()} 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]);
        }
      }
    `:`
      ${nt("index")} {
        if (index < uniforms.size) {
          let outputCoords = getCoordsFromIndex(index);
          var bestIndex = 0;
          var bestValue = getX(${t()} 0);
          let reduceLength = ${e()};
          for (var i = 1; i < reduceLength; i++) {
            let candidate = getX(${t()} i);
            if (candidate ${this.op} bestValue) {
              bestValue = candidate;
              bestIndex = i;
            }
          }
          setOutputAtIndexI32(index, bestIndex);
        }
      }
      `}},q1e=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=je(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]}>;
      ${Vp()}
      fn _start(@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]);
        }
      }
    `}},X1e=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=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.newDim=t,this.shaderKey=`transpose_${t}`}getUserCode(){let e=Mn(this.outputShape.length),t=K1e(this.newDim);return`
      ${nt("index")} {
        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 K1e(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=new Array(t);for(let s=0;s<e.length;s++)n[e[s]]=`resRC.${Ca(s)}`;return n.join()}function _a(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=L1e(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 q1e(r.shape,a);return o.runWebGPUProgram(c,[r],r.dtype)}let u=new X1e(r.shape,a);return o.runWebGPUProgram(u,[r],r.dtype)}var Z1e={kernelName:na,backendName:"webgpu",kernelFunc:_a};function Y1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=v.parseAxisParam(a,r.shape),i=T.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=_a({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=T.getInnerMostAxes(o.length,l.shape.length)),T.assertAxesAreInnerMostDims("argMax",[o[0]],l.shape.length);let c=new IT(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 J1e={kernelName:bo,backendName:"webgpu",kernelFunc:Y1e};function Q1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=v.parseAxisParam(a,r.shape),i=T.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=_a({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=T.getInnerMostAxes(o.length,l.shape.length)),T.assertAxesAreInnerMostDims("argMin",[o[0]],l.shape.length);let c=new IT(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 ege={kernelName:Dc,backendName:"webgpu",kernelFunc:Q1e},tge=qn({opType:Ye.ATAN2}),nge={kernelName:bl,backendName:"webgpu",kernelFunc:tge},f6=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=lt(this.outputShape),this.dispatch=je(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"),`
      ${nt("index")} {
      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});
        }
      }
    `}},sge=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=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="poolWithFilterSizeEqualsOne"}getUserCode(){return`
      ${nt("index")} {
        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);
        }
      }
    `}},rge=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]=T.computeOutAndReduceShapes(this.inputShape,[1]);this.outputShape=n.length===0?[1]:n,this.dispatchLayout=lt(this.outputShape),this.dispatch=je(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;
       }
       ${nt("index")} {
         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) {
          ${n}
        }
       }
     `}};function Zh(e,t,n,s,r){let a=e.shape.length,o=[],i=v.parseAxisParam(t,e.shape),l=i,u=T.getAxesPermutation(l,a),c=e;u!=null&&(c=_a({inputs:{x:e},attrs:{perm:u},backend:r}),l=T.getInnerMostAxes(l.length,a),o.push(c)),T.assertAxesAreInnerMostDims(s,l,a);let[p,d]=T.computeOutAndReduceShapes(c.shape,l),h=p;n&&(h=T.expandShapeToKeepDim(p,i));let f;if((s==="max"||s==="prod")&&r.shouldExecuteOnCPU([c])){let m=r.tensorMap.get(c.dataId).values;switch(s){case"max":let g=w1e(m,v.sizeFromShape(d),h,e.dtype);f=r.makeTensorInfo(h,e.dtype,g);break;case"prod":let{outVals:y,outShape:x,outDtype:A}=N1e(c.shape,c.dtype,m,l);f=r.makeTensorInfo(x,A,y);break;default:throw new Error(`${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":ch(e.dtype),b=[{type:"int32",data:[m]}],w=new rge(x,s),k=r.runWebGPUProgram(w,[c],A,b);o.push(k),f=He({inputs:{x:k},attrs:{shape:h},backend:r})}return o.forEach(m=>r.disposeData(m.dataId)),f}function Ib(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reductionIndices:a,keepDims:o}=s;return Zh(r,a,o,"max",n)}var age={kernelName:Wo,backendName:"webgpu",kernelFunc:Ib};function CT(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{keepDims:a,axis:o}=s;return Zh(r,o,a,"mean",n)}var oge={kernelName:Go,backendName:"webgpu",kernelFunc:CT};function TT(e,t,n,s){if(t.filterWidth===1&&t.filterHeight===1&&v.arraysEqual(t.inShape,t.outShape))return sr({inputs:{x:e},backend:s});if(t.filterWidth===t.inWidth&&t.filterHeight===t.inHeight&&t.batchSize===1&&t.padInfo.type==="VALID"){let o=e.shape.length,i=He({inputs:{x:e},backend:s,attrs:{shape:[e.shape[o-3]*e.shape[o-2],e.shape[o-1]]}}),l;n==="avg"?l=CT({inputs:{x:i},backend:s,attrs:{axis:0,keepDims:!1}}):(v.assert(n==="max",()=>`Invalid pool type ${n}`),l=Ib({inputs:{x:i},backend:s,attrs:{reductionIndices:0,keepDims:!1}}));let u=He({inputs:{x:l},backend:s,attrs:{shape:t.outShape}});return s.disposeData(i.dataId),s.disposeData(l.dataId),u}let r,a=[{type:"int32",data:[t.strideHeight,t.strideWidth]}];return t.filterHeight===1&&t.filterWidth===1?r=new sge(t):(n==="avg"?r=new f6(t,"avg"):(v.assert(n==="max",()=>`Invalid pool type ${n}`),r=new f6(t,"max")),a.push({type:"int32",data:[t.padInfo.top,t.padInfo.left]},{type:"int32",data:[t.dilationHeight,t.dilationWidth]},{type:"int32",data:[t.inHeight,t.inWidth]},{type:"int32",data:[t.effectiveFilterHeight,t.effectiveFilterWidth]})),s.runWebGPUProgram(r,[e],e.dtype,a)}function ige(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1,c=T.computePool2DInfo(r.shape,a,o,u,i,l);return TT(r,c,"avg",n)}var lge={kernelName:vo,backendName:"webgpu",kernelFunc:ige};function uge(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;return Sb({a:r,b:a,transposeA:o,transposeB:i,backend:n})}var cge={kernelName:wo,backendName:"webgpu",kernelFunc:uge},dge=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=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.start=e,this.uniforms=`start : ${Mn(e.length)}, `,this.shaderKey="slice"}getUserCode(){let e=Mn(this.rank),t=pge(this.rank),n;return this.start.length===1?n=this.outputShape.map((r,a)=>"sourceLoc = uniforms.start + coords;"):n=this.outputShape.map((r,a)=>`sourceLoc.${$y[a]} = uniforms.start.${Ca(a)} + coords.${$y[a]};`),`
      ${nt("index")} {
        if (index < uniforms.size) {
          var sourceLoc : ${e};
          let coords = getCoordsFromIndex(index);
          ${n.join(`
`)}
          setOutputAtIndex(index, getSource(${t}));
        }
      }
    `}},$y=["x","y","z","w","u","v"];function pge(e){if(e===1)return"sourceLoc";if(e<=6)return $y.slice(0,e).map(t=>`sourceLoc.${t}`).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}function Sd(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,size:o}=s,[i,l]=jt.parseSliceParams(r,a,o);if(jt.assertParamsValid(r,i,l),n.shouldExecuteOnCPU([r])||r.dtype==="string"){let p=n.tensorMap.get(r.dataId),d=$1e(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 dge(i,l),c=[{type:"int32",data:i}];return n.runWebGPUProgram(u,[r],r.dtype,c)}var hge={kernelName:Yl,backendName:"webgpu",kernelFunc:Sd},fge=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=T.getReshaped(r.shape,a,i),u=T.getPermuted(l.length,a.length),c=T.getReshapedPermuted(r.shape,a,i),p=T.getSliceBeginCoords(o,a.length),d=T.getSliceSize(c,o,a.length),h=[],f=He({inputs:{x:r},backend:n,attrs:{shape:l}}),m=_a({inputs:{x:f},backend:n,attrs:{perm:u}}),g=He({inputs:{x:m},backend:n,attrs:{shape:c}}),y=Sd({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},mge={kernelName:vl,backendName:"webgpu",kernelFunc:fge},NT=qn({opType:Ye.NOT_EQUAL,dtype:"bool",cpuKernelImpl:T1e}),gge={kernelName:Ll,backendName:"webgpu",kernelFunc:NT};function Yh(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.tensorMap.get(s.dataId);return sr({inputs:{x:r.complexTensorInfos.real},backend:n})}var yge={kernelName:eh,backendName:"webgpu",kernelFunc:Yh};function Age(e,t){let n=new Kh(e.shape,Oe.TO_INT),s=t.runWebGPUProgram(n,[e],"int32");return{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}function Py(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dtype:a}=s;if(a==="complex64"){if(r.dtype==="complex64")return sr({inputs:{x:r},backend:n});let o=Gt(r.shape),i=Py({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=kd({inputs:{real:i,imag:o},backend:n});return o.dispose(),n.disposeData(i.dataId),l}if(r.dtype==="complex64"){let o=Yh({inputs:{input:r},backend:n}),i=Py({inputs:{x:o},backend:n,attrs:{dtype:a}});return n.disposeData(o.dataId),i}if(!v.hasEncodingLoss(r.dtype,a)){let o=sr({inputs:{x:r},backend:n});return{dataId:o.dataId,shape:o.shape,dtype:a}}if(n.shouldExecuteOnCPU([r])){let o=n.tensorMap.get(r.dataId).values,[i,l,u]=l1e(o,r.shape,r.dtype,a);return n.makeTensorInfo(i,l,u)}if(a==="int32")return Age(r,n);if(a==="bool"){let o=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),l=NT({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 xge={kernelName:ko,backendName:"webgpu",kernelFunc:Py},bge=kn({opType:Oe.CEIL,cpuKernelImpl:u1e}),vge={kernelName:So,backendName:"webgpu",kernelFunc:bge},wge=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=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.shaderKey="clipVec4"}getUserCode(){return`
      ${nt("index")} {
        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);
        }
      }
    `}},kge=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=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="clip"}getUserCode(){return`
      ${nt("index")} {
        if(index < uniforms.size) {
          let value = getAByOutputIndex(index);
          if (isnan(value)) {
            setOutputAtIndex(index, value);
            return;
          }
          setOutputAtIndex(index, clamp(value, uniforms.minVal, uniforms.maxVal));
        }
      }
    `}};function Sge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{clipValueMin:a,clipValueMax:o}=s,i,l=[{type:"float32",data:[a]},{type:"float32",data:[o]}];return v.sizeFromShape(r.shape)%4===0?i=new wge(r.shape):i=new kge(r.shape),n.runWebGPUProgram(i,[r],r.dtype,l)}var Ige={kernelName:$a,backendName:"webgpu",kernelFunc:Sge},Cge=class{constructor(e){this.uniforms="",this.workPerThread=4,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=T.computeOutShape(e,1),this.variableNames=e.map((t,n)=>`T${n}`),this.dispatchLayout=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.offsetLength=e.length-1;for(let t=0;t<this.offsetLength;t++)this.uniforms+=`offset${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`
      ${nt("index")} {
        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 U2(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.tensorMap.get(s.dataId);return sr({inputs:{x:r.complexTensorInfos.imag},backend:n})}var Tge={kernelName:Yp,backendName:"webgpu",kernelFunc:U2};function Ap(e,t,n){let s=e[0].dtype;if(s==="complex64"){let f=e.map(A=>Yh({inputs:{input:A},backend:n})),m=e.map(A=>U2({inputs:{input:A},backend:n})),g=Ap(f,t,n),y=Ap(m,t,n),x=kd({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 He({inputs:{x:w},backend:n,attrs:{shape:[-1,k]}})}),m=f.map(w=>({vals:n.readSync(w.dataId),shape:w.shape})),g=T.computeOutShape(f.map(w=>w.shape),1),y=f[0].shape[0]===1,x=c1e(m,g,s,y),A=T.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(Ap(y,t,n))}let m=Ap(f,t,n);for(let g of f)n.disposeData(g.dataId);return m}let{tensors2D:o,outShape:i}=Nge(e,t,n),l=o.map(f=>f.shape),u=new Cge(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=He({inputs:{x:d},backend:n,attrs:{shape:i}});return n.disposeData(d.dataId),h}function Nge(e,t,n){let s=T.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>He({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=T.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 sr({inputs:{x:i[0]},backend:n});let l=i.map(u=>u.shape);return T.assertParamsConsistent(l,a),Ap(i,a,n)}var Ege={kernelName:wl,backendName:"webgpu",kernelFunc:ET};function Rge(e,t,n,s,r=!1,a=null,o=!1,i=4,l=4,u=4){let c=_=>{switch(_){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 ${_} is not supported.`)}},p=_=>{switch(_){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 ${_} 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 = ${Jt(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 ${Jt(i)}(0.0);`:s&&n?`
      let col = colIn * ${i};
      ${x}`:`
      let col = colIn * ${i};
      if (row < uniforms.dimInner && col < uniforms.dimBOuter) {
        ${x}
      }
      return ${Jt(i)}(0.0);`,b=`${p(l)}`,w=Jt(u),k=Jt(e?i:l),C=Jt(e?l:i);return`
      ${wi(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) -> ${C} {
        ${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}
        ${wd(r,a)}
        setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
        }
      }`}var _ge=class{constructor(e,t,n,s,r=!1,a=null,o=!1){this.variableNames=["x","W"],this.uniforms="filterDims : vec2<i32>, pad : vec2<i32>, stride : vec2<i32>, dilation : vec2<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=e.outShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.isVec4=((e.inChannels%4===0||e.inChannels%3===0)&&this.isChannelsLast||e.outWidth%4===0&&!this.isChannelsLast)&&e.outChannels%4===0,this.dispatchLayout=this.isChannelsLast?{x:[3],y:[1,2],z:[0]}:{x:[2,3],y:[1],z:[0]},this.workGroupSize=bb(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=vb(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize,this.elementsPerThread),this.isVec4?(this.isChannelsLast&&e.inChannels%4!==0?(this.innerElementSize=3,this.variableTypes=["f32","vec4<f32>"]):(this.innerElementSize=4,this.variableTypes=["vec4<f32>","vec4<f32>"]),r&&(this.variableNames.push("bias"),this.variableTypes.push("vec4<f32>")),o&&(this.variableNames.push("preluActivationWeights"),this.variableTypes.push("vec4<f32>"))):(this.innerElementSize=this.elementsPerThread[0],r&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights")),this.addBias=r,this.activation=a,this.hasPreluActivationWeights=o,this.tileAOuter=this.workGroupSize[1]*this.elementsPerThread[1],this.tileBOuter=this.workGroupSize[0]*this.elementsPerThread[0],this.tileInner=Math.max(this.workGroupSize[0]*this.innerElementSize,this.workGroupSize[1]),this.fitAOuter=t%this.tileAOuter===0,this.fitBOuter=n%this.tileBOuter===0,this.fitInner=s%this.tileInner===0,this.shaderKey=`conv2DMM_${this.elementsPerThread}_${this.activation}}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.innerElementSize}_${this.isChannelsLast}`}getUserCode(){let e=this.isVec4?W2(this.elementsPerThread,this.workGroupSize,!this.isChannelsLast,this.tileInner):V2(this.elementsPerThread,this.workGroupSize,!this.isChannelsLast,this.tileInner),t=this.isVec4?[this.innerElementSize,4,4]:[1,1,1];return`
    ${Rge(this.isChannelsLast,this.fitAOuter,this.fitBOuter,this.fitInner,this.addBias,this.activation,this.hasPreluActivationWeights,t[0],t[1],t[2])}
    ${e}
  `}};function m6(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 Dge({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=He({inputs:{x:e},backend:s,attrs:{shape:[1,n.batchSize,y]}}),f=He({inputs:{x:t},backend:s,attrs:{shape:[1,y,n.outChannels]}})}else h=He({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=He({inputs:{x:t},backend:s,attrs:{shape:[1,n.inChannels,n.outChannels]}});if(d.push(h),d.push(f),a!=null){let y=m6(a.shape,l);y!=null&&(a=He({inputs:{x:a},backend:s,attrs:{shape:y}}),d.push(a))}if(r!=null){let y=m6(r.shape,l);y!=null&&(r=He({inputs:{x:r},backend:s,attrs:{shape:y}}),d.push(r))}let m=Sb({a:l?h:f,b:l?f:h,transposeA:u,transposeB:c,backend:s,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o}),g=He({inputs:{x:m},backend:s,attrs:{shape:n.outShape}});d.push(m);for(let y of d)s.disposeData(y.dataId);return g}function RT({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 Dge({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 _ge(n,d,h,f,l,i,u),x=[],A=[e,t];l&&(!c&&r.shape.length===1&&(r=He({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=He({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 $ge(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=n,p=T.convertConv2DDataFormat(l),d=T.computeConv2DInfo(r.shape,a.shape,o,u,i,c,!1,p);return RT({x:r,filter:a,convInfo:d,backend:s})}var Pge={kernelName:Io,backendName:"webgpu",kernelFunc:$ge};function Fge(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 ${Jt(e)}(0.0);
      }
      if (xC < 0.0 || xC >= f32(uniforms.outBackprop[2]) || fract(xC) > 0.0) {
        return ${Jt(e)}(0.0);
      }
      let coord = vec4<i32>(
          batch,
          i32(xR),
          i32(xC),
          col % uniforms.outBackprop[3]);
      return x[getIndexFromCoords4D(coord, uniforms.xShape)/${e}];`}
      }
      return ${Jt(e)}(0.0);`;return`
  fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${Jt(e)} {
    let col = colIn * ${e};
    ${s}
  }

  fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${Jt(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 ${Jt(e)}(0.0);
  }

  fn mm_write(batch: i32, row : i32, colIn : i32, valueInput : ${Jt(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 Oge=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=bb(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=vb(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize,this.elementsPerThread),this.isVec4&&(this.variableTypes=["vec4<f32>","f32"]),this.shaderKey=`conv2DDerInputMM_${this.isVec4}_${this.elementsPerThread}`}getUserCode(){let e=this.isVec4?W2(this.elementsPerThread,this.workGroupSize):V2(this.elementsPerThread,this.workGroupSize);return`
    ${Fge(this.isVec4?4:1)}
    ${e}
    `}},Mge=class{constructor(e){this.variableNames=["dy","W"],this.uniforms="filterDims : vec2<i32>, pads : vec2<i32>, stride : vec2<i32>, outBackprop : vec4<i32>,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",this.shaderKey=`conv2DDerInput_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?1:2,t=this.isChannelsLast?2:3,n=this.isChannelsLast?3:1;return`
    ${nt("index")} {
      if(index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let batch = coords[0];
        let d1 = coords[${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 zge(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=T.convertConv2DDataFormat(u),d=T.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(H().getBool("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE"))f=new Mge(d);else{f=new Oge(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 Lge={kernelName:Co,backendName:"webgpu",kernelFunc:zge},Bge=kn({opType:Oe.COS}),Wge={kernelName:To,backendName:"webgpu",kernelFunc:Bge},Vge=kn({opType:Oe.COSH}),Uge={kernelName:No,backendName:"webgpu",kernelFunc:Vge},Gge=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=lt(this.outputShape),this.dispatch=je(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`
    ${nt("index")} {
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let height_ratio = f32(${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);
        }
      }
    }
    `}},Hge=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 Gge(r.shape[3],a.shape,i,l),p=[{type:"float32",data:[u]}];return n.runWebGPUProgram(c,[r,a,o],"float32",p)},jge={kernelName:Sl,backendName:"webgpu",kernelFunc:Hge},Up;(function(e){e.Prod="*",e.Sum="+"})(Up||(Up={}));var g6=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=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),this.exclusive=n,this.reverse=s,this.op=e,this.shaderKey=`cum_${this.op}_${this.exclusive}_${this.reverse}`}getUserCode(){let e=this.outputShape.length,t=this.op===Up.Prod?"1.0":"0.0",n=this.exclusive?t:`getX(${y6(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"),`
      ${nt("index")} {
       if (index < uniforms.size) {
         var coords = getCoordsFromIndex(index);

         let end = ${A6(e,"coords",this.op)};
         var val = ${n};
         let pow2 = i32(pow(2.0, uniforms.index));
         if (${r}) {
           let idx = ${a};
           ${A6(e,"coords",this.op)} = idx;
           val ${this.op}= getX(${y6(e,"coords",this.op)});
         }
         setOutputAtIndex(index, val);
       }
      }
    `}};function y6(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 ${e} is not yet supported`)}function A6(e,t,n){if(e===1)return`${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 ${e} is not yet supported`)}function _T(e,t,n,s,r,a){let o=t.shape.length,i=T.getAxesPermutation([s],o),l=t;i!=null&&(l=_a({inputs:{x:t},backend:n,attrs:{perm:i}}));let u=T.getInnerMostAxes(1,o)[0];if(u!==o-1)throw new Error(`WebGPU cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${s}`);let c=l.shape[u],p=sr({inputs:{x:l},backend:n});for(let d=0;d<=Math.ceil(Math.log2(c))-1;d++){let h=new g6(e,l.shape,!1,a),f=p,m=[{type:"float32",data:[d]}];p=n.runWebGPUProgram(h,[p],p.dtype,m),n.disposeData(f.dataId)}if(r){let d=new g6(e,l.shape,r,a),h=p,f=[{type:"float32",data:[0]}];p=n.runWebGPUProgram(d,[p],p.dtype,f),n.disposeData(h.dataId)}if(i!=null){let d=T.getUndoAxesPermutation(i),h=_a({inputs:{x:p},backend:n,attrs:{perm:d}});return n.disposeData(p.dataId),n.disposeData(l.dataId),h}return p}function qge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;return _T(Up.Prod,r,n,a,o,i)}var Xge={kernelName:kl,backendName:"webgpu",kernelFunc:qge};function Kge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;return _T(Up.Sum,r,n,a,o,i)}var Zge={kernelName:Eo,backendName:"webgpu",kernelFunc:Kge},Yge=class{constructor(e,t){this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.uniforms="blockSize : i32,",this.outputShape=e,this.dispatchLayout=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`depthToSpace_${t}`,this.dataFormat=t}getUserCode(){return`
      ${nt("index")} {
        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 = ${this.getInputSamplingString()};
          setOutputAtIndex(index, rlt);
        }
      }`}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?"uniforms.outShape[3]":"uniforms.outShape[1]"}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function Jge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockSize:a,dataFormat:o}=s,i=r.shape[0],l=o==="NHWC"?r.shape[1]:r.shape[2],u=o==="NHWC"?r.shape[2]:r.shape[3],c=o==="NHWC"?r.shape[3]:r.shape[1],p=l*a,d=u*a,h=c/(a*a),f=o==="NHWC"?[i,p,d,h]:[i,h,p,d],m=[{type:"int32",data:[a]}],g=new Yge(f,o);return n.runWebGPUProgram(g,[r],r.dtype,m)}var Qge={kernelName:Il,backendName:"webgpu",kernelFunc:Jge},e3e=class{constructor(e,t,n,s=!1,r=null,a=!1){this.variableNames=["x","W"],this.uniforms="pad : vec2<i32>, inDims : vec2<i32>,",this.workGroupSize=[16,16,1],this.outputShape=e,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),s&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),this.addBias=s,this.activation=r,this.hasPreluActivation=a,this.filterHeight=t,this.filterWidth=n,this.shaderKey=`depthwiseNCHW_${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`
      ${wi(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;
      }

      ${Vp()}
      fn _start(@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);
          }
        }
        ${wd(this.addBias,this.activation)}
        if (coordsInBounds4D(coords, uniforms.outShape)) {
          setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
        }
      }
    `}},DT=class{constructor(e,t=!1,n=null,s=!1){this.variableNames=["x","W"],this.uniforms="pad : vec2<i32>, inDims : vec2<i32>,",this.workGroupSize=[4,4,4],this.isVec4=!0,this.outputShape=e.outShape,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize,[4,4,1]),v.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),t&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=n,this.hasPreluActivation=s,this.shaderKey=`depthwiseVec4_${n}_${this.convInfo.filterHeight}_${this.convInfo.filterWidth}`}getUserCode(){let e=4+this.convInfo.filterWidth-1;return`
      ${wi(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;
      }
      ${Vp()}
      fn _start(@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];
            ${wd(this.addBias,this.activation)}
            setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
          }
        }
      }
    `}},$T=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=lt(this.outputShape),this.dispatch=je(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`
      ${wi(this.activation,this.hasPreluActivation,!1,4)}

      ${nt()} {
        let coords = getOutputCoords();
        let batch = coords[0];
        let xRCCorner = vec2<i32>(coords.${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;
              }
            }
          }
          ${wd(this.addBias,this.activation)}
        if (coordsInBounds4D(coords, uniforms.outShape)) {
          setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
        }
      }
    `}};function t3e(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=T.convertConv2DDataFormat(l),d=u;d==null&&(d=[1,1]);let h=T.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 e3e(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 DT(h):(g=new $T(h),f.push({type:"int32",data:[h.filterHeight]},{type:"int32",data:[h.filterWidth]},{type:"int32",data:[h.strideHeight,h.strideWidth]},{type:"int32",data:[h.dilationHeight,h.dilationWidth]})),n.runWebGPUProgram(g,[r,a],r.dtype,f)}var n3e={kernelName:Ro,backendName:"webgpu",kernelFunc:t3e},PT=qn({opType:Ye.MUL,cpuKernelImpl:I1e,supportsComplex:!0}),s3e={kernelName:Xo,backendName:"webgpu",kernelFunc:PT};function Cb(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return Zh(r,a,o,"sum",n)}var r3e={kernelName:ii,backendName:"webgpu",kernelFunc:Cb};function a3e(e){let{inputs:t,backend:n,attrs:s}=e,{equation:r}=s,a=t,{allDims:o,summedDims:i,idDims:l}=T.decodeEinsumEquation(r,a.length);T.checkEinsumDimSizes(o.length,l,a);let{path:u,steps:c}=T.getEinsumComputePath(i,l),p=c.length,d=null,h=o.length,f=[];for(let m=0;m<p;++m){for(let g of c[m]){let{permutationIndices:y,expandDims:x}=T.getEinsumPermutation(h,l[g]),A;T.isIdentityPermutation(y)?A=a[g]:(A=_a({inputs:{x:a[g]},backend:n,attrs:{perm:y}}),f.push(A));let b=A.shape.slice();for(let w=0;w<x.length;++w)b.splice(x[w],0,1);v.arraysEqual(A.shape,b)||(A=He({inputs:{x:A},backend:n,attrs:{shape:b}}),f.push(A)),d===null?d=A:(d=PT({inputs:{a:A,b:d},backend:n}),f.push(d))}m<p-1&&(u[m]>=0&&(d=Cb({inputs:{x:d},backend:n,attrs:{axis:u[m]-(o.length-h),keepDims:!1}}),f.push(d)),h--)}for(let m of f)m!==d&&n.disposeData(m.dataId);return d}var o3e={kernelName:Zp,backendName:"webgpu",kernelFunc:a3e},i3e=kn({opType:Oe.ELU}),l3e={kernelName:Do,backendName:"webgpu",kernelFunc:i3e},u3e=qn({opType:Ye.EQUAL,dtype:"bool",cpuKernelImpl:d1e}),c3e={kernelName:Cl,backendName:"webgpu",kernelFunc:u3e},FT=kn({opType:Oe.EXP,cpuKernelImpl:p1e,dtype:"float32"}),d3e={kernelName:$o,backendName:"webgpu",kernelFunc:FT};function Fy(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),He({inputs:{x:a},backend:s,attrs:{shape:i}})}var p3e={kernelName:Tl,backendName:"webgpu",kernelFunc:Fy},h3e=kn({opType:Oe.EXPM1,cpuKernelImpl:h1e}),f3e={kernelName:Nl,backendName:"webgpu",kernelFunc:h3e},m3e=class{constructor(e){this.outputShape=[],this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="flipLeftRight"}getUserCode(){return`
      ${nt("index")} {
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let coordX = uniforms.xShape[2] - coords[2] - 1;
          let outputValue = getX(coords[0], coords[1], coordX, coords[3]);
          setOutputAtIndex(index, outputValue);
        }
      }
    `}},g3e={kernelName:El,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,s=t,r=new m3e(n.shape);return s.runWebGPUProgram(r,[n],n.dtype)}},y3e=kn({opType:Oe.FLOOR,cpuKernelImpl:f1e}),A3e={kernelName:Po,backendName:"webgpu",kernelFunc:y3e},x3e=qn({opType:Ye.INT_DIV,dtype:"int32"}),b3e={kernelName:Fo,backendName:"webgpu",kernelFunc:x3e},v3e=class{constructor(e,t,n=!1){this.isFromPixels=!0,this.outputShape=[0],this.variableNames=[],this.workGroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize,[t,1,1]),this.importVideo=n,this.shaderKey=`fromPixels_${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>"};
      ${nt("index")} {
        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]));
          }
        }
      }
  `}},w3e={kernelName:Ip,backendName:"webgpu",kernelFunc:k3e},Qu,_3=H().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU"),cm=new Map;function k3e(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=H().getBool("WEBGPU_IMPORT_EXTERNAL_TEXTURE")&&o,f=o||i;if(u||l||f){let x;if(h){let $=r;if(!cm.has($)||cm.get($).expired){let R={source:$};cm.set($,n.device.importExternalTexture(R))}x={width:c,height:p,format:null,usage:null,texture:cm.get($)}}else{if(f){let S=H().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(Qu==null||S!==_3)&&(_3=S,Qu=document.createElement("canvas").getContext("2d",{willReadFrequently:_3})),Qu.canvas.width=c,Qu.canvas.height=p,Qu.drawImage(r,0,0,c,p),r=Qu.canvas}let $=GPUTextureUsage.COPY_DST|GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING,R="rgba8unorm",P=n.textureManager.acquireTexture(d[1],d[0],R,$);n.queue.copyExternalImageToTexture({source:r},{texture:P},[d[1],d[0]]),x={width:c,height:p,format:R,usage:$,texture:P}}let A=v.sizeFromShape(d),b=v.computeStrides(d),w=new v3e(d,a,h),k=[{type:"uint32",data:[A]},{type:"uint32",data:[a]},{type:"uint32",data:[...b]}],C=n.makeTensorInfo([p,c],"int32"),E=n.tensorMap.get(C.dataId);E.resourceInfo=x;let _=n.runWebGPUProgram(w,[C],"int32",k);return n.disposeData(C.dataId),_}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 S3e=class{constructor(e,t,n,s,r){this.uniforms="varianceEpsilon : f32,",this.workGroupSize=[128,1,1],this.size=!0,this.variableNames=["x","mean","variance"],T.assertAndGetBroadcastShape(e,t),T.assertAndGetBroadcastShape(e,n),this.outputShape=e,this.dispatchLayout=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),s!=null&&(T.assertAndGetBroadcastShape(e,s),this.variableNames.push("offset")),r!=null&&(T.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)"),`
      ${nt("index")} {
        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)));
        }
      }
  `}},I3e={kernelName:Oo,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 S3e(s.shape,o.shape,i.shape,p,d),f=[{type:"float32",data:[l]}];return u.runWebGPUProgram(h,c,s.dtype,f)}};function C3e(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=T.convertConv2DDataFormat(c),g=T.computeConv2DInfo(r.shape,a.shape,l,p,u,d,!1,m);return RT({x:r,filter:a,convInfo:g,backend:n,bias:o,preluActivationWeights:i,leakyreluAlpha:f,activation:h})}var T3e={kernelName:oo,backendName:"webgpu",kernelFunc:C3e};function N3e(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(T.eitherStridesOrDilationsAreOne(l,f),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${f}'`);let m=T.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 DT(m,y,d,x):(b=new $T(m,y,d,x),A.push({type:"int32",data:[m.filterHeight]},{type:"int32",data:[m.filterWidth]},{type:"int32",data:[m.strideHeight,m.strideWidth]},{type:"int32",data:[m.dilationHeight,m.dilationWidth]})),d==="leakyrelu"&&(A.push({type:"float32",data:[h]}),b.uniforms+=" alpha : f32,"),n.runWebGPUProgram(b,g,"float32",A)}var E3e={kernelName:io,backendName:"webgpu",kernelFunc:N3e},R3e=class{constructor(e,t){this.variableNames=["A","indices"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`gathernd_${e}`,this.sliceDim=e,this.uniforms=`sliceDim : i32, strides : ${Mn(e)},`}getUserCode(){let e;return this.sliceDim>1?e="uniforms.strides[j]":e="uniforms.strides",`
      ${nt("index")} {
        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 _3e(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]=T.prepareAndValidate(s,r),d=He({inputs:{x:r},backend:n,attrs:{shape:[u,o]}}),h=He({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=m1e(x,A,s.dtype,u,o,c,p,s.shape,i);return n.makeTensorInfo(l,s.dtype,b.values)}let f=new R3e(o,[u,c]),m=[{type:"int32",data:[o]},{type:"int32",data:p}],g=n.runWebGPUProgram(f,[h,d],h.dtype,m),y=He({inputs:{x:g},backend:n,attrs:{shape:l}});return n.disposeData(d.dataId),n.disposeData(h.dataId),n.disposeData(g.dataId),y}var D3e={kernelName:_l,backendName:"webgpu",kernelFunc:_3e},$3e=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=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="gather"}getUserCode(){let e=P3e(this.aShape);return`
      ${nt("index")} {
        if (index < uniforms.size) {
          let resRC = getCoordsFromIndex(index);
          let indexZ = i32(getIndices(resRC.x, resRC.z));
          let inBounds = select(0.0, 1.0, indexZ >= 0 && indexZ < uniforms.aShape[2]);
          setOutputAtIndex(index, inBounds * getA(${e}));
        }
      }
    `}};function P3e(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 OT(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=T.segment_util.collectGatherOpShapeInfo(r,a,l,i),c=v.sizeFromShape(a.shape),p=[],d=He({inputs:{x:r},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=He({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=Ue(h.shape,h.dtype,A),k=n.tensorMap.get(d.dataId).values,C=Ue(d.shape,d.dtype,k),E=g1e(C,b,f);return p.forEach(_=>n.disposeData(_.dataId)),n.makeTensorInfo(u.outputShape,E.dtype,E.values)}let m=new $3e(d.shape,f),g=n.runWebGPUProgram(m,[d,h],d.dtype);p.push(g);let y=He({inputs:{x:g},backend:n,attrs:{shape:u.outputShape}});return p.forEach(x=>n.disposeData(x.dataId)),y}var F3e={kernelName:Rl,backendName:"webgpu",kernelFunc:OT},O3e=qn({opType:Ye.GREATER,cpuKernelImpl:A1e,dtype:"bool"}),M3e={kernelName:Dl,backendName:"webgpu",kernelFunc:O3e},z3e=qn({opType:Ye.GREATER_EQUAL,dtype:"bool",cpuKernelImpl:y1e}),L3e={kernelName:Mo,backendName:"webgpu",kernelFunc:z3e},B3e=kn({opType:Oe.IS_NAN,dtype:"bool"}),W3e={kernelName:$l,backendName:"webgpu",kernelFunc:B3e};function V3e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{alpha:a}=s,o=[{type:"float32",data:[a]}],i=new Kh(r.shape,Oe.LEAKYRELU);return i.uniforms="alpha : f32,",n.runWebGPUProgram(i,[r],"float32",o)}var U3e={kernelName:Lo,backendName:"webgpu",kernelFunc:V3e},G3e=qn({opType:Ye.LESS,dtype:"bool",cpuKernelImpl:b1e}),H3e={kernelName:Pl,backendName:"webgpu",kernelFunc:G3e},j3e=qn({opType:Ye.LESS_EQUAL,dtype:"bool",cpuKernelImpl:x1e}),q3e={kernelName:Fl,backendName:"webgpu",kernelFunc:j3e},X3e=kn({opType:Oe.LOG,cpuKernelImpl:v1e}),K3e={kernelName:Bo,backendName:"webgpu",kernelFunc:X3e},Z3e=qn({opType:Ye.LOGICAL_AND,dtype:"bool"}),Y3e={kernelName:Ol,backendName:"webgpu",kernelFunc:Z3e},J3e=kn({opType:Oe.LOGICAL_NOT}),Q3e={kernelName:Ml,backendName:"webgpu",kernelFunc:J3e},eye=qn({opType:Ye.MAX,cpuKernelImpl:k1e}),tye={kernelName:Vo,backendName:"webgpu",kernelFunc:eye};function nye(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1,c=T.computePool2DInfo(r.shape,a,o,u,i,l);return TT(r,c,"max",n)}var sye={kernelName:Uo,backendName:"webgpu",kernelFunc:nye};function rye(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return Zh(r,a,o,"min",n)}var aye={kernelName:Ho,backendName:"webgpu",kernelFunc:rye},oye=qn({opType:Ye.MIN,cpuKernelImpl:S1e}),iye={kernelName:jo,backendName:"webgpu",kernelFunc:oye},lye=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=lt(this.outputShape),this.dispatch=je(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=Mn(e),i=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
      ${nt("index")} {
        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}));
        }
      }
    `}},uye={kernelName:qo,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 lye(s.shape,r,a);return o.runWebGPUProgram(l,[s],s.dtype,i)}};function cye(e){let{inputs:t,backend:n}=e,{x:s}=t;if(n.shouldExecuteOnCPU([s])){let a=n.tensorMap.get(s.dataId),[o,i]=C1e(a.values,s.shape,s.dtype);return n.makeTensorInfo(i,s.dtype,o)}let r=new Kh(s.shape,Oe.NEG);return n.runWebGPUProgram(r,[s],s.dtype)}var dye={kernelName:zl,backendName:"webgpu",kernelFunc:cye};function pye(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}=Ar.nonMaxSuppressionV3Impl(u,c,o,i,l);return n.makeTensorInfo([p.length],"int32",new Int32Array(p))}var hye={kernelName:Bl,backendName:"webgpu",kernelFunc:pye};function fye(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}=Ar.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 mye={kernelName:Wl,backendName:"webgpu",kernelFunc:fye};function Jm(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="complex64"){let r=Yh({inputs:{input:s},backend:n}),a=Jm({inputs:{x:r},backend:n}),o=U2({inputs:{input:s},backend:n}),i=Jm({inputs:{x:o},backend:n}),l=kd({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 vu({attrs:{shape:s.shape,dtype:s.dtype,value:s.dtype==="string"?"":0},backend:n})}var gye={kernelName:ou,backendName:"webgpu",kernelFunc:Jm};function MT(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=Yh({inputs:{input:s},backend:n}),a=MT({inputs:{x:r},backend:n}),o=U2({inputs:{input:s},backend:n}),i=Jm({inputs:{x:o},backend:n}),l=kd({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 vu({attrs:{shape:s.shape,dtype:s.dtype,value:1},backend:n})}var yye={kernelName:Vl,backendName:"webgpu",kernelFunc:MT};function Aye(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return Fy({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=Fy({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 xye={kernelName:Gl,backendName:"webgpu",kernelFunc:Aye},bye=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=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),t.map((n,s)=>{this.uniforms+=` pad${s} : vec2<i32>,`}),this.xShape=e,this.shaderKey="pad"}getUserCode(){let e=this.xShape.length,t=Mn(e),n=this.xShape.map((c,p)=>`uniforms.pad${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`
      ${nt("index")} {
        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}));
          }
        }
      }
    `}},zT=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 sr({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 vu({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 bye(r.shape,a);return n.runWebGPUProgram(l,[r],r.dtype,i)},vye={kernelName:Ko,backendName:"webgpu",kernelFunc:zT},wye=qn({opType:Ye.POW}),kye={kernelName:Zo,backendName:"webgpu",kernelFunc:wye};function Sye(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t,a=new Dy(Ye.PRELU,s.shape,r.shape);return n.runWebGPUProgram(a,[s,r],"float32")}var Iye={kernelName:Yo,backendName:"webgpu",kernelFunc:Sye};function Cye(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return Zh(r,a,o,"prod",n)}var Tye={kernelName:Jo,backendName:"webgpu",kernelFunc:Cye},Nye=e=>{let{backend:t,attrs:n}=e,{start:s,stop:r,step:a,dtype:o}=n,i=E1e(s,r,a,o);return t.makeTensorInfo([i.length],o,i)},Eye={kernelName:Hc,backendName:"webgpu",kernelFunc:Nye},LT=qn({opType:Ye.DIV}),Rye={kernelName:_o,backendName:"webgpu",kernelFunc:LT},_ye=kn({opType:Oe.RECIPROCAL}),Dye={kernelName:Hl,backendName:"webgpu",kernelFunc:_ye},$ye=kn({opType:Oe.RELU}),Pye={kernelName:Qo,backendName:"webgpu",kernelFunc:$ye},Fye=kn({opType:Oe.RELU6}),Oye={kernelName:ni,backendName:"webgpu",kernelFunc:Fye},Mye=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=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="resizeBilinear"}getUserCode(){return`
      ${nt("index")} {
        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 zye(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 Mye(r.shape,l,u);return n.runWebGPUProgram(f,[r],"float32",h)}var Lye={kernelName:ti,backendName:"webgpu",kernelFunc:zye},Bye=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=lt(this.outputShape),this.dispatch=je(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",`
      ${nt("index")} {
        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 Wye(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 Bye(r.shape,l,u,o);return n.runWebGPUProgram(f,[r],r.dtype,h)}var Vye={kernelName:ei,backendName:"webgpu",kernelFunc:Wye},Uye=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=lt(this.outputShape),this.dispatch=je(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`
        ${nt("index")} {
          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));
            ${this.fillSnippet}
            if(coordX >= 0 && coordX < uniforms.xShape[2] && coordY >= 0 &&
                coordY < uniforms.xShape[1]) {
              outputValue = getX(coords[0], coordY, coordX, coords[3]);
            }
            setOutputAtIndex(index, outputValue);
          }
        }
      `}},Gye={kernelName:iu,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:s}=e,{radians:r,fillValue:a,center:o}=t,i=n,l=new Uye(s.shape,a),[u,c]=T.getImageCenter(o,s.shape[1],s.shape[2]),p=[{type:"float32",data:[u]},{type:"float32",data:[c]},{type:"float32",data:[Math.sin(r)]},{type:"float32",data:[Math.cos(r)]}];return typeof a=="number"?p.push({type:"float32",data:[Number.parseFloat(a.toFixed(2))]}):p.push({type:"float32",data:a}),i.runWebGPUProgram(l,[s],s.dtype,p)}},Hye=kn({opType:Oe.RSQRT,cpuKernelImpl:R1e}),jye={kernelName:si,backendName:"webgpu",kernelFunc:Hye},bm=class{constructor(e,t,n,s,r,a,o,i=!0){this.variableNames=["updates","indices"],this.workGroupSize=[64,1,1],this.atomic=!0,this.outputShape=a,this.type=o,this.sumDupeIndices=i,this.dispatchLayout=lt(e),this.dispatch=je(this.dispatchLayout,e,this.workGroupSize),this.sliceDimGreaterThanOne=t>1,this.shaderKey=`scatter_${n}_${s}_${this.sliceDimGreaterThanOne}_${o}_${i}`;let l=Mn(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}

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

          ${i("&result[flatIndex]","updateValue")};
        }
      }`}};function qye(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}=T.calculateShapes(a,r,o),d=[p/u,u];if(p===0)return n.makeTensorInfo(o,r.dtype);let h=He({inputs:{x:r},backend:n,attrs:{shape:[l,i]}}),f=He({inputs:{x:a},backend:n,attrs:{shape:[l,u]}}),m=f.dtype,g=vu({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 bm(f.shape,i,h.shape.length,f.shape.length,c,d,m),b=n.runWebGPUProgram(A,[f,h],m,x,g),w=He({inputs:{x:b},backend:n,attrs:{shape:o}});return n.disposeData(h.dataId),n.disposeData(f.dataId),n.disposeData(b.dataId),w}var Xye={kernelName:Kl,backendName:"webgpu",kernelFunc:qye},Kye=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=lt(this.outputShape),this.dispatch=je(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`
      ${nt("index")} {
        if (index < uniforms.size) {
          let resRC = getCoordsFromIndex(index);
          let cVal = getC(${e});
          if (cVal >= 1.0) {
            setOutputAtIndex(index, getA(${t}));
          } else {
            setOutputAtIndex(index, getB(${t}));
          }
        }
      }
    `}};function Zye(e){let{inputs:t,backend:n}=e,{condition:s,t:r,e:a}=t,o=new Kye(s.shape.length,r.shape,r.shape.length);return n.runWebGPUProgram(o,[s,r,a],Hn(r.dtype,a.dtype))}var Yye={kernelName:Zl,backendName:"webgpu",kernelFunc:Zye},Jye=kn({opType:Oe.SIGMOID}),Qye={kernelName:ai,backendName:"webgpu",kernelFunc:Jye},eAe=kn({opType:Oe.SIN}),tAe={kernelName:ri,backendName:"webgpu",kernelFunc:eAe},nAe=kn({opType:Oe.SINH}),sAe={kernelName:Jl,backendName:"webgpu",kernelFunc:nAe},BT=qn({opType:Ye.SUB,cpuKernelImpl:O1e,supportsComplex:!0}),rAe={kernelName:ci,backendName:"webgpu",kernelFunc:BT};function aAe(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{dim:a}=s,o=v.parseAxisParam([a],r.shape),i=Ib({inputs:{x:r},backend:n,attrs:{reductionIndices:o,keepDims:!1}}),l=T.expandShapeToKeepDim(i.shape,o),u=He({inputs:{x:i},backend:n,attrs:{shape:l}}),c=BT({inputs:{a:r,b:u},backend:n}),p=FT({inputs:{x:c},backend:n}),d=Cb({inputs:{x:p},backend:n,attrs:{axis:o,keepDims:!1}}),h=He({inputs:{x:d},backend:n,attrs:{shape:l}}),f=LT({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 oAe={kernelName:li,backendName:"webgpu",kernelFunc:aAe},iAe=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=zT({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),p=T.getReshaped(c.shape,a,i,!1),d=T.getPermuted(p.length,a.length,!1),h=T.getReshapedPermuted(c.shape,a,i,!1),f=He({inputs:{x:c},backend:n,attrs:{shape:p}}),m=_a({inputs:{x:f},backend:n,attrs:{perm:d}}),g=He({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},lAe={kernelName:Ql,backendName:"webgpu",kernelFunc:iAe},uAe=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=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),this.rank=this.outputShape.length,this.shaderKey="tile"}getUserCode(){let e=cAe(this.rank,"uniforms.");return`
      ${nt("index")} {
        if (index < uniforms.size) {
          let resRC = getCoordsFromIndex(index);
          setOutputAtIndex(index, getA(${e}));
        }
      }
    `}};function cAe(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 WT(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=Ue(r.shape,r.dtype,u),p=M1e(c,a);return n.makeTensorInfo(p.shape,p.dtype,p.values)}let o=new uAe(r.shape,a);return n.runWebGPUProgram(o,[r],r.dtype)}var dAe={kernelName:Pa,backendName:"webgpu",kernelFunc:WT};function pAe(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}=T.calculateShapes(a,r,i),h=!1;if(a.dtype==="string"){let E=n.bufferSync(r),_=n.bufferSync(a),$=v.decodeString(n.readSync(o.dataId)[0]),R=_1e(E,_,i,d,c,u,l,p,$,h);return n.makeTensorInfo(i,R.dtype,R.values)}let f=[d/c,c],m=He({inputs:{x:r},backend:n,attrs:{shape:[u,l]}}),g=a.shape.length?He({inputs:{x:a},backend:n,attrs:{shape:[u,c]}}):sr({inputs:{x:a},backend:n}),y=g.dtype,x=n.makeTensorInfo([],y,v.makeZerosTypedArray(1,y)),A=He({inputs:{x:o},backend:n,attrs:{shape:Array(f.length).fill(1)}}),b=WT({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 bm([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 bm([u,c],l,m.shape.length,x.shape.length,p,f,y,h);n.runWebGPUProgram(E,[x,m],y,k,b)}{let E=new bm([u,c],l,m.shape.length,g.shape.length,p,f,y);n.runWebGPUProgram(E,[g,m],y,k,b)}}let C=He({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),C}var hAe={kernelName:rh,backendName:"webgpu",kernelFunc:pAe};function fAe(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=T.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=Sd({inputs:{x:r},backend:n,attrs:{begin:c,size:h}});return c[i]+=d,f})}var mAe={kernelName:eu,backendName:"webgpu",kernelFunc:fAe},gAe=kn({opType:Oe.SQRT}),yAe={kernelName:oi,backendName:"webgpu",kernelFunc:gAe},AAe={kernelName:Zc,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{x:n}=e,s=t,r=new Kh(n.shape,Oe.SQUARE);return s.runWebGPUProgram(r,[n],n.dtype)}},xAe=qn({opType:Ye.SQUARED_DIFFERENCE}),bAe={kernelName:ui,backendName:"webgpu",kernelFunc:xAe},vAe=class{constructor(e){this.variableNames=["x"],this.workPerThread=1,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]);let t=Mn(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`
       ${nt("index")} {
         if (index < uniforms.size) {
           let coords = getCoordsFromIndex(index);
           setOutputAtIndex(index, getX(${t}));
         }
       }
     `}};function wAe(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}=jt.sliceInfo(r.shape,a,o,i,l,u,c,p,d),w;if(m)w=He({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=jt.computeOutShape(x,A,b),C=Sd({inputs:{x:r},backend:n,attrs:{begin:x,size:k}});w=He({inputs:{x:C},backend:n,attrs:{shape:f}}),n.disposeData(C.dataId)}else if(n.shouldExecuteOnCPU([r])){let C=n.readSync(r.dataId),E=Ue(r.shape,r.dtype,C),_=P1e(h,E,b,x);w=n.makeTensorInfo(f,r.dtype,_.values)}else{let C=new vAe(h),E=[{type:"int32",data:x},{type:"int32",data:b}],_=n.runWebGPUProgram(C,[r],r.dtype,E);w=He({inputs:{x:_},backend:n,attrs:{shape:f}}),n.disposeData(_.dataId)}return w}var kAe={kernelName:tu,backendName:"webgpu",kernelFunc:wAe};function SAe(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]=F1e(d,h,r,a,o,i,l,u);return[n.makeTensorInfo([f.length],"string",f),n.makeTensorInfo(p.shape,"int32",m)]}var IAe={kernelName:Yc,backendName:"webgpu",kernelFunc:SAe},CAe=kn({opType:Oe.TANH}),TAe={kernelName:di,backendName:"webgpu",kernelFunc:CAe},NAe=class{constructor(e){this.variableNames=["x","indices"],this.workGroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),this.uniforms=`inputSize : i32, firstPass : i32, negativeInf : f32,
        dir : i32, inc : i32,`,this.shaderKey="swap"}getUserCode(){return`
        ${nt("index")} {
          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));
            }
          }
        }
      `}},EAe=class{constructor(e){this.variableNames=["x","indices"],this.workGroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=lt(this.outputShape),this.dispatch=je(this.dispatchLayout,this.outputShape,this.workGroupSize),this.uniforms="inputSize : i32, firstPass : i32, k : i32,",this.shaderKey="merge"}getUserCode(){return`
        ${nt("index")} {
          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 ec(e,t){t!==null&&e.disposeData(t.dataId)}function x6(e){let t=1;for(;t<e;)t*=2;return t}function RAe(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,C]=z1e(w,i,r.dtype,a,o);return[n.makeTensorInfo(k.shape,k.dtype,k.values),n.makeTensorInfo(C.shape,C.dtype,C.values)]}if(a===0)return i[i.length-1]=0,[n.makeTensorInfo(i,r.dtype,[]),n.makeTensorInfo(i,"int32",[])];if(l===1)return[r,vu({attrs:{shape:i,dtype:"int32",value:0},backend:n})];let c=v.sizeFromShape(i)/l,p=He({inputs:{x:r},attrs:{shape:[c,l]},backend:n}),d=x6(a),h=x6(l),f=null,m=()=>f===null?[p,p]:[p,f],g=(w,k,C)=>{let E=m(),_=new NAe(C),R=[{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]}],P=f;f=n.runWebGPUProgram(_,E,"int32",R),ec(n,P)};for(let w=1;w<d;w*=2){let k=w*2;for(let C=w;C>=1;C/=2)g(k,C,[c,h])}for(let w=h;w>d;w/=2){let k=m(),C=new EAe([c,w/2]),_=[{type:"int32",data:[l]},{type:"int32",data:[f===null?1:0]},{type:"int32",data:[d]}],$=f;f=n.runWebGPUProgram(C,k,"int32",_),ec(n,$);let R=d/2,P=R*2;for(let S=R;S>=1;S/=2)g(P,S,f.shape)}let y=f;f=Sd({inputs:{x:f},backend:n,attrs:{begin:0,size:[c,a]}}),ec(n,y);let x=OT({inputs:{x:p,indices:f},backend:n,attrs:{axis:1,batchDims:1}});ec(n,p);let A=i.slice(0,-1);A.push(a),y=f,f=He({inputs:{x:f},attrs:{shape:A},backend:n}),ec(n,y);let b=x;return x=He({inputs:{x},attrs:{shape:A},backend:n}),ec(n,b),[x,f]}var _Ae={kernelName:su,backendName:"webgpu",kernelFunc:RAe},DAe=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=lt(this.outputShape),this.dispatch=je(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;
          }

          ${nt("index")} {
            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 $Ae(e){let{inputs:t,backend:n,attrs:s}=e,{image:r,transforms:a}=t,{interpolation:o,fillMode:i,fillValue:l,outputShape:u}=s,[c,p,d,h]=r.shape,[f,m]=u!=null?u:[p,d],g=[c,f,m,h],y=new DAe(g),x=o==="nearest"?1:2,A;switch(i){case"constant":A=1;break;case"reflect":A=2;break;case"wrap":A=3;break;case"nearest":A=4;break;default:A=1;break}let b=[{type:"int32",data:[x]},{type:"int32",data:[A]},{type:"float32",data:[l]}];return n.runWebGPUProgram(y,[r,a],"float32",b)}var PAe={kernelName:ru,backendName:"webgpu",kernelFunc:$Ae};function FAe(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=Sd({inputs:{x:o},backend:n,attrs:{begin:d,size:h}}),y=He({inputs:{x:g},backend:n,attrs:{shape:u}});f[m]=y,p.push(g)}return p.forEach(m=>n.disposeData(m.dataId)),f}var OAe={kernelName:au,backendName:"webgpu",kernelFunc:FAe},MAe=[r1e,W1e,U1e,j1e,J1e,ege,nge,lge,cge,mge,xge,vge,Ige,o1e,Ege,Pge,Lge,Wge,Uge,jge,Xge,Zge,Qge,n3e,o3e,l3e,c3e,d3e,p3e,f3e,t1e,g3e,w3e,A3e,b3e,I3e,T3e,E3e,D3e,F3e,M3e,L3e,a1e,Tge,W3e,U3e,H3e,q3e,K3e,Y3e,Q3e,age,tye,sye,oge,aye,iye,uye,s3e,dye,hye,mye,gge,yye,xye,vye,kye,Iye,Tye,Eye,yge,Rye,Dye,Pye,Oye,n1e,Lye,Vye,Gye,jye,Xye,Yye,Qye,tAe,sAe,hge,kAe,IAe,oAe,lAe,hAe,mAe,yAe,AAe,bAe,rAe,r3e,TAe,dAe,_Ae,PAe,Z1e,OAe,gye];for(let e of MAe)rr(e);var zAe="3.20.0",LAe="3.20.0",BAe="3.20.0",WAe="3.20.0",VAe="3.20.0",UAe="3.20.0",GAe="3.20.0",Jh={tfjs:zAe,"tfjs-core":LAe,"tfjs-data":BAe,"tfjs-layers":WAe,"tfjs-converter":VAe,"tfjs-backend-webgl":UAe,"tfjs-backend-wasm":GAe};var VT=`
  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 UT=`
  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];
  }
`,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[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;
  }
`,HT=`
  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);
  }
`,jT=`
  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;
  }
`,qT=`
  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;
  }
`;var Tb=(e,t,n)=>{let s=new RegExp("\\b"+t+" \\w+ (\\w+)","ig");e.replace(s,(r,a)=>(n[a]=0,r))},Nb=class{constructor(t,n,s){fe(this,"uniform",{});fe(this,"attribute",{});fe(this,"gl");fe(this,"id");fe(this,"compile",(t,n)=>{let s=this.gl.createShader(n);return s?(this.gl.shaderSource(s,t),this.gl.compileShader(s),this.gl.getShaderParameter(s,this.gl.COMPILE_STATUS)?s:(ne(`filter: gl compile failed: ${this.gl.getShaderInfoLog(s)||"unknown"}`),null)):(ne("filter: could not create shader"),null)});this.gl=t;let r=this.compile(n,this.gl.VERTEX_SHADER),a=this.compile(s,this.gl.FRAGMENT_SHADER);if(this.id=this.gl.createProgram(),!(!r||!a)){if(!this.id){ne("filter: could not create webgl program");return}if(this.gl.attachShader(this.id,r),this.gl.attachShader(this.id,a),this.gl.linkProgram(this.id),!this.gl.getProgramParameter(this.id,this.gl.LINK_STATUS)){ne(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)||"unknown"}`);return}this.gl.useProgram(this.id),Tb(n,"attribute",this.attribute);for(let o in this.attribute)this.attribute[o]=this.gl.getAttribLocation(this.id,o);Tb(n,"uniform",this.uniform),Tb(s,"uniform",this.uniform);for(let o in this.uniform)this.uniform[o]=this.gl.getUniformLocation(this.id,o)}}};function XT(){let e=0,t=null,n=!1,s=-1,r=[null,null],a=[],o=null,i=null,l=vr(100,100),u={},c={INTERMEDIATE:1},p=l.getContext("webgl");if(!p){ne("filter: cannot get webgl context");return}this.gl=p;function d(x,A){if(!(x===l.width&&A===l.height)){if(l.width=x,l.height=A,!o){let b=new Float32Array([-1,-1,0,1,1,-1,1,1,-1,1,0,0,-1,1,0,0,1,-1,1,1,1,1,1,0]);o=p.createBuffer(),p.bindBuffer(p.ARRAY_BUFFER,o),p.bufferData(p.ARRAY_BUFFER,b,p.STATIC_DRAW),p.pixelStorei(p.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0)}p.viewport(0,0,l.width,l.height),r=[null,null]}}function h(x,A){let b=p.createFramebuffer();p.bindFramebuffer(p.FRAMEBUFFER,b);let w=p.createRenderbuffer();p.bindRenderbuffer(p.RENDERBUFFER,w);let k=p.createTexture();return p.bindTexture(p.TEXTURE_2D,k),p.texImage2D(p.TEXTURE_2D,0,p.RGBA,x,A,0,p.RGBA,p.UNSIGNED_BYTE,null),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_MAG_FILTER,p.LINEAR),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_MIN_FILTER,p.LINEAR),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_WRAP_S,p.CLAMP_TO_EDGE),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_WRAP_T,p.CLAMP_TO_EDGE),p.framebufferTexture2D(p.FRAMEBUFFER,p.COLOR_ATTACHMENT0,p.TEXTURE_2D,k,0),p.bindTexture(p.TEXTURE_2D,null),p.bindFramebuffer(p.FRAMEBUFFER,null),{fbo:b,texture:k}}function f(x){return r[x]=r[x]||h(l.width,l.height),r[x]}function m(x=0){if(!i)return;let A=null,b=null,w=!1;e===0?A=t:A=f(s).texture||null,e++,n&&!(x&c.INTERMEDIATE)?(b=null,w=e%2===0):(s=(s+1)%2,b=f(s).fbo||null),p.bindTexture(p.TEXTURE_2D,A),p.bindFramebuffer(p.FRAMEBUFFER,b),p.uniform1f(i.uniform.flipY,w?-1:1),p.drawArrays(p.TRIANGLES,0,6)}function g(x){if(u[x])return 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t={model:"",flags:[]};this.node&&this.platform.startsWith("linux"),this.cpu?this.cpu=t:Object.defineProperty(this,"cpu",{value:t})}},me=new Qh;var K2=class{constructor(){fe(this,"config");fe(this,"element");fe(this,"stream");fe(this,"start",async t=>{if(t!=null&&t.debug&&(this.config.debug=t==null?void 0:t.debug),t!=null&&t.crop&&(this.config.crop=t==null?void 0:t.crop),t!=null&&t.mode&&(this.config.mode=t==null?void 0:t.mode),t!=null&&t.width&&(this.config.width=t==null?void 0:t.width),t!=null&&t.height&&(this.config.height=t==null?void 0:t.height),t!=null&&t.element)if(typeof t.element=="string"){let r=document.getElementById(t.element);if(r&&r instanceof HTMLVideoElement)this.element=r;else{this.config.debug&&ne("webcam","cannot get dom element",t.element);return}}else if(t.element instanceof HTMLVideoElement)this.element=t.element;else{this.config.debug&&ne("webcam","unknown dom element",t.element);return}else this.element=document.createElement("video");let n={audio:!1,video:{facingMode:this.config.mode==="front"?"user":"environment",resizeMode:this.config.crop?"crop-and-scale":"none",width:{ideal:this.config.width>0?this.config.width:window.innerWidth},height:{ideal:this.config.height>0?this.config.height:window.innerHeight}}};if(this.element.addEventListener("play",()=>{this.config.debug&&ne("webcam","play")}),this.element.addEventListener("pause",()=>{this.config.debug&&ne("webcam","pause")}),this.element.addEventListener("click",async()=>{!this.element||!this.stream||(this.element.paused?await this.element.play():this.element.pause())}),!(navigator!=null&&navigator.mediaDevices)){this.config.debug&&ne("webcam","no devices");return}try{this.stream=await navigator.mediaDevices.getUserMedia(n)}catch(r){ne("webcam",r);return}if(!this.stream){this.config.debug&&ne("webcam","no stream");return}this.element.srcObject=this.stream,await new Promise(r=>{this.element?this.element.onloadeddata=()=>r(!0):r(!1)}),await 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Ze={tf255:255,tf1:1,tf2:2,tf05:.5,tf127:127.5,rgb:[.2989,.587,.114]};function nN(){Ze.tf255=Te(255,"float32"),Ze.tf1=Te(1,"float32"),Ze.tf2=Te(2,"float32"),Ze.tf05=Te(.5,"float32"),Ze.tf127=Te(127.5,"float32"),Ze.rgb=Ot([.2989,.587,.114],"float32")}var Cd=e=>[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])],Y2=e=>[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2,1],J2=(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],Q2=(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],aN=(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}},Mb=(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=Ce.cropAndResize(t,[a],[0],n),i=ye(o,Ze.tf255);return Q(o),i},e1=(e,t)=>{let n=Y2(e),s=Cd(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}},t1=e=>{let t=Y2(e),n=Cd(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}},oN=e=>{let 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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=Le(n.boxes,[r[p],0],[1,-1]),h.slice=Le(n.batch,[r[p],pN-1],[1,-1]),h.squeeze=Ke(h.slice),h.landmarks=V(h.squeeze,[pN,-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=aN(m,[(e.shape[2]||0)/Si,(e.shape[1]||0)/Si]),y=e1(g,t.face.scale||xxe),x=t1(y);a.push(x),Object.keys(h).forEach(A=>Q(h[A]))}}return Object.keys(n).forEach(p=>Q(n[p])),a}var n1={};xa(n1,{connected:()=>Wb,kpt:()=>Bb});var 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yN=224,vxe,wxe=5,s1=[8,16,32,32,32];function AN(){let e=[],t=0;for(;t<wxe;){let n=0,s=t;for(;s<s1.length&&s1[s]===s1[t];)n+=2,s++;let r=s1[t],a=Math.ceil(yN/r),o=Math.ceil(yN/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}vxe={x:Ot(e.map(n=>n.x)),y:Ot(e.map(n=>n.y))}}function za(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 xN(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 r1(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 wN={initial:!0},Xn={detector:null,landmarks:null},Nd={detector:[224,224],landmarks:[256,256]},Vb=Number.MAX_SAFE_INTEGER,Sxe={landmarks:["ld_3d","activation_segmentation","activation_heatmap","world_3d","output_poseflag"],detector:[]},o1=null,nf,Ii=[[0,0],[0,0],[0,0],[0,0]],bN=0,vN=e=>1-1/(1+Math.exp(e));async function kN(e){var t;if(wN.initial&&(Xn.detector=null),!Xn.detector&&e.body.detector&&e.body.detector.modelPath){Xn.detector=await Ve(e.body.detector.modelPath);let n=(t=Xn.detector)!=null&&t.executor?Object.values(Xn.detector.modelSignature.inputs):void 0;Nd.detector[0]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[1].size):0,Nd.detector[1]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[2].size):0}else e.debug&&Xn.detector&&ne("cached model:",Xn.detector.modelUrl);return AN(),Xn.detector}async function SN(e){var t;if(wN.initial&&(Xn.landmarks=null),Xn.landmarks)e.debug&&ne("cached 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Nxe(e,t,n){var f,m;if(!((f=Xn.landmarks)!=null&&f.executor))return null;let s={};[s.ld,s.segmentation,s.heatmap,s.world,s.poseflag]=(m=Xn.landmarks)==null?void 0:m.execute(e,Sxe.landmarks);let r=(await s.poseflag.data())[0],a=await s.ld.data(),o=await s.world.data();Object.keys(s).forEach(g=>Q(s[g]));let i=[],l=5;for(let g=0;g<a.length/l;g++){let y=vN(a[l*g+3]),x=vN(a[l*g+4]),A=Math.trunc(100*y*x*r)/100,b=[a[l*g+0]/Nd.landmarks[0],a[l*g+1]/Nd.landmarks[1],a[l*g+2]+0],w=[Math.trunc(n[0]*b[0]),Math.trunc(n[1]*b[1]),b[2]],k=[o[l*g+0],o[l*g+1],o[l*g+2]+0];i.push({part:Bb[g],positionRaw:b,position:w,distance:k,score:A})}if(r<(t.body.minConfidence||0))return null;Txe(i);let u=Cxe(i,n),c=u.map(g=>g.position),p=za(c,[n[0],n[1]]),d={};for(let[g,y]of Object.entries(Wb)){let x=[];for(let A=0;A<y.length-1;A++){let 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qb=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","bodyCenter","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"],Xb={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var In,EN=0,gs={id:0,keypoints:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,annotations:{}},Kb=Number.MAX_SAFE_INTEGER;async function RN(e){return me.initial&&(In=null),In?e.debug&&ne("cached model:",In.modelUrl):In=await Ve(e.body.modelPath),In}async function Rxe(e,t){let[n,s]=e.shape,r=V(e,[s*n]),a=xn(r,0),o=(await a.data())[0];if(o>t){let i=Ms(r,0),l=pu(i,n),u=(await l.data())[0],c=ye(i,n),p=(await c.data())[0];return Q([r,a,i,l,c]),[u,p,o]}return Q([r,a]),[0,0,o]}async function 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d=p.slice(0,_d.numCoordinates*3),{rawCoords:h,iris:f}=MN(d,s,r,!0),m=p.slice(_d.numCoordinates*3),{rawCoords:g,iris:y}=MN(m,o,i,!1),x=$xe(e);Math.abs(x)<30?(u1(e,h,"left",null),u1(e,g,"right",null)):x<1?u1(e,h,"left",["EyeUpper0","EyeLower0"]):u1(e,g,"right",["EyeUpper0","EyeLower0"]);let A=zN(e,f,"left"),b=zN(e,y,"right");return e.concat(A).concat(b)}var 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Ti(e){let t=e.map(n=>n[0]);return t.push(e[e.length-1][1]),t}var Vxe={lips:Ti(Pxe),leftEye:Ti(Fxe),leftEyebrow:Ti(Oxe),leftIris:Ti(Mxe),rightEye:Ti(zxe),rightEyebrow:Ti(Lxe),rightIris:Ti(Bxe),faceOval:Ti(Wxe)},Uxe=Object.entries(Vxe).map(([e,t])=>t.map(n=>[n,e])).flat(),$Se=new 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function GN(e,t){var l,u,c,p,d,h,f,m,g,y;if(!(Lt!=null&&Lt.executor))return[];let n=(((l=t.face.detector)==null?void 0:l.skipTime)||0)>ue()-ha.timestamp,s=ha.skipped<(((u=t.face.detector)==null?void 0:u.skipFrames)||0);!t.skipAllowed||!n||!s||ha.boxes.length===0?(ha.boxes=await mN(e,t),ha.timestamp=ue(),ha.skipped=0):ha.skipped++;let r=[],a=[],o=0,i=rf;for(let x=0;x<ha.boxes.length;x++){let A=ha.boxes[x],b=0,w,k={id:o++,mesh:[],meshRaw:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,boxScore:0,faceScore:0,annotations:{}};if([b,w,k.tensor]=cN((c=t.face.detector)==null?void 0:c.rotation,A,e,(p=t.face.mesh)!=null&&p.enabled?rf:Td()),t.filter.equalization){let C=k.tensor?await G2(k.tensor):void 0;Q(k.tensor),C&&(k.tensor=C)}if(k.boxScore=Math.round(100*A.confidence)/100,(d=t.face.mesh)!=null&&d.enabled)if(!Lt)t.debug&&ne("face mesh detection requested, but model is not loaded");else{if(((h=t.face.attention)==null?void 0:h.enabled)&&!me.kernels.includes("atan2"))return t.face.attention.enabled=!1,Q(k.tensor),r;let C=Lt.execute(k.tensor),_=await C.find($=>$.shape[$.shape.length-1]===1).data();if(k.faceScore=Math.round(100*_[0])/100,k.faceScore<(((f=t.face.detector)==null?void 0:f.minConfidence)||1)){if(A.confidence=k.faceScore,t.face.mesh.keepInvalid){k.box=J2(A,e),k.boxRaw=Q2(A,e),k.score=k.boxScore,k.mesh=A.landmarks.map($=>[(A.startPoint[0]+A.endPoint[0])/2+(A.endPoint[0]+A.startPoint[0])*$[0]/Td(),(A.startPoint[1]+A.endPoint[1])/2+(A.endPoint[1]+A.startPoint[1])*$[1]/Td()]),k.meshRaw=k.mesh.map($=>[$[0]/(e.shape[2]||1),$[1]/(e.shape[1]||1),($[2]||0)/i]);for(let $ of Object.keys(wu))k.annotations[$]=[k.mesh[wu[$]]]}}else{let $=C.find(M=>M.shape[M.shape.length-1]===1404),R=V($,[-1,3]),P=await R.array();Q(R),(m=t.face.attention)!=null&&m.enabled?P=await UN(P,C):(g=t.face.iris)!=null&&g.enabled&&(P=await BN(P,k.tensor,rf)),k.mesh=uN(P,A,b,w,rf),k.meshRaw=k.mesh.map(M=>[M[0]/(e.shape[2]||0),M[1]/(e.shape[1]||0),(M[2]||0)/i]);for(let M of Object.keys(kr))k.annotations[M]=kr[M].map(L=>k.mesh[L]);k.score=k.faceScore;let S={...dN(k.mesh,A),confidence:A.confidence,landmarks:A.landmarks};k.box=J2(S,e),k.boxRaw=Q2(S,e),a.push(S)}Q(C)}else{k.box=J2(A,e),k.boxRaw=Q2(A,e),k.score=k.boxScore,k.mesh=A.landmarks.map(C=>[(A.startPoint[0]+A.endPoint[0])/2+(A.endPoint[0]+A.startPoint[0])*C[0]/Td(),(A.startPoint[1]+A.endPoint[1])/2+(A.endPoint[1]+A.startPoint[1])*C[1]/Td()]),k.meshRaw=k.mesh.map(C=>[C[0]/(e.shape[2]||0),C[1]/(e.shape[1]||0),(C[2]||0)/i]);for(let C of Object.keys(wu))k.annotations[C]=[k.mesh[wu[C]]]}k.score>(((y=t.face.detector)==null?void 0:y.minConfidence)||1)?r.push(k):Q(k.tensor)}return ha.boxes=a,r}async function HN(e){var t,n,s,r,a,o;return me.initial&&(Lt=null),((t=e.face.attention)==null?void 0:t.enabled)&&(Lt==null?void 0:Lt.signature)&&Object.keys(((n=Lt==null?void 0:Lt.signature)==null?void 0:n.outputs)||{}).length<6&&(Lt=null),Lt?e.debug&&ne("cached model:",Lt.modelUrl):(s=e.face.attention)!=null&&s.enabled?Lt=await Ve(e.face.attention.modelPath):Lt=await Ve((r=e.face.mesh)==null?void 0:r.modelPath),rf=Lt.executor&&((a=Lt==null?void 0:Lt.inputs)==null?void 0:a[0].shape)?(o=Lt==null?void 0:Lt.inputs)==null?void 0:o[0].shape[2]:256,Lt}var jN=ku,qN=ef;var Kn,Ni=[],XN=0,KN=0,n4=Number.MAX_SAFE_INTEGER;async function ZN(e){var t;return me.initial&&(Kn=null),Kn?e.debug&&ne("cached model:",Kn.modelUrl):Kn=await Ve((t=e.face.description)==null?void 0:t.modelPath),Kn}function s4(e){let t=e.image||e.tensor||e;if(!(Kn!=null&&Kn.inputs[0].shape))return t;let n=Ce.resizeBilinear(t,[Kn.inputs[0].shape[2],Kn.inputs[0].shape[1]],!1),s=z(n,Ze.tf255);return Q(n),s}async function r4(e,t,n,s){var i,l,u,c;let r={age:0,gender:"unknown",genderScore:0,descriptor:[]};if(!(Kn!=null&&Kn.executor))return r;let a=n4<(((i=t.face.description)==null?void 0:i.skipFrames)||0),o=(((l=t.face.description)==null?void 0:l.skipTime)||0)>ue()-XN;return 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Object.keys(n).forEach(r=>Q(n[r])),s}normalizeLandmarks(t,n){let s={};s.reshape=V(t,[-1,7,2]),s.div=ye(s.reshape,this.inputSizeTensor),s.landmarks=de(s.div,this.anchors[n]?this.anchors[n]:0);let r=z(s.landmarks,this.inputSizeTensor);return Object.keys(s).forEach(a=>Q(s[a])),r}async predict(t,n){var i;let s={};s.resize=Ce.resizeBilinear(t,[this.inputSize,this.inputSize]),s.div=ye(s.resize,Ze.tf127),s.image=Ae(s.div,Ze.tf1),s.batched=this.model.execute(s.image),s.predictions=Ke(s.batched),s.slice=Le(s.predictions,[0,0],[-1,1]),s.sigmoid=On(s.slice),s.scores=Ke(s.sigmoid);let r=await s.scores.data();s.boxes=Le(s.predictions,[0,1],[-1,4]),s.norm=this.normalizeBoxes(s.boxes),s.nms=await Ce.nonMaxSuppressionAsync(s.norm,s.scores,3*(((i=n.hand)==null?void 0:i.maxDetected)||1),n.hand.iouThreshold,n.hand.minConfidence);let a=await s.nms.array(),o=[];for(let l of a){let u={};u.box=Le(s.norm,[l,0],[1,-1]),u.slice=Le(s.predictions,[l,5],[1,14]),u.norm=this.normalizeLandmarks(u.slice,l),u.palmLandmarks=V(u.norm,[-1,2]);let c=await u.box.data(),p=c.slice(0,2),d=c.slice(2,4),h=await u.palmLandmarks.array(),f={startPoint:p,endPoint:d,palmLandmarks:h,confidence:r[l]},m=rE(f,[(t.shape[2]||1)/this.inputSize,(t.shape[1]||0)/this.inputSize]);o.push(m),Object.keys(u).forEach(g=>Q(u[g]))}return Object.keys(s).forEach(l=>Q(s[l])),o}};var Yxe=5,uE=1.65,cE=[0,5,9,13,17,1,2],Jxe=0,Qxe=2,dE=0,f1=class{constructor(t,n){fe(this,"handDetector");fe(this,"handPoseModel");fe(this,"inputSize");fe(this,"storedBoxes");fe(this,"skipped");fe(this,"detectedHands");var s,r,a;this.handDetector=t,this.handPoseModel=n,this.inputSize=((a=(r=(s=this.handPoseModel)==null?void 0:s.inputs)==null?void 0:r[0].shape)==null?void 0:a[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=>c4([...a,1],n)),r=this.calculateLandmarksBoundingBox(s);return d1(p1(r),Yxe)}getBoxForHandLandmarks(t){let n=this.calculateLandmarksBoundingBox(t),s=d1(p1(n),uE);s.palmLandmarks=[];for(let r=0;r<cE.length;r++)s.palmLandmarks.push(t[cE[r]].slice(0,2));return s}transformRawCoords(t,n,s,r){let a=c1(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=u4(s,[0,0]),u=i.map(h=>[...c4(h,l),h[2]]),c=oE(r),p=[...af(n),1],d=[Ei(p,c[0]),Ei(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()-dE,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?aE(u.palmLandmarks[Jxe],u.palmLandmarks[Qxe]):0,p=af(u),d=[p[0]/t.shape[2],p[1]/t.shape[1]],h=n.hand.rotation&&me.kernels.includes("rotatewithoffset")?Ce.rotateWithOffset(t,c,0,d):t.clone(),f=u4(-c,p),m=s?this.getBoxForPalmLandmarks(u.palmLandmarks,f):u,g=sE(m,h,[this.inputSize,this.inputSize]),y=ye(g,Ze.tf255);Q(g),Q(h);let[x,A]=this.handPoseModel.execute(y);dE=ue(),Q(y);let b=(await x.data())[0];if(Q(x),b>=n.hand.minConfidence/4){let w=V(A,[-1,3]),k=await w.array();Q(A),Q(w);let C=this.transformRawCoords(k,m,c,f),E=this.getBoxForHandLandmarks(C);this.storedBoxes[l]={...E,confidence:b};let _={landmarks:C,confidence:b,boxConfidence:u.confidence,fingerConfidence:b,box:{topLeft:E.startPoint,bottomRight:E.endPoint}};i.push(_)}else this.storedBoxes[l]=null;Q(A)}else{let c=d1(p1(u),uE),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 ys={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=>ys.nameMapping[e],getPoints:e=>ys.pointsMapping[e]},_i={none:0,half:1,full:2,nameMapping:{0:"none",1:"half",2:"full"},getName:e=>_i.nameMapping[e]},Zt={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=>Zt.nameMapping[e]},Ri=class{constructor(t){fe(this,"name");fe(this,"curls");fe(this,"directions");fe(this,"weights");fe(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:qr,index:La,middle:Ba,ring:Nu,pinky:Eu}=ys,{none:Xr,half:tbe,full:Kr}=_i,{verticalUp:Dd,verticalDown:eIe,horizontalLeft:d4,horizontalRight:nbe,diagonalUpRight:sbe,diagonalUpLeft:$d,diagonalDownRight:tIe,diagonalDownLeft:nIe}=Zt,Di=new Ri("thumbs up");Di.curl(qr,Xr,1);Di.direction(qr,Dd,1);Di.direction(qr,$d,.25);Di.direction(qr,sbe,.25);for(let e of[ys.index,ys.middle,ys.ring,ys.pinky])Di.curl(e,Kr,1),Di.direction(e,d4,1),Di.direction(e,nbe,1);var hn=new Ri("victory");hn.curl(qr,tbe,.5);hn.curl(qr,Xr,.5);hn.direction(qr,Dd,1);hn.direction(qr,$d,1);hn.curl(La,Xr,1);hn.direction(La,Dd,.75);hn.direction(La,$d,1);hn.curl(Ba,Xr,1);hn.direction(Ba,Dd,1);hn.direction(Ba,$d,.75);hn.curl(Nu,Kr,1);hn.direction(Nu,Dd,.2);hn.direction(Nu,$d,1);hn.direction(Nu,d4,.2);hn.curl(Eu,Kr,1);hn.direction(Eu,Dd,.2);hn.direction(Eu,$d,1);hn.direction(Eu,d4,.2);hn.weight(La,2);hn.weight(Ba,2);var $i=new Ri("point");$i.curl(qr,Kr,1);$i.curl(La,Xr,.5);$i.curl(Ba,Kr,.5);$i.curl(Nu,Kr,.5);$i.curl(Eu,Kr,.5);$i.weight(La,2);$i.weight(Ba,2);var Pi=new Ri("middle finger");Pi.curl(qr,Xr,1);Pi.curl(La,Kr,.5);Pi.curl(Ba,Kr,.5);Pi.curl(Nu,Kr,.5);Pi.curl(Eu,Kr,.5);Pi.weight(La,2);Pi.weight(Ba,2);var Pd=new Ri("open palm");Pd.curl(qr,Xr,.75);Pd.curl(La,Xr,.75);Pd.curl(Ba,Xr,.75);Pd.curl(Nu,Xr,.75);Pd.curl(Eu,Xr,.75);var pE=[Di,hn,$i,Pi,Pd];var rbe=.7,Ru={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 hE(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 mE(e,t){if(!e||!t)return[0,0];let n=hE(e[0],e[1],t[0],t[1]);if(e.length===2)return n;let s=hE(e[1],e[2],t[1],t[2]);return[n,s]}function fE(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 abe(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>Ru.NO_CURL_START_LIMIT?y=_i.none:g>Ru.HALF_CURL_START_LIMIT?y=_i.half:y=_i.full,y}function gE(e,t,n,s){let r;return s===Math.abs(e)?e>0?r=Zt.horizontalLeft:r=Zt.horizontalRight:s===Math.abs(t)?t>0?r=Zt.horizontalLeft:r=Zt.horizontalRight:n>0?r=Zt.horizontalLeft:r=Zt.horizontalRight,r}function yE(e,t,n,s){let r;return s===Math.abs(e)?e<0?r=Zt.verticalDown:r=Zt.verticalUp:s===Math.abs(t)?t<0?r=Zt.verticalDown:r=Zt.verticalUp:n<0?r=Zt.verticalDown:r=Zt.verticalUp,r}function obe(e,t,n,s,r,a,o,i){let l,u=yE(e,t,n,s),c=gE(r,a,o,i);return u===Zt.verticalUp?c===Zt.horizontalLeft?l=Zt.diagonalUpLeft:l=Zt.diagonalUpRight:c===Zt.horizontalLeft?l=Zt.diagonalDownLeft:l=Zt.diagonalDownRight,l}function ibe(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+=Ru.DISTANCE_VOTE_POWER:m>.66?h+=Ru.DISTANCE_VOTE_POWER:f+=Ru.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],C=n[1];A===g?(k=n[0],C=n[1]):A===x&&(b=t[0],w=t[1]);let $=mE([b,w],[k,C]),R=fE($,Ru.TOTAL_ANGLE_VOTE_POWER);d+=R[0],h+=R[1],f+=R[2];for(let S of s){let M=fE(S,Ru.SINGLE_ANGLE_VOTE_POWER);d+=M[0],h+=M[1],f+=M[2]}let P;return d===Math.max(d,h,f)?P=yE(l,i,u,p):f===Math.max(h,f)?P=gE(a,r,o,c):P=obe(l,i,u,p,a,r,o,c),P}function AE(e){let t=[],n=[],s=[],r=[];if(!e)return{curls:s,directions:r};for(let a of ys.all){let o=ys.getPoints(a),i=[],l=[];for(let u of o){let c=e[u[0]],p=e[u[1]],d=mE(c,p),h=d[0],f=d[1];i.push(h),l.push(f)}t.push(i),n.push(l)}for(let a of ys.all){let o=a===ys.thumb?1:0,i=ys.getPoints(a),l=e[i[o][0]],u=e[i[o+1][1]],c=e[i[3][1]],p=abe(l,u,c),d=ibe(l,u,c,t[a].slice(o));s[a]=p,r[a]=d}return{curls:s,directions:r}}function m1(e){if(!e||e.length===0)return null;let t=AE(e),n={};for(let s of ys.all)n[ys.getName(s)]={curl:_i.getName(t.curls[s]),direction:Zt.getName(t.directions[s])};return n}function xE(e){let t=[];if(!e||e.length===0)return t;let n=AE(e);for(let s of pE){let r=s.matchAgainst(n.curls,n.directions);r>=rbe&&t.push({name:s.name,confidence:r})}return t}var bE={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]},_u,Du,vE;async function h4(e,t){let n=await vE.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(bE))a[c]=bE[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=m1(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 f4(e){var n,s;me.initial&&(_u=null,Du=null),!_u||!Du?[_u,Du]=await Promise.all([e.hand.enabled?Ve((n=e.hand.detector)==null?void 0:n.modelPath):null,e.hand.landmarks?Ve((s=e.hand.skeleton)==null?void 0:s.modelPath):null]):(e.debug&&ne("cached model:",_u.modelUrl),e.debug&&ne("cached model:",Du.modelUrl));let t=_u?new h1(_u):void 0;return t&&Du&&(vE=new f1(t,Du)),[_u,Du]}var nn=[null,null],lbe=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],Fi=[[0,0],[0,0]],ube=["hand","fist","pinch","point","face","tip","pinchtip"],kE=4,SE=1.6,cbe=512,dbe=1.4,g1=Number.MAX_SAFE_INTEGER,m4=0,Wa=[0,0],tn={boxes:[],hands:[]},IE={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 CE(e){var t;if(me.initial&&(nn[0]=null),nn[0])e.debug&&ne("cached model:",nn[0].modelUrl);else{y1(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),nn[0]=await Ve((t=e.hand.detector)==null?void 0:t.modelPath);let n=nn[0].executor?Object.values(nn[0].modelSignature.inputs):void 0;Fi[0][0]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[1].size):0,Fi[0][1]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[2].size):0}return nn[0]}async function TE(e){var t;if(me.initial&&(nn[1]=null),nn[1])e.debug&&ne("cached model:",nn[1].modelUrl);else{nn[1]=await Ve((t=e.hand.skeleton)==null?void 0:t.modelPath);let n=nn[1].executor?Object.values(nn[1].modelSignature.inputs):void 0;Fi[1][0]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[1].size):0,Fi[1][1]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[2].size):0}return nn[1]}async function pbe(e,t){let n=[];if(!e||!nn[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,cbe),o=Math.round(a*r/8)*8;s.resize=Ce.resizeBilinear(e,[a,o]),s.cast=ge(s.resize,"int32"),[s.rawScores,s.rawBoxes]=await nn[0].executeAsync(s.cast,lbe),s.boxes=Ke(s.rawBoxes,[0,2]),s.scores=Ke(s.rawScores,[0]);let i=wn(s.scores,1);Q(i[kE]),i.splice(kE,1),s.filtered=un(i,1),Q(i),s.max=xn(s.filtered,1),s.argmax=Ms(s.filtered,1);let l=0;s.nms=await Ce.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=Le(s.boxes,d,1),f=await h.data();Q(h);let m=[f[1],f[0],f[3]-f[1],f[2]-f[0]],g=r1(m,dbe),y=[Math.trunc(m[0]*Wa[0]),Math.trunc(m[1]*Wa[1]),Math.trunc(m[2]*Wa[0]),Math.trunc(m[3]*Wa[1])],x=c[d],A=ube[p[d]],b={id:l++,score:x,box:y,boxRaw:g,label:A};n.push(b)}return Object.keys(s).forEach(d=>Q(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 g4(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&&nn[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=Ce.cropAndResize(e,[a],[0],[Fi[1][0],Fi[1][1]],"bilinear"),r.div=ye(r.crop,Ze.tf255),[r.score,r.keypoints]=nn[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=V(r.keypoints,[-1,3]);let c=(await r.reshaped.array()).map(p=>[p[0]/Fi[1][1],p[1]/Fi[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=>[Wa[0]*(p[0]+t.boxRaw[0]),Wa[1]*(p[1]+t.boxRaw[1]),p[2]||0]),s.landmarks=m1(s.keypoints);for(let p of Object.keys(IE))s.annotations[p]=IE[p].map(d=>s.landmarks&&s.keypoints[d]?s.keypoints[d]:null)}Object.keys(r).forEach(l=>Q(r[l]))}return s}async function y4(e,t){var r,a;if(!((r=nn[0])!=null&&r.executor)||!((a=nn[1])!=null&&a.executor)||!nn[0].inputs[0].shape||!nn[1].inputs[0].shape)return[];Wa=[e.shape[2]||0,e.shape[1]||0],g1++;let n=(t.hand.skipTime||0)>ue()-m4,s=g1<(t.hand.skipFrames||0);return t.skipAllowed&&n&&s?tn.hands:new Promise(async o=>{let i=3*(t.hand.skipTime||0)>ue()-m4,l=g1<3*(t.hand.skipFrames||0);t.skipAllowed&&tn.hands.length===t.hand.maxDetected?tn.hands=await Promise.all(tn.boxes.map(c=>g4(e,c,t))):t.skipAllowed&&i&&l&&tn.hands.length>0?tn.hands=await Promise.all(tn.boxes.map(c=>g4(e,c,t))):(tn.boxes=await pbe(e,t),m4=ue(),tn.hands=await Promise.all(tn.boxes.map(c=>g4(e,c,t))),g1=0);let u=[...tn.boxes];if(tn.boxes.length=0,t.cacheSensitivity>0)for(let c=0;c<tn.hands.length;c++){let 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n=(t.object.skipTime||0)>ue()-YE,s=_4<(t.object.skipFrames||0);return t.skipAllowed&&n&&s&&w1.length>0?(_4++,w1):(_4=0,!me.kernels.includes("mod")||!me.kernels.includes("sparsetodense")?w1:new Promise(async r=>{let a=[e.shape[2]||0,e.shape[1]||0],o=Ce.resizeBilinear(e,[S1,S1],!1),i=ye(o,Ze.tf255),l=at(i,[0,3,1,2]),u;t.object.enabled&&(u=Ir.execute(l)),YE=ue();let c=await gbe(u,a,t);w1=c,Q([o,i,l,...u]),r(c)}))}var uf=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],ybe=uf.length,lf=uf.reduce((e,t,n)=>(e[t]=n,e),{}),Abe=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],OIe=Abe.map(([e,t])=>[lf[e],lf[t]]),eR=[["nose","leftEye"],["leftEye","leftEar"],["nose","rightEye"],["rightEye","rightEar"],["nose","leftShoulder"],["leftShoulder","leftElbow"],["leftElbow","leftWrist"],["leftShoulder","leftHip"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["nose","rightShoulder"],["rightShoulder","rightElbow"],["rightElbow","rightWrist"],["rightShoulder","rightHip"],["rightHip","rightKnee"],["rightKnee","rightAnkle"]];function 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u=Math.min(u,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],l)+Math.PI/2)%Math.PI,strength:u}},NR=(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,C,E]=m,_,$,R;return A<1?A>-1?(R=Math.asin(A),$=Math.atan2(-k,g),_=Math.atan2(-w,b)):(R=-Math.PI/2,$=-Math.atan2(C,E),_=0):(R=Math.PI/2,$=Math.atan2(C,E),_=0),Number.isNaN(_)&&(_=0),Number.isNaN($)&&($=0),Number.isNaN(R)&&(R=0),{pitch:2*-_,yaw:2*-$,roll:2*-R}},o=e.meshRaw;if(!o||o.length<300)return{angle:{pitch:0,yaw:0,roll:0},matrix:[1,0,0,0,1,0,0,0,1],gaze:{bearing:0,strength:0}};let i=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,l=[o[10],o[152],o[234],o[454]].map(m=>[m[0]*t[0]/i,m[1]*t[1]/i,m[2]]),u=n(s(l[1],l[0])),c=n(s(l[3],l[2])),p=n(r(c,u));c=r(u,p);let d=[c[0],c[1],c[2],u[0],u[1],u[2],p[0],p[1],p[2]],h=a(d),f=o.length===478?Bbe(e):{bearing:0,strength:0};return{angle:h,matrix:d,gaze:f}};var sv=async(e,t)=>{var f,m,g,y,x,A,b,w,k,C,E,_,$,R,P,S,M,L,U,K,q,Z,J,te,le,ae,pe,ce,xe;let n=ue(),s,r,a,o,i,l,u,c,p,d=[];e.state="run:face";let h=await GN(t,e.config);if(e.performance.face=me.perfadd?(e.performance.face||0)+Math.trunc(ue()-n):Math.trunc(ue()-n),!t.shape||t.shape.length!==4)return[];if(!h)return[];for(let ie=0;ie<h.length;ie++){if(e.analyze("Get Face"),!h[ie].tensor||h[ie].tensor.isDisposedInternal){ne("Face object is disposed:",h[ie].tensor);continue}if((f=e.config.face.detector)!=null&&f.mask){let ut=await TR(h[ie]);Q(h[ie].tensor),ut&&(h[ie].tensor=ut)}let _e=h[ie].mesh&&h[ie].mesh.length>200?NR(h[ie],[t.shape[2],t.shape[1]]):null;e.analyze("Start 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j4(h[ie].tensor||Xe([]),e.config,ie,h.length):null,e.performance.ssrnet=Math.trunc(ue()-n)),e.analyze("End SSRNet:"),e.analyze("Start MobileFaceNet:"),e.config.async?i=(R=e.config.face.mobilefacenet)!=null&&R.enabled?S4(h[ie].tensor||Xe([]),e.config,ie,h.length):null:(e.state="run:mobilefacenet",n=ue(),i=(P=e.config.face.mobilefacenet)!=null&&P.enabled?await S4(h[ie].tensor||Xe([]),e.config,ie,h.length):null,e.performance.mobilefacenet=Math.trunc(ue()-n)),e.analyze("End MobileFaceNet:"),e.analyze("Start InsightFace:"),e.config.async?l=(S=e.config.face.insightface)!=null&&S.enabled?x4(h[ie].tensor||Xe([]),e.config,ie,h.length):null:(e.state="run:mobilefacenet",n=ue(),l=(M=e.config.face.insightface)!=null&&M.enabled?await x4(h[ie].tensor||Xe([]),e.config,ie,h.length):null,e.performance.mobilefacenet=Math.trunc(ue()-n)),e.analyze("End InsightFace:"),e.analyze("Start Description:"),e.config.async?p=r4(h[ie].tensor||Xe([]),e.config,ie,h.length):(e.state="run:description",n=ue(),p=await r4(h[ie].tensor||Xe([]),e.config,ie,h.length),e.performance.description=me.perfadd?(e.performance.description||0)+Math.trunc(ue()-n):Math.trunc(ue()-n)),e.analyze("End Description:"),e.config.async&&([s,a,o,i,l,p,r,u,c]=await Promise.all([s,a,o,i,l,p,r,u,c])),e.analyze("Finish Face:"),((L=e.config.face.ssrnet)==null?void 0:L.enabled)&&s&&a&&(p={...p,age:s.age,gender:a.gender,genderScore:a.genderScore}),((U=e.config.face.gear)==null?void 0:U.enabled)&&r&&(p={...p,age:r.age,gender:r.gender,genderScore:r.genderScore,race:r.race}),((K=e.config.face.mobilefacenet)==null?void 0:K.enabled)&&i&&(p.descriptor=i),((q=e.config.face.insightface)==null?void 0:q.enabled)&&l&&(p.descriptor=l),(Z=e.config.face.iris)!=null&&Z.enabled;let De=((le=(te=(J=h[ie])==null?void 0:J.annotations)==null?void 0:te.leftEyeIris)==null?void 0:le[0])&&((ce=(pe=(ae=h[ie])==null?void 0:ae.annotations)==null?void 0:pe.rightEyeIris)==null?void 0:ce[0])&&h[ie].annotations.leftEyeIris.length>0&&h[ie].annotations.rightEyeIris.length>0&&h[ie].annotations.leftEyeIris[0]!==null&&h[ie].annotations.rightEyeIris[0]!==null?Math.max(Math.abs(h[ie].annotations.leftEyeIris[3][0]-h[ie].annotations.leftEyeIris[1][0]),Math.abs(h[ie].annotations.rightEyeIris[4][1]-h[ie].annotations.rightEyeIris[2][1]))/t.shape[2]:0,Ge=(xe=e.config.face.detector)!=null&&xe.return?Ke(h[ie].tensor):null;Q(h[ie].tensor),h[ie].tensor&&delete h[ie].tensor;let ze={...h[ie],id:ie};p.age&&(ze.age=p.age),p.gender&&(ze.gender=p.gender),p.genderScore&&(ze.genderScore=p.genderScore),p.descriptor&&(ze.embedding=p.descriptor),p.race&&(ze.race=p.race),o&&(ze.emotion=o),u&&(ze.real=u),c&&(ze.live=c),De&&De!==0&&(ze.iris=Math.trunc(500/De/11.7)/100),_e&&(ze.rotation=_e),Ge&&(ze.tensor=Ge),d.push(ze),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),d};var ER=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},RR=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},_R=e=>{var n,s,r,a;if(!e)return[];let t=[];for(let o=0;o<e.length;o++){if(!((s=(n=e[o].annotations)==null?void 0:n.leftEyeIris)!=null&&s[0])||!((a=(r=e[o].annotations)==null?void 0:r.rightEyeIris)!=null&&a[0]))continue;let i=e[o].annotations.leftEyeIris[3][0]-e[o].annotations.leftEyeIris[1][0],l=e[o].annotations.leftEyeIris[4][1]-e[o].annotations.leftEyeIris[2][1],u=Math.abs(i*l),c=e[o].annotations.rightEyeIris[3][0]-e[o].annotations.rightEyeIris[1][0],p=e[o].annotations.rightEyeIris[4][1]-e[o].annotations.rightEyeIris[2][1],d=Math.abs(c*p),h=!1;Math.abs(u-d)/Math.max(u,d)<.25&&(h=!0,t.push({iris:o,gesture:"facing center"}));let m=Math.abs(e[o].mesh[263][0]-e[o].annotations.leftEyeIris[0][0])/e[o].box[2],g=Math.abs(e[o].mesh[33][0]-e[o].annotations.rightEyeIris[0][0])/e[o].box[2];(m>.06||g>.06)&&(h=!1),m>g?m>.05&&t.push({iris:o,gesture:"looking right"}):g>.05&&t.push({iris:o,gesture:"looking left"});let y=Math.abs(e[o].mesh[145][1]-e[o].annotations.rightEyeIris[0][1])/e[o].box[3],x=Math.abs(e[o].mesh[374][1]-e[o].annotations.leftEyeIris[0][1])/e[o].box[3];(x<.01||y<.01||x>.022||y>.022)&&(h=!1),(x<.01||y<.01)&&t.push({iris:o,gesture:"looking down"}),(x>.022||y>.022)&&t.push({iris:o,gesture:"looking 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s=Date.now()-e.timestamp,r=s<1e3?8-Math.log(s+1):1;if(e.canvas&&(Re.canvas=e.canvas),e.error&&(Re.error=e.error),!Re.body||e.body.length!==Re.body.length)Re.body=JSON.parse(JSON.stringify(e.body));else for(let S=0;S<e.body.length;S++){let M=e.body[S].box.map((Z,J)=>((r-1)*Re.body[S].box[J]+Z)/r),L=e.body[S].boxRaw.map((Z,J)=>((r-1)*Re.body[S].boxRaw[J]+Z)/r),U=e.body[S].keypoints.map((Z,J)=>{var te,le,ae,pe,ce,xe,ie,_e,De;return{score:Z.score,part:Z.part,position:[Re.body[S].keypoints[J]?((r-1)*(Re.body[S].keypoints[J].position[0]||0)+(Z.position[0]||0))/r:Z.position[0],Re.body[S].keypoints[J]?((r-1)*(Re.body[S].keypoints[J].position[1]||0)+(Z.position[1]||0))/r:Z.position[1],Re.body[S].keypoints[J]?((r-1)*(Re.body[S].keypoints[J].position[2]||0)+(Z.position[2]||0))/r:Z.position[2]],positionRaw:[Re.body[S].keypoints[J]?((r-1)*(Re.body[S].keypoints[J].positionRaw[0]||0)+(Z.positionRaw[0]||0))/r:Z.positionRaw[0],Re.body[S].keypoints[J]?((r-1)*(Re.body[S].keypoints[J].positionRaw[1]||0)+(Z.positionRaw[1]||0))/r:Z.positionRaw[1],Re.body[S].keypoints[J]?((r-1)*(Re.body[S].keypoints[J].positionRaw[2]||0)+(Z.positionRaw[2]||0))/r:Z.positionRaw[2]],distance:[Re.body[S].keypoints[J]?((r-1)*(((te=Re.body[S].keypoints[J].distance)==null?void 0:te[0])||0)+(((le=Z.distance)==null?void 0:le[0])||0))/r:(ae=Z.distance)==null?void 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S=0;S<e.face.length;S++){let M=e.face[S].box.map((U,K)=>((r-1)*Re.face[S].box[K]+U)/r),L=e.face[S].boxRaw.map((U,K)=>((r-1)*Re.face[S].boxRaw[K]+U)/r);if(e.face[S].rotation){let U={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};U.matrix=(d=e.face[S].rotation)==null?void 0:d.matrix,U.angle={roll:((r-1)*(((f=(h=Re.face[S].rotation)==null?void 0:h.angle)==null?void 0:f.roll)||0)+(((g=(m=e.face[S].rotation)==null?void 0:m.angle)==null?void 0:g.roll)||0))/r,yaw:((r-1)*(((x=(y=Re.face[S].rotation)==null?void 0:y.angle)==null?void 0:x.yaw)||0)+(((b=(A=e.face[S].rotation)==null?void 0:A.angle)==null?void 0:b.yaw)||0))/r,pitch:((r-1)*(((k=(w=Re.face[S].rotation)==null?void 0:w.angle)==null?void 0:k.pitch)||0)+(((E=(C=e.face[S].rotation)==null?void 0:C.angle)==null?void 0:E.pitch)||0))/r},U.gaze={bearing:((r-1)*(((_=Re.face[S].rotation)==null?void 0:_.gaze.bearing)||0)+((($=e.face[S].rotation)==null?void 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2Q==`;async function jbe(e){let t=(r,a="application/octet-stream")=>fetch(`data:${a};base64,${r}`).then(o=>o.blob()),n,s;switch(e.config.warmup){case"face":n=await t(D1);break;case"body":case"full":n=await t($1);break;default:n=null}if(n){let r=await createImageBitmap(n);s=await e.detect(r,e.config),r.close()}return s}async function qbe(e){return new Promise(t=>{let n;switch(e.config.warmup){case"face":n="data:image/jpeg;base64,"+D1;break;case"full":case"body":n="data:image/jpeg;base64,"+$1;break;default:n=""}let s;if(typeof Image!="undefined")s=new Image;else if(me.Image)s=new me.Image;else return;s.onload=async()=>{let r=vr(s.naturalWidth,s.naturalHeight);if(!r)ne("Warmup: Canvas not found"),t(void 0);else{let a=r.getContext("2d");a&&a.drawImage(s,0,0);let o=await e.image(r),i=o.tensor?await e.detect(o.tensor,e.config):void 0;t(i)}},n?s.src=n:t(void 0)})}async function Xbe(e){let t=r=>Buffer.from(r,"base64"),n;e.config.warmup==="face"?n=t(D1):n=t($1);let s;if("node"in Qe&&dn()==="tensorflow"){let r=(void 0).decodeJpeg(n),a=Ft(r,0);e.tf.dispose(r),s=await e.detect(a,e.config),e.tf.dispose(a)}else e.config.debug&&ne("Warmup tfjs-node not loaded");return s}async function Kbe(e){let t;return typeof createImageBitmap=="function"?t=await jbe(e):typeof Image!="undefined"||me.Canvas!==void 0?t=await qbe(e):t=await Xbe(e),t}async function Zbe(e){var i,l,u,c;if(!H().flagRegistry.ENGINE_COMPILE_ONLY)return;let t=dn(),n=Us();if(t!=="webgl"&&t!=="humangl"||!(n!=null&&n.checkCompileCompletion))return;H().set("ENGINE_COMPILE_ONLY",!0);let s=Qt().state.numTensors,r=[];for(let[p,d]of Object.entries(e.models).filter(([h,f])=>h!==null&&f!==null)){let h=(l=(i=d.inputs)==null?void 0:i[0])!=null&&l.shape?[...d.inputs[0].shape]:[1,64,64,3],f=(c=(u=d.inputs)==null?void 0:u[0])!=null&&c.dtype?d.inputs[0].dtype:"float32";for(let g=0;g<h.length;g++)h[g]===-1&&(h[g]=g===0?1:64);let m=Gt(h,f);try{let g=d.execute(m);r.push(p),Array.isArray(g)?g.forEach(y=>Q(y)):Q(g)}catch(g){e.config.debug&&ne("compile fail model:",p)}Q(m)}let a=await n.checkCompileCompletionAsync();n.getUniformLocations(),e.config.debug&&ne("compile pass:",{models:r,kernels:a.length}),H().set("ENGINE_COMPILE_ONLY",!1);let o=Qt().state.numTensors;o-s>0&&ne("tensor leak:",o-s)}async function OR(e,t){await df(e,!1);let n=ue();return e.state="warmup",t&&(e.config=Vt(e.config,t)),!e.config.warmup||e.config.warmup.length===0||e.config.warmup==="none"?{face:[],body:[],hand:[],gesture:[],object:[],performance:e.performance,timestamp:ue(),persons:[],error:null}:new Promise(async s=>{await Od.load(e),await Zbe(e);let r=await Kbe(e),a=ue();e.config.debug&&ne("warmup",e.config.warmup,Math.round(a-n),"ms"),e.emit("warmup"),s(r)})}var Ud,hf,ff,P1,Oi,lv=class{constructor(t){fe(this,"version");fe(this,"config");fe(this,"result");fe(this,"state");fe(this,"process");fe(this,"tf");fe(this,"env");fe(this,"draw");fe(this,"models");fe(this,"events");fe(this,"faceTriangulation");fe(this,"faceUVMap");fe(this,"performance");Ku(this,Ud,void 0);Ku(this,hf,void 0);Ku(this,ff,void 0);fe(this,"gl");fe(this,"analyze",(...t)=>{if(!Zr(this,hf))return;let n=this.tf.engine().state.numTensors,s=Zr(this,Ud);sp(this,Ud,n);let r=n-s;r!==0&&ne(...t,r)});Ku(this,P1,t=>{if(!Zr(this,ff))return null;if(!t)return"input is not defined";if(this.env.node&&!(t instanceof it))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});fe(this,"similarity",av);fe(this,"distance",pf);fe(this,"match",ov);fe(this,"webcam",new K2);fe(this,"emit",t=>{var n;(n=this.events)!=null&&n.dispatchEvent&&this.events.dispatchEvent(new Event(t))});Ku(this,Oi,{});this.env=me;let n=(Jh.tfjs||lA).replace(/-(.*)/,"");Xa.wasmPath=`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${n}/dist/`,Xa.modelBasePath=me.browser?"../models/":"file://models/",Xa.backend=me.browser?"webgl":"tensorflow",this.version=_b,Object.defineProperty(this,"version",{value:_b}),this.config=JSON.parse(JSON.stringify(Xa)),Object.seal(this.config),this.config.cacheModels=typeof indexedDB!="undefined",t&&(this.config=Vt(this.config,t)),YT(this.config),this.tf=Qe,this.state="idle",sp(this,Ud,0),sp(this,hf,!1),sp(this,ff,!1),this.performance={},this.events=typeof EventTarget!="undefined"?new EventTarget:void 0,this.models=new cf,this.draw={options:Jn,canvas:(r,a)=>Q4(r,a),face:(r,a,o)=>Md(r,a,o),body:(r,a,o)=>zd(r,a,o),hand:(r,a,o)=>Ld(r,a,o),gesture:(r,a,o)=>Wd(r,a,o),object:(r,a,o)=>Bd(r,a,o),person:(r,a,o)=>J4(r,a,o),all:(r,a,o)=>ev(r,a,o)},this.result={face:[],body:[],hand:[],gesture:[],object:[],performance:{},timestamp:0,persons:[],error:null},this.process={tensor:null,canvas:null},this.faceTriangulation=jN,this.faceUVMap=qN,this.gl=Dt,R1(this,null,""),this.emit("create"),(this.config.debug||this.env.browser)&&ne(`version: ${this.version}`),this.config.debug&&ne(`tfjs version: ${this.tf.version["tfjs-core"]}`);let s=JSON.parse(JSON.stringify(this.env));delete s.kernels,delete s.initial,delete s.perfadd,this.config.debug&&ne("environment:",s)}reset(){let t=this.config.backend;this.config=JSON.parse(JSON.stringify(Xa)),this.config.backend=t,Eb(),me.initial=!0}validate(t){let n=g3(Xa,t||this.config);return n.length===0&&(this.config=Vt(this.config,t)),n}check(){return _1(this)}now(){return ue()}image(t,n=!0){return q2(t,this.config,n)}async segmentation(t,n){var a,o,i;if(n&&(this.config=Vt(this.config,n)),!this.config.segmentation.enabled)return null;let s=await q2(t,this.config);if(!s.tensor)return null;let r=null;return(a=this.config.segmentation.modelPath)!=null&&a.includes("rvm")&&(r=await cR(s.tensor,this.config)),(o=this.config.segmentation.modelPath)!=null&&o.includes("meet")&&(r=await zE(s.tensor,this.config)),(i=this.config.segmentation.modelPath)!=null&&i.includes("selfie")&&(r=await pR(s.tensor,this.config)),Q(s.tensor),r}enhance(t){return s4(t)}compare(t,n){return ZT(this.config,t,n)}async init(){await df(this,!0),await this.tf.ready(),Eb()}async load(t){this.state="load";let n=ue(),s=Object.values(this.models).filter(o=>o).length;t&&(this.config=Vt(this.config,t)),this.env.initial&&(await df(this,!1)||ne("error: backend check failed"),await fh(),this.env.browser&&(this.config.debug&&ne("configuration:",this.config),this.config.debug&&ne("tf flags:",this.tf.ENV.flags))),await X4(this),this.env.initial&&this.config.debug&&ne("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),this.env.initial=!1,Object.values(this.models).filter(o=>o).length!==s&&(_1(this),this.emit("load"));let a=Math.trunc(ue()-n);a>(this.performance.loadModels||0)&&(this.performance.loadModels=this.env.perfadd?(this.performance.loadModels||0)+a:a)}next(t=this.result){return $R(t,this.config)}getModelStats(){return q4(this)}async warmup(t){let n=ue(),s=await OR(this,t),r=ue();return this.performance.warmup=Math.trunc(r-n),s}async profile(t,n){let s=await this.tf.profile(()=>this.detect(t,n)),r={},a=0;for(let i of s.kernels)r[i.name]?r[i.name]+=i.kernelTimeMs:r[i.name]=i.kernelTimeMs,a+=i.kernelTimeMs;let o=[];Object.entries(r).forEach(i=>o.push({kernel:i[0],time:i[1],perc:0}));for(let i of o)i.perc=Math.round(1e3*i.time/a)/1e3,i.time=Math.round(1e3*i.time)/1e3;return o.sort((i,l)=>l.time-i.time),o.length=20,o}async detect(t,n){return this.state="detect",new Promise(async s=>{var g,y,x,A,b,w,k,C,E,_,$,R,P,S,M,L,U,K,q,Z,J;this.state="config";let r;this.config=Vt(this.config,n),this.state="check";let a=Zr(this,P1).call(this,t);a&&(ne(a,t),this.emit("error"),s({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:ue(),persons:[],error:a}));let o=ue();await this.load(),r=ue(),this.state="image";let i=await q2(t,this.config);if(this.process=i,this.performance.inputProcess=this.env.perfadd?(this.performance.inputProcess||0)+Math.trunc(ue()-r):Math.trunc(ue()-r),this.analyze("Get Image:"),!i.tensor){this.config.debug&&ne("could not convert input to tensor"),this.emit("error"),s({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:ue(),persons:[],error:"could not convert input to tensor"});return}this.emit("image"),r=ue(),this.config.skipAllowed=await KT(this.config,i.tensor),this.performance.totalFrames||(this.performance.totalFrames=0),this.performance.cachedFrames||(this.performance.cachedFrames=0),this.performance.totalFrames++,this.config.skipAllowed&&this.performance.cachedFrames++,this.performance.cacheCheck=this.env.perfadd?(this.performance.cacheCheck||0)+Math.trunc(ue()-r):Math.trunc(ue()-r),this.analyze("Check Changed:");let l=[],u=[],c=[],p=[];this.state="detect:face",this.config.async?(l=this.config.face.enabled?sv(this,i.tensor):[],this.performance.face&&delete this.performance.face):(r=ue(),l=this.config.face.enabled?await sv(this,i.tensor):[],this.performance.face=this.env.perfadd?(this.performance.face||0)+Math.trunc(ue()-r):Math.trunc(ue()-r)),this.config.async&&(this.config.body.maxDetected===-1||this.config.hand.maxDetected===-1)&&(l=await l),this.analyze("Start Body:"),this.state="detect:body";let d=this.config.body.maxDetected===-1?Vt(this.config,{body:{maxDetected:this.config.face.enabled?1*l.length:1}}):this.config;this.config.async?((g=this.config.body.modelPath)!=null&&g.includes("posenet")?u=this.config.body.enabled?M4(i.tensor,d):[]:(y=this.config.body.modelPath)!=null&&y.includes("blazepose")?u=this.config.body.enabled?Ub(i.tensor,d):[]:(x=this.config.body.modelPath)!=null&&x.includes("efficientpose")?u=this.config.body.enabled?Zb(i.tensor,d):[]:(A=this.config.body.modelPath)!=null&&A.includes("movenet")&&(u=this.config.body.enabled?R4(i.tensor,d):[]),this.performance.body&&delete this.performance.body):(r=ue(),(b=this.config.body.modelPath)!=null&&b.includes("posenet")?u=this.config.body.enabled?await M4(i.tensor,d):[]:(w=this.config.body.modelPath)!=null&&w.includes("blazepose")?u=this.config.body.enabled?await Ub(i.tensor,d):[]:(k=this.config.body.modelPath)!=null&&k.includes("efficientpose")?u=this.config.body.enabled?await Zb(i.tensor,d):[]:(C=this.config.body.modelPath)!=null&&C.includes("movenet")&&(u=this.config.body.enabled?await R4(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?Vt(this.config,{hand:{maxDetected:this.config.face.enabled?2*l.length:1}}):this.config;this.config.async?((_=(E=this.config.hand.detector)==null?void 0:E.modelPath)!=null&&_.includes("handdetect")?c=this.config.hand.enabled?h4(i.tensor,h):[]:(R=($=this.config.hand.detector)==null?void 0:$.modelPath)!=null&&R.includes("handtrack")&&(c=this.config.hand.enabled?y4(i.tensor,h):[]),this.performance.hand&&delete this.performance.hand):(r=ue(),(S=(P=this.config.hand.detector)==null?void 0:P.modelPath)!=null&&S.includes("handdetect")?c=this.config.hand.enabled?await h4(i.tensor,h):[]:(L=(M=this.config.hand.detector)==null?void 0:M.modelPath)!=null&&L.includes("handtrack")&&(c=this.config.hand.enabled?await y4(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?((U=this.config.object.modelPath)!=null&&U.includes("nanodet")?p=this.config.object.enabled?D4(i.tensor,this.config):[]:(K=this.config.object.modelPath)!=null&&K.includes("centernet")&&(p=this.config.object.enabled?jb(i.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(r=ue(),(q=this.config.object.modelPath)!=null&&q.includes("nanodet")?p=this.config.object.enabled?await D4(i.tensor,this.config):[]:(Z=this.config.object.modelPath)!=null&&Z.includes("centernet")&&(p=this.config.object.enabled?await jb(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=[...RR(l),...ER(u),...DR(c),..._R(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=((J=this.process.tensor)==null?void 0:J.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 FR(l,u,c,f,m)}},Q(i.tensor),this.emit("detect"),this.state="idle",s(this.result)})}async sleep(t){return new Promise(n=>{setTimeout(n,t)})}async video(t,n=!0,s=0){n?(Zr(this,Oi)[t.id]||(this.config.debug&&ne("video start",t.id),Zr(this,Oi)[t.id]=!0),!t.paused&&Zr(this,Oi)[t.id]&&t.readyState>=2&&await this.detect(t),s>0&&await this.sleep(s),Zr(this,Oi)[t.id]&&requestAnimationFrame(()=>this.video(t,n,s))):(this.config.debug&&ne("video stop",t.id),Zr(this,Oi)[t.id]=!1)}};Ud=new WeakMap,hf=new WeakMap,ff=new WeakMap,P1=new WeakMap,Oi=new WeakMap;return F_(Jbe);})();