/*
      Human library
      homepage: <https://github.com/vladmandic/human>
      author: <https://github.com/vladmandic>'
    */
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to tidy()");t=e}else{if(typeof e!="string"&&!(e instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if(typeof t!="function")throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");n=e}let r;return this.scopedRun(()=>this.startScope(n),()=>this.endScope(r),()=>(r=t(),r instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),r))}scopedRun(e,t,n){e();try{let r=n();return t(),r}catch(r){throw t(),r}}nextTensorId(){return N2.nextTensorId++}nextVariableId(){return N2.nextVariableId++}clone(e){let t=U.runKernel(c2,{x:e}),n={x:e},r=a=>({x:()=>{let o="float32",i={x:a},l={dtype:o};return U.runKernel(u2,i,l)}}),s=[];return this.addTapeNode(this.state.activeScope.name,n,[t],r,s,{}),t}runKernel(e,t,n){if(!(rp(e,this.backendName)!=null))throw new Error(`Kernel '${e}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,n){let r=this.backend.numDataIds(),s=0;n.forEach(i=>{s+=i.dtype==="complex64"?3:1});let a=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],o=r-t-s-a;if(o>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${o} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[],r=this.isTapeOn(),s=this.state.numBytes,a=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let o;this.backendName==null&&this.backend;let i,l=T2(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(T2(e)){let{kernelName:p,inputs:f,attrs:m}=e;this.backendName==null&&this.backend;let g=rp(p,this.backendName);L(g!=null,()=>`Cannot find registered kernel '${p}' for backend '${this.backendName}'`),o=()=>{let y=this.backend.numDataIds();i=g.kernelFunc({inputs:f,attrs:m,backend:this.backend});let A=Array.isArray(i)?i:[i];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(p,y,A);let x=A.map(b=>{if(b.rank!=null)return b;let{dataId:v,shape:w,dtype:I}=b;return this.makeTensorFromDataId(v,w,I)});if(r){let b=this.getTensorsForGradient(p,f,x);n=this.saveTensorsForBackwardMode(b)}return x}}else{let{forwardFunc:p}=e,f=m=>{!r||(n=m.map(g=>this.keep(this.clone(g))))};o=()=>{let m=this.backend.numDataIds();i=this.tidy(()=>p(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,d=T2(e)?null:e.backwardsFunc,h;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=o():(h=this.profiler.profileKernel(l,u,()=>o()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(h),t=h.outputs)}),r&&this.addTapeNode(l,u,t,d,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-s,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-a,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map(p=>u[p]!=null?u[p].shape:null),outputShapes:t.map(p=>p.shape),kernelTimeMs:h.timeMs,extraInfo:h.extraInfo}),Array.isArray(i)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(n=>this.keep(this.clone(n)))}getTensorsForGradient(e,t,n){let r=g2(e);if(r!=null){let s=r.inputsToSave||[],a=r.outputsToSave||[],o;r.saveAllInputs?(L(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),o=Object.keys(t).map(l=>t[l])):o=s.map(l=>t[l]);let i=n.filter((l,u)=>a[u]);return o.concat(i)}return[]}makeTensor(e,t,n,r){if(e==null)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",r=r||this.backend;let s=e;n==="string"&&Ia(e[0])&&(s=e.map(i=>Qu(i)));let a=r.write(s,t,n),o=new Tt(t,n,a,this.nextTensorId());if(this.trackTensor(o,r),n==="string"){let i=this.state.tensorInfo.get(a),l=j3(s);this.state.numBytes+=l-i.bytes,i.bytes=l}return o}makeTensorFromDataId(e,t,n,r){n=n||"float32";let s=new Tt(t,n,e,this.nextTensorId());return this.trackTensor(s,r),s}makeVariable(e,t=!0,n,r){n=n||this.nextVariableId().toString(),r!=null&&r!==e.dtype&&(e=e.cast(r));let s=new rc(e,t,n,this.nextTensorId());if(this.state.registeredVariables[s.name]!=null)throw new Error(`Variable with name ${s.name} was already registered`);return this.state.registeredVariables[s.name]=s,this.incRef(s,this.backend),s}trackTensor(e,t){this.state.numTensors++,e.dtype==="string"&&this.state.numStringTensors++;let n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*n2(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 rc||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*n2(e.dtype);this.state.numBytes-=n}t.backend.disposeData(e.dataId)&&this.removeDataId(e.dataId,t.backend)}disposeVariables(){for(let e in this.state.registeredVariables){let t=this.state.registeredVariables[e];this.disposeVariable(t)}}disposeVariable(e){this.disposeTensor(e),this.state.registeredVariables[e.name]!=null&&delete this.state.registeredVariables[e.name]}memory(){let e=this.backend.memory();return e.numTensors=this.state.numTensors,e.numDataBuffers=this.state.numDataBuffers,e.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(e.unreliable=!0,e.reasons==null&&(e.reasons=[]),e.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),e}async profile(e){this.state.profiling=!0;let t=this.state.numBytes,n=this.state.numTensors;this.state.activeProfile.kernels=[],this.state.activeProfile.result=await e(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max(...this.state.activeProfile.kernels.map(r=>r.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-n;for(let r of this.state.activeProfile.kernels)r.kernelTimeMs=await r.kernelTimeMs,r.extraInfo=await r.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>0&&this.state.kernelDepth===0}addTapeNode(e,t,n,r,s,a){let o={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:n,saved:s},i=g2(e);i!=null&&(r=i.gradFunc),r!=null&&(o.gradient=l=>(l=l.map((u,c)=>{if(u==null){let d=n[c],h=np(d.size,d.dtype);return this.makeTensor(h,d.shape,d.dtype)}return u}),r(l.length>1?l:l[0],s,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=S2(e),n=new Set(t.map(s=>s.id));for(let s=0;s<this.state.activeScope.track.length;s++){let a=this.state.activeScope.track[s];!a.kept&&!n.has(a.id)&&a.dispose()}let r=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(s=>{!s.kept&&s.scopeId===r.id&&this.track(s)})}gradients(e,t,n,r=!1){if(L(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 s=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));L(s instanceof Tt,()=>"The result y returned by f() must be a tensor.");let a=FD(this.state.activeTape,t,s);if(!r&&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[s.id]=n==null?qD(s.shape):n,MD(o,a,l=>this.tidy(l),KD);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:s,grads:i}})}customGrad(e){return L(Sa(e),()=>"The f passed in customGrad(f) must be a function."),(...t)=>{L(t.every(o=>o instanceof Tt),()=>"The args passed in customGrad(f)(x1, x2,...) must all be tensors");let n,r={};t.forEach((o,i)=>{r[i]=o});let s=(o,i)=>(n=e(...t,i),L(n.value instanceof Tt,()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"),L(Sa(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];L(u.length===t.length,()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...)."),L(u.every(d=>d instanceof Tt),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors.");let c={};return u.forEach((d,h)=>{c[h]=()=>d}),c};return this.runKernelFunc({forwardFunc:s,backwardsFunc:a,inputs:r})}}readSync(e){return this.state.tensorInfo.get(e).backend.readSync(e)}read(e){return this.state.tensorInfo.get(e).backend.read(e)}async time(e){let t=Ju(),n=await this.backend.time(e);return n.wallMs=Ju()-t,n}track(e){return this.state.activeScope!=null&&(e.scopeId=this.state.activeScope.id,this.state.activeScope.track.push(e)),e}get registeredVariables(){return this.state.registeredVariables}reset(){this.pendingBackendInitId++,this.state.dispose(),this.ENV.reset(),this.state=new H7;for(let e in this.registry)this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e];this.backendName=null,this.backendInstance=null,this.pendingBackendInit=null}},C2=N2;C2.nextTensorId=0;C2.nextVariableId=0;function qD(e){let t=r2(Jt(e),"float32");return U.makeTensor(t,e,"float32")}function G7(){let e=J3();if(e._tfengine==null){let t=new Y3(e);e._tfengine=new C2(t)}return nD(e._tfengine.ENV),LD(()=>e._tfengine),e._tfengine}var U=G7();function KD(e,t){let n={a:e,b:t};return U.runKernel(l2,n)}var j7={};De(j7,{isBrowser:()=>q7,isMobile:()=>ZD});function XD(){return typeof navigator!="undefined"&&navigator!=null}function ZD(e){if(e||XD()){if(e||(e=navigator),e.product==="ReactNative")return!0;let t=e.userAgent||e.vendor||window.opera;return/(android|bb\d+|meego).+mobile|avantgo|bada\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\/|plucker|pocket|psp|series(4|6)0|symbian|treo|up\.(browser|link)|vodafone|wap|windows ce|xda|xiino/i.test(t)||/1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s\-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|\-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw\-(n|u)|c55\/|capi|ccwa|cdm\-|cell|chtm|cldc|cmd\-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc\-s|devi|dica|dmob|do(c|p)o|ds(12|\-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(\-|_)|g1 u|g560|gene|gf\-5|g\-mo|go(\.w|od)|gr(ad|un)|haie|hcit|hd\-(m|p|t)|hei\-|hi(pt|ta)|hp( i|ip)|hs\-c|ht(c(\-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i\-(20|go|ma)|i230|iac( |\-|\/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |\/)|klon|kpt |kwc\-|kyo(c|k)|le(no|xi)|lg( g|\/(k|l|u)|50|54|\-[a-w])|libw|lynx|m1\-w|m3ga|m50\/|ma(te|ui|xo)|mc(01|21|ca)|m\-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(\-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)\-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|\-([1-8]|c))|phil|pire|pl(ay|uc)|pn\-2|po(ck|rt|se)|prox|psio|pt\-g|qa\-a|qc(07|12|21|32|60|\-[2-7]|i\-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55\/|sa(ge|ma|mm|ms|ny|va)|sc(01|h\-|oo|p\-)|sdk\/|se(c(\-|0|1)|47|mc|nd|ri)|sgh\-|shar|sie(\-|m)|sk\-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h\-|v\-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl\-|tdg\-|tel(i|m)|tim\-|t\-mo|to(pl|sh)|ts(70|m\-|m3|m5)|tx\-9|up(\.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|\-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(\-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas\-|your|zeto|zte\-/i.test(t.substr(0,4))}return!1}function q7(){return typeof window!="undefined"&&window.document!=null||typeof WorkerGlobalScope!="undefined"}var es=ct();es.registerFlag("DEBUG",()=>!1,e=>{e&&console.warn("Debugging mode is ON. The output of every math call will be downloaded to CPU and checked for NaNs. This significantly impacts performance.")});es.registerFlag("IS_BROWSER",()=>q7());es.registerFlag("IS_NODE",()=>typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined");es.registerFlag("IS_CHROME",()=>typeof navigator!="undefined"&&navigator!=null&&navigator.userAgent!=null&&/Chrome/.test(navigator.userAgent)&&/Google Inc/.test(navigator.vendor));es.registerFlag("PROD",()=>!1);es.registerFlag("TENSORLIKE_CHECK_SHAPE_CONSISTENCY",()=>es.getBool("DEBUG"));es.registerFlag("DEPRECATION_WARNINGS_ENABLED",()=>!0);es.registerFlag("IS_TEST",()=>!1);es.registerFlag("CHECK_COMPUTATION_FOR_ERRORS",()=>!0);es.registerFlag("WRAP_TO_IMAGEBITMAP",()=>!1);function Ss(e,t){let n=e;if(Cn(e))return t==="string"?[]:[e.length];if(!Array.isArray(e))return[];let r=[];for(;Array.isArray(n)||Cn(n)&&t!=="string";)r.push(n.length),n=n[0];return Array.isArray(e)&&ct().getBool("TENSORLIKE_CHECK_SHAPE_CONSISTENCY")&&K7(e,r,[]),r}function K7(e,t,n){if(n=n||[],!Array.isArray(e)&&!Cn(e)){L(t.length===0,()=>`Element arr[${n.join("][")}] is a primitive, but should be an array/TypedArray of ${t[0]} elements`);return}L(t.length>0,()=>`Element arr[${n.join("][")}] should be a primitive, but is an array of ${e.length} elements`),L(e.length===t[0],()=>`Element arr[${n.join("][")}] should have ${t[0]} elements, but has ${e.length} elements`);let r=t.slice(1);for(let s=0;s<e.length;++s)K7(e[s],r,n.concat(s))}function X7(e,t,n,r){if(e!=="string_or_numeric"){if(e==null)throw new Error("Expected dtype cannot be null.");if(e!=="numeric"&&e!==t||e==="numeric"&&t==="string")throw new Error(`Argument '${n}' passed to '${r}' must be ${e} tensor, but got ${t} tensor`)}}function P(e,t,n,r="numeric"){if(e instanceof Tt)return X7(r,e.dtype,t,n),e;let s=ep(e);if(s!=="string"&&["bool","int32","float32"].indexOf(r)>=0&&(s=r),X7(r,s,t,n),e==null||!Cn(e)&&!Array.isArray(e)&&typeof e!="number"&&typeof e!="boolean"&&typeof e!="string"){let l=e==null?"null":e.constructor.name;throw new Error(`Argument '${t}' passed to '${n}' must be a Tensor or TensorLike, but got '${l}'`)}let a=Ss(e,s);!Cn(e)&&!Array.isArray(e)&&(e=[e]);let i=s!=="string"?op(e,s):po(e,[],!0);return U.makeTensor(i,a,s)}function sc(e,t,n,r="numeric"){if(!Array.isArray(e))throw new Error(`Argument ${t} passed to ${n} must be a \`Tensor[]\` or \`TensorLike[]\``);return e.map((a,o)=>P(a,`${t}[${o}]`,n,r))}var Z7="__op";function H(e){let t=Object.keys(e);if(t.length!==1)throw new Error(`Please provide an object with a single key (operation name) mapping to a function. 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Got strides ${n} and dilations '${o}'`);let i=a,l=!1;a.rank===3&&(l=!0,i=ue(a,[1,a.shape[0],a.shape[1],a.shape[2]])),L(i.rank===4,()=>`Error in avgPool: x must be rank 4 but got rank ${i.rank}.`),s!=null&&L(Xn(r),()=>`Error in avgPool: pad must be an integer when using, dimRoundingMode ${s} but got pad ${r}.`);let u={x:i},c={filterSize:t,strides:n,pad:r,dimRoundingMode:s},d=U.runKernel(hv,u,c);return d=Pt(d,a.dtype),l?ue(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var Bk=H({avgPool_:hO});function pO(e,t,n,r,s,a="NDHWC"){let o=P(e,"x","avgPool3d","float32"),i=o,l=!1;o.rank===4&&(l=!0,i=ue(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),L(i.rank===5,()=>`Error in avgPool3d: x must be rank 5 but got rank ${i.rank}.`),L(a==="NDHWC",()=>`Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of ${a}`),s!=null&&L(Xn(r),()=>`Error in avgPool3d: pad must be an integer when using, dimRoundingMode ${s} but got pad ${r}.`);let u={x:i},c={filterSize:t,strides:n,pad:r,dimRoundingMode:s,dataFormat:a},d=U.runKernel(pv,u,c);return d=Pt(d,i.dtype),l?ue(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var fO=H({avgPool3d_:pO});function mO(e,t=0){L(e.length>=1,()=>"Pass at least one tensor to concat");let n=sc(e,"tensors","concat","string_or_numeric");if(n[0].dtype==="complex64"&&n.forEach(a=>{if(a.dtype!=="complex64")throw new Error(`Cannot concatenate complex64 tensors with a tensor
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vO(e,t,n){let r=P(e,"x","batchToSpaceND"),s=t.reduce((i,l)=>i*l);L(r.rank>=1+t.length,()=>`input rank is ${r.rank} but should be > than blockShape.length ${t.length}`),L(n.length===t.length,()=>`crops.length is ${n.length} but should be equal to blockShape.length  ${t.length}`),L(r.shape[0]%s==0,()=>`input tensor batch is ${r.shape[0]} but is not divisible by the product of the elements of blockShape ${t.join(" * ")} === ${s}`);let a={x:r},o={blockShape:t,crops:n};return U.runKernel(mv,a,o)}var Wk=H({batchToSpaceND_:vO});function wO(e){let t;return e.rank===0||e.rank===1?t=ue(e,[1,1,1,e.size]):e.rank===2?t=ue(e,[1,1,e.shape[0],e.shape[1]]):e.rank===3?t=ue(e,[1,e.shape[0],e.shape[1],e.shape[2]]):t=e,t}function kO(e,t,n,r,s,a){a==null&&(a=.001);let o=P(e,"x","batchNorm"),i=P(t,"mean","batchNorm"),l=P(n,"variance","batchNorm"),u;s!=null&&(u=P(s,"scale","batchNorm"));let c;r!=null&&(c=P(r,"offset","batchNorm")),L(i.rank===l.rank,()=>"Batch normalization gradient requires mean and variance 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${u.rank}.`),c!=null&&L(c.rank===2||c.rank===1,()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${c.rank}.`),Ap(o,i,l,c,u,a)}var SO=H({batchNorm2d_:IO});function TO(e,t,n,r,s,a){let o=P(e,"x","batchNorm"),i=P(t,"mean","batchNorm"),l=P(n,"variance","batchNorm"),u;s!=null&&(u=P(s,"scale","batchNorm"));let c;return r!=null&&(c=P(r,"offset","batchNorm")),L(o.rank===3,()=>`Error in batchNorm3D: x must be rank 3 but got rank ${o.rank}.`),L(i.rank===3||i.rank===1,()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${i.rank}.`),L(l.rank===3||l.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${l.rank}.`),u!=null&&L(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${u.rank}.`),c!=null&&L(c.rank===3||c.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${c.rank}.`),Ap(o,i,l,c,u,a)}var NO=H({batchNorm3d_:TO});function CO(e,t,n,r,s,a){let o=P(e,"x","batchNorm"),i=P(t,"mean","batchNorm"),l=P(n,"variance","batchNorm"),u;s!=null&&(u=P(s,"scale","batchNorm"));let c;return r!=null&&(c=P(r,"offset","batchNorm")),L(o.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${o.rank}.`),L(i.rank===4||i.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${i.rank}.`),L(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${l.rank}.`),u!=null&&L(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${u.rank}.`),c!=null&&L(c.rank===4||c.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${c.rank}.`),Ap(o,i,l,c,u,a)}var EO=H({batchNorm4d_:CO});function $O(e,t,n){let r=P(e,"x","bincount"),s=P(t,"weights","bincount");L(r.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${r.dtype}`),L(n>=0,()=>`size must be non-negative, but got ${n}.`),L(s.size===r.size||s.size===0,()=>`Error in bincount: weights must have the same size as input or0-length, but got input shape: ${r.shape}, weights shape: ${s.shape}.`);let a={x:r,weights:s},o={size:n};return U.runKernel(gv,a,o)}var Vk=H({bincount_:$O});function _O(e,t){let n=P(e,"broadcastTo","x"),r=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=${n.rank}.`);if(t.length>n.rank){let u=n.shape.slice();for(;u.length<t.length;)u.unshift(1);n=ue(n,u)}let s=n.shape,a=Array.from(t);for(let u=t.length-1;u>=0;u--)if(s[u]===t[u])a[u]=1;else if(n.shape[u]!==1)throw new Error(`broadcastTo(): [${r}] cannot be broadcast to [${t}].`);if(a.map((u,c)=>u>1?c:-1).filter(u=>u>=0).length===0)return Js(n);let i={x:n},l={reps:a};return U.runKernel(d2,i,l)}var xp=H({broadcastTo_:_O});function RO(e){let n={x:P(e,"x","ceil")};return U.runKernel(yv,n)}var DO=H({ceil_:RO});function FO(e,t,n){let r=P(e,"x","clipByValue");L(t<=n,()=>`Error in clip: min (${t}) must be less than or equal to max (${n}).`);let s={x:r},a={clipValueMin:t,clipValueMax:n};return U.runKernel(Av,s,a)}var MO=H({clipByValue_:FO});function OO(e){return an(e,0)}var PO=H({concat1d_:OO});function zO(e,t){return an(e,t)}var lc=H({concat2d_:zO});function LO(e,t){return an(e,t)}var BO=H({concat3d_:LO});function WO(e,t){return an(e,t)}var VO=H({concat4d_:WO});function UO(e,t,n,r,s="NHWC",a=[1,1],o){let i=P(e,"x","conv2d"),l=P(t,"filter","conv2d"),u=i,c=!1;i.rank===3&&(c=!0,u=ue(i,[1,i.shape[0],i.shape[1],i.shape[2]])),L(u.rank===4,()=>`Error in conv2d: input must be rank 4, but got rank ${u.rank}.`),L(l.rank===4,()=>`Error in conv2d: filter must be rank 4, but got rank ${l.rank}.`),o!=null&&L(Xn(r),()=>`Error in conv2d: pad must be an integer when using, dimRoundingMode ${o} but got pad ${r}.`);let d=s==="NHWC"?u.shape[3]:u.shape[1];L(d===l.shape[2],()=>`Error in conv2d: depth of input (${d}) must match input depth for filter ${l.shape[2]}.`),L(Qs(n,a),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`);let h={x:u,filter:l},p={strides:n,pad:r,dataFormat:s,dilations:a,dimRoundingMode:o},f=U.runKernel(wv,h,p);return c?ue(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var bp=H({conv2d_:UO});function HO(e,t,n,r,s="NWC",a=1,o){let i=P(e,"x","conv1d"),l=P(t,"filter","conv1d"),u=i,c=!1;i.rank===2&&(c=!0,u=ue(i,[1,i.shape[0],i.shape[1]])),L(u.rank===3,()=>`Error in conv1d: input must be rank 3, but got rank ${u.rank}.`),L(l.rank===3,()=>`Error in conv1d: filter must be rank 3, but got rank ${l.rank}.`),o!=null&&L(Xn(r),()=>`Error in conv1d: pad must be an integer when using, dimRoundingMode ${o} but got pad ${r}.`),L(u.shape[2]===l.shape[1],()=>`Error in conv1d: depth of input (${u.shape[2]}) must match input depth for filter ${l.shape[1]}.`),L(Qs(n,a),()=>`Error in conv1D: Either stride or dilation must be 1. Got stride ${n} and dilation '${a}'`),L(s==="NWC",()=>`Error in conv1d: got dataFormat of ${s} but only NWC is currently supported.`);let d=ue(l,[1,l.shape[0],l.shape[1],l.shape[2]]),h=ue(u,[u.shape[0],1,u.shape[1],u.shape[2]]),g=bp(h,d,[1,n],r,"NHWC",[1,a],o);return c?ue(g,[g.shape[2],g.shape[3]]):ue(g,[g.shape[0],g.shape[2],g.shape[3]])}var GO=H({conv1d_:HO});function jO(e,t,n,r,s,a="NHWC",o){L(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let i=e,l=t,u=!1;t.rank===3&&(u=!0,l=ue(t,[1,t.shape[0],t.shape[1],t.shape[2]]),i=[1,e[0],e[1],e[2]]),L(i.length===4,()=>`Error in conv2dDerInput: inShape must be length 4, but got length ${i.length}.`),L(l.rank===4,()=>`Error in conv2dDerInput: dy must be rank 4, but got rank ${l.rank}`),L(n.rank===4,()=>`Error in conv2dDerInput: filter must be rank 4, but got rank ${n.rank}`);let c=a==="NHWC"?i[3]:i[1],d=a==="NHWC"?l.shape[3]:l.shape[1];L(c===n.shape[2],()=>`Error in conv2dDerInput: depth of input (${c}) must match input depth for filter ${n.shape[2]}.`),L(d===n.shape[3],()=>`Error in conv2dDerInput: depth of output (${d}) must match output depth for filter ${n.shape[3]}.`),o!=null&&L(Xn(s),()=>`Error in conv2dDerInput: pad must be an integer when using, dimRoundingMode ${o} but got pad ${s}.`);let h={dy:l,filter:n},p={strides:r,pad:s,dataFormat:a,dimRoundingMode:o,inputShape:i},f=U.runKernel(Iv,h,p);return u?ue(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var Uk=H({conv2DBackpropInput_:jO});function qO(e,t,n,r,s,a){let o=P(e,"x","conv2dTranspose"),i=P(t,"filter","conv2dTranspose");return Uk(n,o,i,r,s,"NHWC",a)}var KO=H({conv2dTranspose_:qO});function XO(e,t,n,r,s="NDHWC",a=[1,1,1]){let o=P(e,"x","conv3d"),i=P(t,"filter","conv3d"),l=o,u=!1;o.rank===4&&(u=!0,l=ue(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),L(l.rank===5,()=>`Error in conv3d: input must be rank 5, but got rank ${l.rank}.`),L(i.rank===5,()=>`Error in conv3d: filter must be rank 5, but got rank ${i.rank}.`),L(l.shape[4]===i.shape[3],()=>`Error in conv3d: depth of input (${l.shape[4]}) must match input depth for filter ${i.shape[3]}.`),L(Qs(n,a),()=>`Error in conv3D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`),L(s==="NDHWC",()=>`Error in conv3d: got dataFormat of ${s} but only NDHWC is currently supported.`);let c={x:l,filter:i},d={strides:n,pad:r,dataFormat:s,dilations:a},h=U.runKernel(Sv,c,d);return u?ue(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}var ZO=H({conv3d_:XO});function YO(e,t,n,r,s){L(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let a=e,o=t,i=!1;t.rank===4&&(i=!0,o=ue(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];L(a.length===5,()=>`Error in conv3dDerInput: inShape must be length 5, but got length ${a.length}.`),L(o.rank===5,()=>`Error in conv3dDerInput: dy must be rank 5, but got rank ${o.rank}`),L(n.rank===5,()=>`Error in conv3dDerInput: filter must be rank 5, but got rank ${n.rank}`),L(l===n.shape[3],()=>`Error in conv3dDerInput: depth of input (${l}) must match input depth for filter ${n.shape[3]}.`),L(u===n.shape[4],()=>`Error in conv3dDerInput: depth of output (${u}) must match output depth for filter ${n.shape[4]}.`);let c={dy:o,filter:n},d={pad:s,strides:r,inputShape:a},h=U.runKernel(Tv,c,d);return i?ue(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}var JO=H({conv3DBackpropInput_:YO});function QO(e,t,n,r,s){let a=P(e,"x","conv3dTranspose"),o=P(t,"filter","conv3dTranspose");return JO(n,a,o,r,s)}var eP=H({conv3dTranspose_:QO});function tP(e){let n={x:P(e,"x","cos")};return U.runKernel(Nv,n)}var nP=H({cos_:tP});function rP(e){let n={x:P(e,"x","cosh")};return U.runKernel(Cv,n)}var sP=H({cosh_:rP});function aP(e,t=0,n=!1,r=!1){let a={x:P(e,"x","cumsum")},o={axis:t,exclusive:n,reverse:r};return U.runKernel(Ev,a,o)}var oP=H({cumsum_:aP});function iP(e,t,n,r=!1){let s=P(e,"x","denseBincount"),a=P(t,"weights","denseBincount");L(s.dtype==="int32",()=>`Error in denseBincount: input dtype must be int32, but got ${s.dtype}`),L(s.rank<=2,()=>`Error in denseBincount: input must be at most rank 2, but got rank ${s.rank}.`),L(n>=0,()=>`size must be non-negative, but got ${n}.`),L(a.size===s.size||a.size===0,()=>`Error in denseBincount: weights must have the same shape as x or 0-length, but got x shape: ${s.shape}, weights shape: ${a.shape}.`);let o={x:s,weights:a},i={size:n,binaryOutput:r};return U.runKernel(_v,o,i)}var lP=H({denseBincount_:iP});function uP(e,t,n="NHWC"){let r=P(e,"x","depthToSpace"),s=n==="NHWC"?r.shape[1]:r.shape[2],a=n==="NHWC"?r.shape[2]:r.shape[3],o=n==="NHWC"?r.shape[3]:r.shape[1];L(s*t>=0,()=>`Negative dimension size caused by overflow when multiplying
    ${s} and ${t}  for depthToSpace with input shape
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d={x:u,filter:l},h={strides:n,pad:r,dataFormat:s,dilations:a,dimRoundingMode:o},p=U.runKernel(Dv,d,h);return c?ue(p,[p.shape[1],p.shape[2],p.shape[3]]):p}var ty=H({depthwiseConv2d_:dP});function hP(e){let n={x:P(e,"x","diag")};return U.runKernel(Ov,n)}var pP=H({diag_:hP});function fP(e,t,n,r,s=[1,1],a="NHWC"){let o=P(e,"x","dilation2d"),i=P(t,"filter","dilation2d");L(o.rank===3||o.rank===4,()=>`Error in dilation2d: input must be rank 3 or 4, but got rank ${o.rank}.`),L(i.rank===3,()=>`Error in dilation2d: filter must be rank 3, but got rank ${i.rank}.`),L(a==="NHWC",()=>`Error in dilation2d: Only NHWC is currently supported, but got dataFormat of ${a}`);let l=o,u=!1;o.rank===3&&(l=ue(o,[1,o.shape[0],o.shape[1],o.shape[2]]),u=!0);let c={x:l,filter:i},d={strides:n,pad:r,dilations:s},h=U.runKernel(Pv,c,d);return u?ue(h,[h.shape[1],h.shape[2],h.shape[3]]):h}var mP=H({dilation2d_:fP});function gP(e,t){let n=e.length,r=[];for(let s=0;s<n;s++){let 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l={image:o,transforms:i},u={interpolation:n,fillMode:r,fillValue:s,outputShape:a};return U.runKernel(T7,l,u)}var ZW=H({transform_:XW});function YW(e,t,n){L(t%1==0,()=>`bandPart(): numLower must be an integer, got ${t}.`),L(n%1==0,()=>`bandPart(): numUpper must be an integer, got ${n}.`);let r=P(e,"a","bandPart");L(r.rank>=2,()=>`bandPart(): Rank must be at least 2, got ${r.rank}.`);let s=r.shape,[a,o]=r.shape.slice(-2);if(!(t<=a))throw new Error(`bandPart(): numLower (${t}) must not be greater than the number of rows (${a}).`);if(!(n<=o))throw new Error(`bandPart(): numUpper (${n}) must not be greater than the number of columns (${o}).`);t<0&&(t=a),n<0&&(n=o);let i=ue(pc(0,a,1,"int32"),[-1,1]),l=pc(0,o,1,"int32"),u=He(i,l),c=Sp(ry(u,ut(+t,"int32")),Zk(u,ut(-n,"int32"))),d=ji([a,o],r.dtype);return ue(So(fc(ue(r,[-1,a,o])).map(h=>Gi(c,h,d))),s)}var JW=H({bandPart_:YW});function QW(e){let t;if(Array.isArray(e)){t=!1,L(e!=null&&e.length>0,()=>"Gram-Schmidt process: input must not be null, 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U.tidy(()=>{L(e.shape.length===2,()=>`qr2d() requires a 2D Tensor, but got a ${e.shape.length}D Tensor.`);let n=e.shape[0],r=e.shape[1],s=qk(n),a=Js(e),o=ra([[1]],[1,1]),i=Js(o),l=n>=r?r:n;for(let u=0;u<l;++u){let c=a,d=i,h=s;[i,a,s]=U.tidy(()=>{let p=Ze(a,[u,u],[n-u,1]),f=cy(p),m=Ze(a,[u,u],[1,1]),g=Gi(kp(m,0),ra([[-1]]),ra([[1]])),y=He(m,fe(g,f)),A=Qe(p,y);A.shape[0]===1?i=Js(o):i=an([o,Ze(A,[1,0],[A.shape[0]-1,A.shape[1]])],0);let x=$a(Qe(yt(g,y),f)),b=Ze(a,[u,0],[n-u,r]),v=fe(x,i),w=fp(i);if(u===0)a=He(b,yt(v,yt(w,b)));else{let C=He(b,yt(v,yt(w,b)));a=an([Ze(a,[0,0],[u,r]),C],0)}let I=fp(v),T=Ze(s,[0,u],[n,s.shape[1]-u]);if(u===0)s=He(T,yt(yt(T,i),I));else{let C=He(T,yt(yt(T,i),I));s=an([Ze(s,[0,0],[n,u]),C],1)}return[i,a,s]}),Ve([c,d,h])}return!t&&n>r&&(s=Ze(s,[0,0],[n,r]),a=Ze(a,[0,0],[r,r])),[s,a]})}var nV=H({qr_:tV}),Pn;(function(e){e[e.NONE=0]="NONE",e[e.MEAN=1]="MEAN",e[e.SUM=2]="SUM",e[e.SUM_BY_NONZERO_WEIGHTS=3]="SUM_BY_NONZERO_WEIGHTS"})(Pn||(Pn={}));function rV(e,t,n=Pn.SUM_BY_NONZERO_WEIGHTS){let r=P(e,"losses","computeWeightedLoss"),s=null;t!=null&&(s=P(t,"weights","computeWeightedLoss"));let a=s==null?r:fe(r,s);if(n===Pn.NONE)return a;if(n===Pn.SUM)return _t(a);if(n===Pn.MEAN){if(s==null)return Tp(a);{let o=r.size/s.size,i=Qe(_t(a),_t(s));return o>1?Qe(i,ut(o)):i}}if(n===Pn.SUM_BY_NONZERO_WEIGHTS){if(s==null)return Qe(_t(a),ut(r.size));{let o=fe(s,ko(r.shape)),i=Pt(_t(l4(o,ut(0))),"float32");return Qe(_t(a),i)}}throw Error(`Unknown reduction: ${n}`)}var sa=H({computeWeightedLoss_:rV});function sV(e,t,n,r=Pn.SUM_BY_NONZERO_WEIGHTS){let s=P(e,"labels","absoluteDifference"),a=P(t,"predictions","absoluteDifference"),o=null;n!=null&&(o=P(n,"weights","absoluteDifference")),Mn(s.shape,a.shape,"Error in absoluteDifference: ");let i=Nr(He(s,a));return sa(i,o,r)}var aV=H({absoluteDifference_:sV});function oV(e,t,n,r,s=Pn.SUM_BY_NONZERO_WEIGHTS){let a=P(e,"labels","cosineDistance"),o=P(t,"predictions","cosineDistance"),i=null;r!=null&&(i=P(r,"weights","cosineDistance")),Mn(a.shape,o.shape,"Error in cosineDistance: ");let l=ut(1),u=He(l,_t(fe(a,o),n,!0));return sa(u,i,s)}var iV=H({cosineDistance_:oV});function lV(e,t,n,r=Pn.SUM_BY_NONZERO_WEIGHTS){let s=P(e,"labels","hingeLoss"),a=P(t,"predictions","hingeLoss"),o=null;n!=null&&(o=P(n,"weights","hingeLoss")),Mn(s.shape,a.shape,"Error in hingeLoss: ");let i=ut(1);s=He(fe(ut(2),s),i);let l=Cp(He(i,fe(s,a)));return sa(l,o,r)}var uV=H({hingeLoss_:lV});function cV(e,t,n,r=1,s=Pn.SUM_BY_NONZERO_WEIGHTS){let a=P(e,"labels","huberLoss"),o=P(t,"predictions","huberLoss"),i=null;n!=null&&(i=P(n,"weights","huberLoss")),Mn(a.shape,o.shape,"Error in huberLoss: ");let l=ut(r),u=Nr(He(o,a)),c=i4(u,l),d=He(u,c),h=Me(fe(ut(.5),ns(c)),fe(l,d));return sa(h,i,s)}var dV=H({huberLoss_:cV});function hV(e,t,n,r=1e-7,s=Pn.SUM_BY_NONZERO_WEIGHTS){let a=P(e,"labels","logLoss"),o=P(t,"predictions","logLoss"),i=null;n!=null&&(i=P(n,"weights","logLoss")),Mn(a.shape,o.shape,"Error in logLoss: ");let l=ut(1),u=ut(r),c=$a(fe(a,uc(Me(o,u)))),d=fe(He(l,a),uc(Me(He(l,o),u))),h=He(c,d);return sa(h,i,s)}var pV=H({logLoss_:hV});function fV(e,t,n,r=Pn.SUM_BY_NONZERO_WEIGHTS){let s=P(e,"labels","meanSquaredError"),a=P(t,"predictions","meanSquaredError"),o=null;n!=null&&(o=P(n,"weights","meanSquaredError")),Mn(s.shape,a.shape,"Error in meanSquaredError: ");let i=m4(s,a);return sa(i,o,r)}var mV=H({meanSquaredError_:fV});function gV(e,t){let n=P(e,"labels","sigmoidCrossEntropyWithLogits"),r=P(t,"logits","sigmoidCrossEntropyWithLogits");Mn(n.shape,r.shape,"Error in sigmoidCrossEntropyWithLogits: ");let s=Cp(r),a=fe(r,n),o=Jk(wo($a(Nr(r))));return Me(He(s,a),o)}function yV(e,t,n,r=0,s=Pn.SUM_BY_NONZERO_WEIGHTS){let a=P(e,"multiClassLabels","sigmoidCrossEntropy"),o=P(t,"logits","sigmoidCrossEntropy"),i=null;if(n!=null&&(i=P(n,"weights","sigmoidCrossEntropy")),Mn(a.shape,o.shape,"Error in sigmoidCrossEntropy: "),r>0){let u=ut(r),c=ut(1),d=ut(.5);a=Me(fe(a,He(c,u)),fe(d,u))}let l=gV(a,o);return sa(l,i,s)}var AV=H({sigmoidCrossEntropy_:yV});function xV(e,t,n=-1){if(n===-1&&(n=t.rank-1),n!==t.rank-1)throw Error(`Softmax cross entropy along a non-last dimension is not yet supported. Labels / logits was rank ${t.rank} and dim was ${n}`);return Ns((s,a,o)=>{let l=n4(a,[n],!0),u=He(Pt(a,"float32"),l);o([s,u]);let c=$a(fe(u,s));return{value:_t(c,[n]),gradFunc:(p,f)=>{let[m,g]=f,y=cc(p.shape,[n]);return[fe(ue(p,y),He(Pt(m,"float32"),wo(g))),fe(ue(p,y),He(wo(g),Pt(m,"float32")))]}}})(e,t)}function bV(e,t,n,r=0,s=Pn.SUM_BY_NONZERO_WEIGHTS){let a=P(e,"onehotLabels","softmaxCrossEntropy"),o=P(t,"logits","softmaxCrossEntropy"),i=null;if(n!=null&&(i=P(n,"weights","softmaxCrossEntropy")),Mn(a.shape,o.shape,"Error in softmaxCrossEntropy: "),r>0){let u=ut(r),c=ut(1),d=ut(a.shape[1]);a=Me(fe(a,He(c,u)),Qe(u,d))}let l=xV(a,o);return sa(l,i,s)}var vV=H({softmaxCrossEntropy_:bV});function wV(e,t,n,r){let s=P(e,"indices","sparseFillEmptyRows"),a=P(t,"values","sparseFillEmptyRows"),o=P(n,"denseShape","sparseFillEmptyRows"),i=P(r,"defaultValue","sparseFillEmptyRows",a.dtype);if(s.rank!==2)throw new Error(`Indices should be Tensor2D but received shape
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        ${r.shape}`);if(s.rank!==1)throw new Error(`Input shape should be Tensor1D but received shape ${s.shape}`);if(a.rank!==1)throw new Error(`New shape should be Tensor1D but received shape ${a.shape}`);let o={inputIndices:r,inputShape:s,newShape:a},i=U.runKernel(p7,o);return{outputIndices:i[0],outputShape:i[1]}}var SV=H({sparseReshape_:IV});function TV(e,t,n){let r=P(e,"data","sparseSegmentMean"),s=P(t,"indices","sparseSegmentMean"),a=P(n,"segmentIds","sparseSegmentMean");if(r.rank<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(s.rank!==1)throw new Error(`Indices should be Tensor1D but received shape
          ${s.shape}`);if(a.rank!==1)throw new Error(`Segment ids should be Tensor1D but received shape
          ${a.shape}`);let o={data:r,indices:s,segmentIds:a};return U.runKernel(f7,o)}var NV=H({sparseSegmentMean_:TV});function CV(e,t,n){let r=P(e,"data","sparseSegmentSum"),s=P(t,"indices","sparseSegmentSum"),a=P(n,"segmentIds","sparseSegmentSum");if(r.rank<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(s.rank!==1)throw new Error(`Indices should be Tensor1D but received shape
         ${s.shape}`);if(a.rank!==1)throw new Error(`Segment ids should be Tensor1D but received shape
         ${a.shape}`);let o={data:r,indices:s,segmentIds:a};return U.runKernel(m7,o)}var EV=H({sparseSegmentSum_:CV});function $V(e,t,n,r,s,a,o,i){let l=P(e,"data","stringNGrams","string");if(l.dtype!=="string")throw new Error("Data must be of datatype string");if(l.shape.length!==1)throw new Error(`Data must be a vector, saw: ${l.shape}`);let u=P(t,"dataSplits","stringNGrams");if(u.dtype!=="int32")throw new Error("Data splits must be of datatype int32");let c={separator:n,nGramWidths:r,leftPad:s,rightPad:a,padWidth:o,preserveShortSequences:i},d={data:l,dataSplits:u},h=U.runKernel(x7,d,c);return{nGrams:h[0],nGramsSplits:h[1]}}var _V=H({stringNGrams_:$V});function RV(e,t,n=!0){let r=P(e,"input","stringSplit","string"),s=P(t,"delimiter","stringSplit","string");if(r.rank!==1)throw new Error(`Input should be Tensor1D but received shape ${r.shape}`);if(s.rank!==0)throw new Error(`Delimiter should be a scalar but received shape ${s.shape}`);let a={skipEmpty:n},o={input:r,delimiter:s},i=U.runKernel(b7,o,a);return{indices:i[0],values:i[1],shape:i[2]}}var DV=H({stringSplit_:RV});function FV(e,t){let n=P(e,"input","stringToHashBucketFast","string"),r={numBuckets:t};if(t<=0)throw new Error("Number of buckets must be at least 1");let s={input:n};return U.runKernel(v7,s,r)}var MV=H({stringToHashBucketFast_:FV}),OV={fft:ly,ifft:Ep,rfft:uy,irfft:f4},PV={hammingWindow:pW,hannWindow:w4,frame:k4,stft:yW},Ye={flipLeftRight:vW,resizeNearestNeighbor:GW,resizeBilinear:UW,rotateWithOffset:kW,cropAndResize:xW,nonMaxSuppression:SW,nonMaxSuppressionAsync:DW,nonMaxSuppressionWithScore:MW,nonMaxSuppressionWithScoreAsync:PW,nonMaxSuppressionPadded:LW,nonMaxSuppressionPaddedAsync:WW,threshold:KW,transform:ZW},zV={bandPart:JW,gramSchmidt:eV,qr:nV},LV={absoluteDifference:aV,computeWeightedLoss:sa,cosineDistance:iV,hingeLoss:uV,huberLoss:dV,logLoss:pV,meanSquaredError:mV,sigmoidCrossEntropy:AV,softmaxCrossEntropy:vV},BV={sparseFillEmptyRows:kV,sparseReshape:SV,sparseSegmentMean:NV,sparseSegmentSum:EV},WV={stringNGrams:_V,stringSplit:DV,stringToHashBucketFast:MV},Ra=class extends $k{minimize(e,t=!1,n){let{value:r,grads:s}=this.computeGradients(e,n);if(n!=null){let a=n.map(o=>({name:o.name,tensor:s[o.name]}));this.applyGradients(a)}else this.applyGradients(s);return Ve(s),t?r:(r.dispose(),null)}get iterations(){return this.iterations_==null&&(this.iterations_=0),this.iterations_}incrementIterations(){this.iterations_=this.iterations+1}computeGradients(e,t){return Qk(e,t)}dispose(){this.iterations_!=null&&Ve(this.iterations_)}async saveIterations(){return this.iterations_==null&&(this.iterations_=0),{name:"iter",tensor:ut(this.iterations_,"int32")}}async getWeights(){throw new Error("getWeights() is not implemented for this optimizer yet.")}async setWeights(e){throw new Error(`setWeights() is not implemented for this optimizer class ${this.getClassName()}`)}async extractIterations(e){return this.iterations_=(await e[0].tensor.data())[0],e.slice(1)}};Object.defineProperty(Ra,Symbol.hasInstance,{value:e=>e.minimize!=null&&e.computeGradients!=null&&e.applyGradients!=null});var Fp=class extends Ra{constructor(e,t,n=null){super();this.learningRate=e,this.rho=t,this.epsilon=n,this.accumulatedGrads=[],this.accumulatedUpdates=[],n==null&&(this.epsilon=U.backend.epsilon())}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,r)=>{let s=U.registeredVariables[n],a=!1;this.accumulatedGrads[r]==null&&(this.accumulatedGrads[r]={originalName:`${n}/accum_grad`,variable:Ue(()=>Cr(s).variable(a))}),this.accumulatedUpdates[r]==null&&(this.accumulatedUpdates[r]={originalName:`${n}/accum_var`,variable:Ue(()=>Cr(s).variable(a))});let o=Array.isArray(e)?e[r].tensor:e[n];if(o==null)return;let i=this.accumulatedGrads[r].variable,l=this.accumulatedUpdates[r].variable;Ue(()=>{let u=Me(fe(i,this.rho),fe(ns(o),1-this.rho)),c=fe(Qe(na(Me(l,this.epsilon)),na(Me(i,this.epsilon))),o),d=Me(fe(l,this.rho),fe(ns(c),1-this.rho));i.assign(u),l.assign(d);let h=Me(fe(c,-this.learningRate),s);s.assign(h)})}),this.incrementIterations()}dispose(){this.accumulatedUpdates!=null&&(Ve(this.accumulatedGrads.map(e=>e.variable)),Ve(this.accumulatedUpdates.map(e=>e.variable)))}async getWeights(){let e=[...this.accumulatedGrads,...this.accumulatedUpdates];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=e.length/2,n=!1;this.accumulatedGrads=e.slice(0,t).map(r=>({originalName:r.name,variable:r.tensor.variable(n)})),this.accumulatedUpdates=e.slice(t,t*2).map(r=>({originalName:r.name,variable:r.tensor.variable(n)}))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}};Fp.className="Adadelta";Ea(Fp);var Mp=class extends Ra{constructor(e,t=.1){super();this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,r)=>{let s=U.registeredVariables[n];if(this.accumulatedGrads[r]==null){let i=!1;this.accumulatedGrads[r]={originalName:`${n}/accumulator`,variable:Ue(()=>wp(s.shape,this.initialAccumulatorValue).variable(i))}}let a=Array.isArray(e)?e[r].tensor:e[n];if(a==null)return;let o=this.accumulatedGrads[r].variable;Ue(()=>{let i=Me(o,ns(a));o.assign(i);let l=Me(fe(Qe(a,na(Me(i,U.backend.epsilon()))),-this.learningRate),s);s.assign(l)})}),this.incrementIterations()}dispose(){this.accumulatedGrads!=null&&Ve(this.accumulatedGrads.map(e=>e.variable))}async getWeights(){return[await this.saveIterations()].concat(this.accumulatedGrads.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulatedGrads=e.map(n=>({originalName:n.name,variable:n.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}}static fromConfig(e,t){return new e(t.learningRate,t.initialAccumulatorValue)}};Mp.className="Adagrad";Ea(Mp);var Op=class extends Ra{constructor(e,t,n,r=null){super();this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=r,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],Ue(()=>{this.accBeta1=ut(t).variable(),this.accBeta2=ut(n).variable()}),r==null&&(this.epsilon=U.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);Ue(()=>{let n=He(1,this.accBeta1),r=He(1,this.accBeta2);t.forEach((s,a)=>{let o=U.registeredVariables[s],i=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${s}/m`,variable:Ue(()=>Cr(o).variable(i))}),this.accumulatedSecondMoment[a]==null&&(this.accumulatedSecondMoment[a]={originalName:`${s}/v`,variable:Ue(()=>Cr(o).variable(i))});let l=Array.isArray(e)?e[a].tensor:e[s];if(l==null)return;let u=this.accumulatedFirstMoment[a].variable,c=this.accumulatedSecondMoment[a].variable,d=Me(fe(u,this.beta1),fe(l,1-this.beta1)),h=Me(fe(c,this.beta2),fe(ns(l),1-this.beta2)),p=Qe(d,n),f=Qe(h,r);u.assign(d),c.assign(h);let m=Me(fe(Qe(p,Me(na(f),this.epsilon)),-this.learningRate),o);o.assign(m)}),this.accBeta1.assign(fe(this.accBeta1,this.beta1)),this.accBeta2.assign(fe(this.accBeta2,this.beta2))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),this.accumulatedFirstMoment!=null&&Ve(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedSecondMoment!=null&&Ve(this.accumulatedSecondMoment.map(e=>e.variable))}async getWeights(){let e=[...this.accumulatedFirstMoment,...this.accumulatedSecondMoment];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e),Ue(()=>{this.accBeta1.assign(hc(this.beta1,this.iterations_+1)),this.accBeta2.assign(hc(this.beta2,this.iterations_+1))});let t=e.length/2,n=!1;this.accumulatedFirstMoment=e.slice(0,t).map(r=>({originalName:r.name,variable:r.tensor.variable(n)})),this.accumulatedSecondMoment=e.slice(t,t*2).map(r=>({originalName:r.name,variable:r.tensor.variable(n)}))}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon)}};Op.className="Adam";Ea(Op);var Pp=class extends Ra{constructor(e,t,n,r=null,s=0){super();this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=r,this.decay=s,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],Ue(()=>{this.iteration=ut(0).variable(),this.accBeta1=ut(t).variable()}),r==null&&(this.epsilon=U.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);Ue(()=>{let n=He(1,this.accBeta1),r=Qe(-this.learningRate,Me(fe(this.iteration,this.decay),1));t.forEach((s,a)=>{let o=U.registeredVariables[s],i=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${s}/m`,variable:Cr(o).variable(i)}),this.accumulatedWeightedInfNorm[a]==null&&(this.accumulatedWeightedInfNorm[a]={originalName:`${s}/v`,variable:Cr(o).variable(i)});let l=Array.isArray(e)?e[a].tensor:e[s];if(l==null)return;let u=this.accumulatedFirstMoment[a].variable,c=this.accumulatedWeightedInfNorm[a].variable,d=Me(fe(u,this.beta1),fe(l,1-this.beta1)),h=fe(c,this.beta2),p=Nr(l),f=o4(h,p);u.assign(d),c.assign(f);let m=Me(fe(Qe(r,n),Qe(d,Me(f,this.epsilon))),o);o.assign(m)}),this.iteration.assign(Me(this.iteration,1)),this.accBeta1.assign(fe(this.accBeta1,this.beta1))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),this.accumulatedFirstMoment!=null&&Ve(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedWeightedInfNorm!=null&&Ve(this.accumulatedWeightedInfNorm.map(e=>e.variable))}async getWeights(){throw new Error("getWeights() is not implemented for Adamax yet.")}async setWeights(e){throw new Error("setWeights() is not implemented for Adamax yet.")}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon,t.decay)}};Pp.className="Adamax";Ea(Pp);var mc=class extends Ra{constructor(e){super();this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,r)=>{let s=Array.isArray(e)?e[r].tensor:e[n];if(s==null)return;let a=U.registeredVariables[n];Ue(()=>{let o=Me(fe(this.c,s),a);a.assign(o)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=Mk(ut(-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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n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*gy(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 gf||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*gy(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 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a=O(e,"multiClassLabels","sigmoidCrossEntropy"),o=O(t,"logits","sigmoidCrossEntropy"),i=null;if(n!=null&&(i=O(n,"weights","sigmoidCrossEntropy")),rs(a.shape,o.shape,"Error in sigmoidCrossEntropy: "),r>0){let u=Fe(r),c=Fe(1),d=Fe(.5);a=pe(K(a,Ne(c,u)),K(d,u))}let l=jZ(a,o);return Ua(l,i,s)}var Bwe=V({sigmoidCrossEntropy_:qZ});function KZ(e,t,n=-1){if(n===-1&&(n=t.rank-1),n!==t.rank-1)throw Error(`Softmax cross entropy along a non-last dimension is not yet supported. 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a={skipEmpty:n},o={input:r,delimiter:s},i=G.runKernel(tA,o,a);return{indices:i[0],values:i[1],shape:i[2]}}var iY=V({stringSplit_:oY});function lY(e,t){let n=O(e,"input","stringToHashBucketFast","string"),r={numBuckets:t};if(t<=0)throw new Error("Number of buckets must be at least 1");let s={input:n};return G.runKernel(nA,s,r)}var uY=V({stringToHashBucketFast_:lY}),ni={flipLeftRight:aZ,resizeNearestNeighbor:LI,resizeBilinear:zI,rotateWithOffset:iZ,cropAndResize:rZ,nonMaxSuppression:uZ,nonMaxSuppressionAsync:yZ,nonMaxSuppressionWithScore:xZ,nonMaxSuppressionWithScoreAsync:vZ,nonMaxSuppressionPadded:kZ,nonMaxSuppressionPaddedAsync:SZ,threshold:$Z,transform:RZ},cY={bandPart:FZ,gramSchmidt:OZ,qr:zZ},Vf={sparseFillEmptyRows:YZ,sparseReshape:QZ,sparseSegmentMean:tY,sparseSegmentSum:rY},f1={stringNGrams:aY,stringSplit:iY,stringToHashBucketFast:uY},Ha=class extends B6{minimize(e,t=!1,n){let{value:r,grads:s}=this.computeGradients(e,n);if(n!=null){let 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e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};mx.className="ThresholdedReLU";ce.registerClass(mx);var gx=class extends st{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new lx().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Ke(e);return this.softmax(n,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};gx.className="Softmax";ce.registerClass(gx);function iu(e,t,n){if(typeof e=="number")return si(e,t);if(e.length!==t)throw new q(`The ${n} argument must be an integer or tuple of ${t} integers. 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Received: ${JSON.stringify(e)} including a non-integer number ${s}`)}return e}function ms(e,t,n,r,s=1){if(e==null)return e;let a=t+(t-1)*(s-1),o;return n==="same"?o=e:o=e-a+1,Math.floor((o+r-1)/r)}function Ps(e,t,n,r){if(e==null)return null;if(r==="valid")e=e*t+qa([n-t,0]);else if(r==="same")e=e*t;else throw new q(`Unsupport padding mode: ${r}.`);return e}function yx(e,t){return Z(()=>(Yt(t),t==="channelsFirst"?pt(e,[0,2,3,1]):e))}function f8(e,t){return Z(()=>(Yt(t),t==="channelsFirst"?pt(e,[0,2,3,4,1]):e))}function qte(e,t,n,r=1,s="valid",a,o=1){return Z(()=>{if(a==null&&(a=us()),Yt(a),e.shape.length!==3)throw new q(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new q(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new q(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(a==="channelsFirst"&&(e=pt(e,[0,2,1])),s==="causal")throw new Ge("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let i=OA(e,t,r,s==="same"?"same":"valid","NWC",o);return n!=null&&(i=hs(i,n)),i})}function m8(e,t,n,r=[1,1],s="valid",a,o,i=null){return Z(()=>{if(a==null&&(a=us()),Yt(a),e.rank!==3&&e.rank!==4)throw new q(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new q(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=yx(e,a);if(s==="causal")throw new Ge("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=ti.conv2d({x:l,filter:t,strides:r,pad:s==="same"?"same":"valid",dilations:o,dataFormat:"NHWC",bias:n,activation:i}),a==="channelsFirst"&&(l=pt(l,[0,3,1,2])),l})}function Kte(e,t,n,r=[1,1,1],s="valid",a,o){return Z(()=>{if(a==null&&(a=us()),Yt(a),e.rank!==4&&e.rank!==5)throw new q(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new q(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let i=f8(e,a);if(s==="causal")throw new Ge("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return i=nI(i,t,r,s==="same"?"same":"valid","NDHWC",o),n!=null&&(i=hs(i,n)),a==="channelsFirst"&&(i=pt(i,[0,4,1,2,3])),i})}var Ax=class extends st{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",Ax.verifyArgs(t),this.rank=e,An(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Ge(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=iu(t.kernelSize,e,"kernelSize"),this.strides=iu(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,Yt(this.dataFormat),this.activation=Za(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=zt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=hn(t.biasConstraint),this.biasRegularizer=Lt(t.biasRegularizer),this.activityRegularizer=Lt(t.activityRegularizer),this.dilationRate=iu(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new q(`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 q(`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 q(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Ds("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!N1(e.kernelSize,"number",1,3))throw new q(`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:Xa(this.activation),useBias:this.useBias,biasInitializer:Ht(this.biasInitializer),biasRegularizer:kt(this.biasRegularizer),activityRegularizer:kt(this.activityRegularizer),biasConstraint:dn(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},qd=class extends Ax{constructor(e,t){super(e,t);this.kernel=null,qd.verifyArgs(t),this.filters=t.filters,An(this.filters,"filters"),this.kernelInitializer=zt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=hn(t.kernelConstraint),this.kernelRegularizer=Lt(t.kernelRegularizer)}build(e){e=At(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new q(`The channel dimension of the input should be defined. Found ${e[t]}`);let n=e[t],r=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",r,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:{[t]:n}}],this.built=!0}call(e,t){return Z(()=>{e=Ke(e);let n,r=this.bias==null?null:this.bias.read(),s=sS(this.activation.getClassName());if(s!=null&&this.rank===2)n=m8(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate,s);else{if(this.rank===1)n=qte(e,this.kernel.read(),r,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=m8(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=Kte(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new Ge("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=At(e);let t=[],n=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let s=0;s<n.length;++s){let a=ms(n[s],this.kernelSize[s],this.padding,this.strides[s],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[s]);t.push(a)}let r=[e[0]];return this.dataFormat==="channelsLast"?(r=r.concat(t),r.push(this.filters)):(r.push(this.filters),r=r.concat(t)),r}getConfig(){let e={filters:this.filters,kernelInitializer:Ht(this.kernelInitializer),kernelRegularizer:kt(this.kernelRegularizer),kernelConstraint:dn(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 q(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},g8=class extends qd{constructor(e){super(2,e);g8.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!N1(e.kernelSize,"number",1,2))throw new q(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}},fm=g8;fm.className="Conv2D";ce.registerClass(fm);var y8=class extends qd{constructor(e){super(3,e);y8.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 q(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}},mm=y8;mm.className="Conv3D";ce.registerClass(mm);var xx=class extends fm{constructor(e){super(e);if(this.inputSpec=[new tn({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new q(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=At(e),e.length!==4)throw new q("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new q("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new tn({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return Z(()=>{let n=Ke(e);if(n.shape.length!==4)throw new q(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let r=n.shape,s=r[0],a,o;this.dataFormat==="channelsFirst"?(a=2,o=3):(a=1,o=2);let i=r[a],l=r[o],u=this.kernelSize[0],c=this.kernelSize[1],d=this.strides[0],h=this.strides[1],p=Ps(i,d,u,this.padding),f=Ps(l,h,c,this.padding),m=[s,p,f,this.filters];this.dataFormat!=="channelsLast"&&(n=pt(n,[0,2,3,1]));let g=zA(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(g=pt(g,[0,3,1,2])),this.bias!=null&&(g=hs(g,this.bias.read(),this.dataFormat)),this.activation!=null&&(g=this.activation.apply(g)),g})}computeOutputShape(e){e=At(e);let t=e.slice(),n,r,s;this.dataFormat==="channelsFirst"?(n=1,r=2,s=3):(n=3,r=1,s=2);let a=this.kernelSize[0],o=this.kernelSize[1],i=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[r]=Ps(t[r],i,a,this.padding),t[s]=Ps(t[s],l,o,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};xx.className="Conv2DTranspose";ce.registerClass(xx);var bx=class extends mm{constructor(e){super(e);if(this.inputSpec=[new tn({ndim:5})],this.padding!=="same"&&this.padding!=="valid")throw new q(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=At(e),e.length!==5)throw new q("Input should have rank 5; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new q("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new tn({ndim:5,axes:{[t]:n}})],this.built=!0}call(e,t){return Z(()=>{let n=Ke(e);if(n.shape.length!==5)throw new q(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let r=n.shape,s=r[0],a,o,i;this.dataFormat==="channelsFirst"?(i=2,a=3,o=4):(i=1,a=2,o=3);let l=r[i],u=r[a],c=r[o],d=this.kernelSize[0],h=this.kernelSize[1],p=this.kernelSize[2],f=this.strides[0],m=this.strides[1],g=this.strides[2],y=Ps(l,f,d,this.padding),A=Ps(u,m,h,this.padding),x=Ps(c,g,p,this.padding),b=[s,y,A,x,this.filters];this.dataFormat!=="channelsLast"&&(n=pt(n,[0,2,3,4,1]));let v=Zj(n,this.kernel.read(),b,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(v=pt(v,[0,4,1,2,3])),this.bias!==null&&(v=hs(v,this.bias.read(),this.dataFormat)),this.activation!==null&&(v=this.activation.apply(v)),v})}computeOutputShape(e){e=At(e);let t=e.slice(),n,r,s,a;this.dataFormat==="channelsFirst"?(n=1,r=2,s=3,a=4):(n=4,r=1,s=2,a=3);let o=this.kernelSize[0],i=this.kernelSize[1],l=this.kernelSize[2],u=this.strides[0],c=this.strides[1],d=this.strides[2];return t[n]=this.filters,t[r]=Ps(t[r],u,o,this.padding),t[s]=Ps(t[s],c,i,this.padding),t[a]=Ps(t[a],d,l,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};bx.className="Conv3DTranspose";ce.registerClass(bx);var A8=class extends qd{constructor(e,t){super(e,t);if(this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new q("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new q("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 q(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=zt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=Lt(t.depthwiseRegularizer),this.depthwiseConstraint=hn(t.depthwiseConstraint),this.pointwiseInitializer=zt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=Lt(t.pointwiseRegularizer),this.pointwiseConstraint=hn(t.pointwiseConstraint)}build(e){if(e=At(e),e.length<this.rank+2)throw new q(`Inputs to SeparableConv${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 q(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],r=this.kernelSize.concat([n,this.depthMultiplier]),s=[];for(let o=0;o<this.rank;++o)s.push(1);s.push(n*this.depthMultiplier,this.filters);let a=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",r,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,a,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",s,"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 tn({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return Z(()=>{e=Ke(e);let n;if(this.rank===1)throw new Ge("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=pt(e,[0,2,3,1])),n=bI(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=hs(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=pt(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=kt(this.depthwiseRegularizer),e.pointwiseRegularizer=kt(this.pointwiseRegularizer),e.depthwiseConstraint=dn(this.depthwiseConstraint),e.pointwiseConstraint=dn(this.pointwiseConstraint),e}};A8.className="SeparableConv";var vx=class extends A8{constructor(e){super(2,e)}};vx.className="SeparableConv2D";ce.registerClass(vx);var x8=class extends qd{constructor(e){super(1,e);x8.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"&&!N1(e.kernelSize,"number",1,1))throw new q(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}},wx=x8;wx.className="Conv1D";ce.registerClass(wx);var kx=class extends st{constructor(e){super(e);typeof e.cropping=="number"?this.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:typeof e.cropping[0]=="number"?this.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:this.cropping=e.cropping,this.dataFormat=e.dataFormat===void 0?"channelsLast":e.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(e){return this.dataFormat==="channelsFirst"?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[3]-this.cropping[1][0]-this.cropping[1][1]]:[e[0],e[1]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1],e[3]]}call(e,t){return Z(()=>{if(e=Ke(e),this.dataFormat==="channelsLast"){let n=Gf(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Gf(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Gf(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Gf(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}};kx.className="Cropping2D";ce.registerClass(kx);var Ix=class extends st{constructor(e){super(e);this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=e.size==null?this.DEFAULT_SIZE:e.size,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Yt(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,uee(this.interpolation)}computeOutputShape(e){if(this.dataFormat==="channelsFirst"){let t=e[2]==null?null:this.size[0]*e[2],n=e[3]==null?null:this.size[1]*e[3];return[e[0],e[1],t,n]}else{let t=e[1]==null?null:this.size[0]*e[1],n=e[2]==null?null:this.size[1]*e[2];return[e[0],t,n,e[3]]}}call(e,t){return Z(()=>{let n=Ke(e),r=n.shape;if(this.dataFormat==="channelsFirst"){n=pt(n,[0,2,3,1]);let s=this.size[0]*r[2],a=this.size[1]*r[3],o=this.interpolation==="nearest"?n.resizeNearestNeighbor([s,a]):n.resizeBilinear([s,a]);return pt(o,[0,3,1,2])}else{let s=this.size[0]*r[1],a=this.size[1]*r[2];return this.interpolation==="nearest"?n.resizeNearestNeighbor([s,a]):n.resizeBilinear([s,a])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};Ix.className="UpSampling2D";ce.registerClass(Ix);function Xte(e,t,n=[1,1],r="valid",s,a){return Z(()=>{s==null&&(s=us()),Yt(s);let o=yx(e,s);if(e.rank!==4)throw new q(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new q(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return o=Td(o,t,n,r==="same"?"same":"valid","NHWC",a),s==="channelsFirst"&&(o=pt(o,[0,3,1,2])),o})}var Sx=class extends Ax{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=zt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=hn(e.depthwiseConstraint),this.depthwiseRegularizer=Lt(e.depthwiseRegularizer)}build(e){if(e=At(e),e.length<4)throw new q(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new q(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],r=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",r,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[n*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return Z(()=>{e=Ke(e);let n=Xte(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=hs(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=At(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,s=ms(t,this.kernelSize[0],this.padding,this.strides[0]),a=ms(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],r,s,a]:[e[0],s,a,r]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=Ht(this.depthwiseInitializer),e.depthwiseRegularizer=kt(this.depthwiseRegularizer),e.depthwiseConstraint=dn(this.depthwiseRegularizer),e}};Sx.className="DepthwiseConv2D";ce.registerClass(Sx);function b8(e,t,n,r){if(Array.isArray(e)){if(t!=null||n!=null)throw new q("When inputs is an array, neither initialState or constants should be provided");r!=null&&(n=e.slice(e.length-r,e.length),e=e.slice(0,e.length-r)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function s(a){return a==null||Array.isArray(a)?a:[a]}return t=s(t),n=s(n),{inputs:e,initialState:t,constants:n}}function v8(e,t,n,r=!1,s,a,o=!1,i=!1){return Z(()=>{let l=t.shape.length;if(l<3)throw new q(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(ds(2,l));if(t=pt(t,u),a!=null)throw new Ge("The rnn() functoin of the deeplearn.js backend does not support constants yet.");o&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),s!=null&&(s=s.asType("bool").asType("float32"),s.rank===l-1&&(s=$r(s,-1)),s=pt(s,u)),r&&(t=Fr(t,0),s!=null&&(s=Fr(s,0)));let c=[],d,h=n,p=t.shape[0],f=ls(t),m;s!=null&&(m=ls(s));for(let y=0;y<p;++y){let A=f[y],x=Z(()=>e(A,h));if(s==null)d=x[0],h=x[1];else{let b=Z(()=>{let v=m[y],w=Dr(v).sub(v),I=x[0].mul(v).add(h[0].mul(w)),T=h.map((C,M)=>x[1][M].mul(v).add(C.mul(w)));return{output:I,newStates:T}});d=b.output,h=b.newStates}i&&c.push(d)}let g;return i&&(g=Mr(c,1)),[d,g,h]})}var w8=class extends st{constructor(e){super(e);let t;if(e.cell==null)throw new q("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Am({cells:e.cell}):t=e.cell,t.stateSize==null)throw new q("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 tn({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 ds(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){H1(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],r;if(this.returnSequences?r=[e[0],e[1],n]:r=[e[0],n],this.returnState){let s=[];for(let a of t)s.push([e[0],a]);return[r].concat(s)}else return r}computeMask(e,t){return Z(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let r=this.states.map(s=>null);return[n].concat(r)}else return n})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;n<e;++n)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){let t=null;if(this.numConstants!=null)throw new Ge("Constants support is not implemented in RNN yet.");H1(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,r=e.slice(2);this.inputSpec[0]=new tn({shape:[n,null,...r]});let s=[e[0]].concat(e.slice(2));if(t!=null)throw new Ge("Constants support is not implemented in RNN yet.");this.cell.build(s);let a;if(Array.isArray(this.cell.stateSize)?a=this.cell.stateSize:a=[this.cell.stateSize],this.stateSpec!=null){if(!k.arraysEqual(this.stateSpec.map(o=>o.shape[o.shape.length-1]),a))throw new q(`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 tn({shape:[null,o]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){Z(()=>{if(!this.stateful)throw new da("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new q("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.states_==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>un([n,r])):this.states_=[un([n,this.cell.stateSize])];else if(e==null)je(this.states_),this.keptStates!=null&&(je(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>un([n,r])):this.states_[0]=un([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new q(`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()):je(this.states_);for(let r=0;r<this.states_.length;++r){let s=e[r],a=Array.isArray(this.cell.stateSize)?this.cell.stateSize[r]:this.cell.stateSize,o=[n,a];if(!k.arraysEqual(s.shape,o))throw new q(`State ${r} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${s.shape}`);this.states_[r]=s}}this.states_=this.states_.map(r=>Sn(r.clone()))})}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let s=b8(e,n,r,this.numConstants);e=s.inputs,n=s.initialState,r=s.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 tn({shape:l.shape}));o=o.concat(this.stateSpec)}if(r!=null&&(t.constants=r,a=a.concat(r),this.numConstants=r.length),a[0]instanceof ps){let l=[e].concat(a),u=this.inputSpec.concat(o),c=this.inputSpec;this.inputSpec=u;let d=super.apply(l,t);return this.inputSpec=c,d}else return super.apply(e,t)}call(e,t){return Z(()=>{let n=t==null?null:t.mask,r=t==null?null:t.training,s=t==null?null:t.initialState;e=Ke(e),s==null&&(this.stateful?s=this.states_:s=this.getInitialState(e));let a=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(s.length!==a)throw new q(`RNN Layer has ${a} state(s) but was passed ${s.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let o={training:r},l=v8((p,f)=>{let m=this.cell.call([p].concat(f),o);return[m[0],m.slice(1)]},e,s,this.goBackwards,n,null,this.unroll,this.returnSequences),u=l[0],c=l[1],d=l[2];this.stateful&&this.resetStates(d,r);let h=this.returnSequences?c:u;return this.returnState?[h].concat(d):h})}getInitialState(e){return Z(()=>{let t=un(e.shape);return t=_e(t,[1,2]),t=Ld(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?M1(t,[1,n]):t):this.cell.stateSize>1?[M1(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()===w8.className&&(t.cell={className:this.cell.getClassName(),config:n}),{...n,...e,...t}}static fromConfig(e,t,n={}){let r=t.cell,s=fs(r,n);return new e(Object.assign(t,{cell:s}))}},fa=w8;fa.className="RNN";ce.registerClass(fa);var Kd=class extends st{},gm=class extends Kd{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,An(this.units,"units"),this.activation=Za(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=zt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=zt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=zt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=Lt(e.kernelRegularizer),this.recurrentRegularizer=Lt(e.recurrentRegularizer),this.biasRegularizer=Lt(e.biasRegularizer),this.kernelConstraint=hn(e.kernelConstraint),this.recurrentConstraint=hn(e.recurrentConstraint),this.biasConstraint=hn(e.biasConstraint),this.dropout=ru([1,qa([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=ru([1,qa([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=At(e),this.kernel=this.addWeight("kernel",[e[e.length-1],this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return Z(()=>{if(e=e,e.length!==2)throw new q(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let r=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Ya({ones:()=>Dr(e),rate:this.dropout,training:r})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Ya({ones:()=>Dr(n),rate:this.recurrentDropout,training:r}));let s,a=this.dropoutMask,o=this.recurrentDropoutMask;a!=null?s=Fs(K(e,a),this.kernel.read()):s=Fs(e,this.kernel.read()),this.bias!=null&&(s=hs(s,this.bias.read())),o!=null&&(n=K(n,o));let i=pe(s,Fs(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:Xa(this.activation),useBias:this.useBias,kernelInitializer:Ht(this.kernelInitializer),recurrentInitializer:Ht(this.recurrentInitializer),biasInitializer:Ht(this.biasInitializer),kernelRegularizer:kt(this.kernelRegularizer),recurrentRegularizer:kt(this.recurrentRegularizer),biasRegularizer:kt(this.biasRegularizer),activityRegularizer:kt(this.activityRegularizer),kernelConstraint:dn(this.kernelConstraint),recurrentConstraint:dn(this.recurrentConstraint),biasConstraint:dn(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return{...e,...t}}};gm.className="SimpleRNNCell";ce.registerClass(gm);var Tx=class extends fa{constructor(e){e.cell=new gm(e),super(e)}call(e,t){return Z(()=>{this.cell.dropoutMask!=null&&(je(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(je(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:s})})}static fromConfig(e,t){return new e(t)}};Tx.className="SimpleRNN";ce.registerClass(Tx);var ym=class extends Kd{constructor(e){super(e);if(this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.resetAfter)throw new q("GRUCell does not support reset_after parameter set to true.");this.units=e.units,An(this.units,"units"),this.activation=Za(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Za(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=zt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=zt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=zt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=Lt(e.kernelRegularizer),this.recurrentRegularizer=Lt(e.recurrentRegularizer),this.biasRegularizer=Lt(e.biasRegularizer),this.kernelConstraint=hn(e.kernelConstraint),this.recurrentConstraint=hn(e.recurrentConstraint),this.biasConstraint=hn(e.biasConstraint),this.dropout=ru([1,qa([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=ru([1,qa([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=At(e);let t=e[e.length-1];this.kernel=this.addWeight("kernel",[t,this.units*3],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*3],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units*3],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return Z(()=>{if(e=e,e.length!==2)throw new q(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,r=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Ya({ones:()=>Dr(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Ya({ones:()=>Dr(r),rate:this.recurrentDropout,training:n,count:3}));let s=this.dropoutMask,a=this.recurrentDropoutMask,o,i,l;0<this.dropout&&this.dropout<1&&(e=K(e,s[0]));let u=Fs(e,this.kernel.read());this.useBias&&(u=hs(u,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(r=K(r,a[0]));let c=this.recurrentKernel.read(),[d,h]=dr(c,[2*this.units,this.units],c.rank-1),p=Fs(r,d),[f,m,g]=dr(u,3,u.rank-1),[y,A]=dr(p,2,p.rank-1);o=this.recurrentActivation.apply(pe(f,y)),i=this.recurrentActivation.apply(pe(m,A));let x=Fs(K(i,r),h);l=this.activation.apply(pe(g,x));let b=pe(K(o,r),K(pe(1,Kt(o)),l));return[b,b]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Xa(this.activation),recurrentActivation:Xa(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Ht(this.kernelInitializer),recurrentInitializer:Ht(this.recurrentInitializer),biasInitializer:Ht(this.biasInitializer),kernelRegularizer:kt(this.kernelRegularizer),recurrentRegularizer:kt(this.recurrentRegularizer),biasRegularizer:kt(this.biasRegularizer),activityRegularizer:kt(this.activityRegularizer),kernelConstraint:dn(this.kernelConstraint),recurrentConstraint:dn(this.recurrentConstraint),biasConstraint:dn(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return{...e,...t}}};ym.className="GRUCell";ce.registerClass(ym);var Nx=class extends fa{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. 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Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>un(s)):this.states_=[un(s)];else if(e==null)je(this.states_),this.keptStates!=null&&(je(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>un(s)):this.states_[0]=un(s);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new q(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t?this.keptStates.push(this.states_.slice()):je(this.states_);for(let o=0;o<this.states_.length;++o){let i=e[o],l=s;if(!k.arraysEqual(i.shape,l))throw new q(`State ${o} is incompatible with layer ${this.name}: expected shape=${l}, received shape=${i.shape}`);this.states_[o]=i}}this.states_=this.states_.map(o=>Sn(o.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:r,padding:s,strides:a,dilationRate:o}=this.cell,i=t==="channelsFirst",l=e[i?3:2],u=e[i?4:3],c=ms(l,r[0],s,a[0],o[0]),d=ms(u,r[1],s,a[1],o[1]);return[...e.slice(0,2),...i?[n,c,d]:[c,d,n]]}};k8.className="ConvRNN2D";var xm=class extends Xd{constructor(e){let{filters:t,kernelSize:n,strides:r,padding:s,dataFormat:a,dilationRate:o}=e;super({...e,units:t});this.filters=t,An(this.filters,"filters"),this.kernelSize=iu(n,2,"kernelSize"),this.kernelSize.forEach(i=>An(i,"kernelSize")),this.strides=iu(r||1,2,"strides"),this.strides.forEach(i=>An(i,"strides")),this.padding=s||"valid",Or(this.padding),this.dataFormat=a||"channelsLast",Yt(this.dataFormat),this.dilationRate=iu(o||1,2,"dilationRate"),this.dilationRate.forEach(i=>An(i,"dilationRate"))}build(e){var t;e=At(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new q(`The channel dimension of the input should be defined. Found ${e[n]}`);let r=e[n],s=4,a=this.kernelSize.concat([r,this.filters*s]);this.kernel=this.addWeight("kernel",a,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let o=this.kernelSize.concat([this.filters,this.filters*s]);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 Zr{apply(c,d){let h=l.apply([u]),p=la([u]),f=l.apply([u*2]);return F1([h,p,f])}},t.className="CustomInit",t)}else i=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*s],null,i,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return Z(()=>{if(e.length!==3)throw new q(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,r=e[0],s=e[1],a=e[2],o=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Ya({ones:()=>Dr(r),rate:this.dropout,training:n,count:o}));let i=this.dropoutMask,l=(ee,oe,se)=>!oe||!oe[se]?ee:K(oe[se],ee),u=l(r,i,0),c=l(r,i,1),d=l(r,i,2),h=l(r,i,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Ya({ones:()=>Dr(s),rate:this.recurrentDropout,training:n,count:o}));let p=this.recurrentDropoutMask,f=l(s,p,0),m=l(s,p,1),g=l(s,p,2),y=l(s,p,3),A=3,[x,b,v,w]=dr(this.kernel.read(),o,A),[I,T,C,M]=this.useBias?dr(this.bias.read(),o):[null,null,null,null];u=this.inputConv(u,x,I,this.padding),c=this.inputConv(c,b,T,this.padding),d=this.inputConv(d,v,C,this.padding),h=this.inputConv(h,w,M,this.padding);let[$,R,N,F]=dr(this.recurrentKernel.read(),o,A);f=this.recurrentConv(f,$),m=this.recurrentConv(m,R),g=this.recurrentConv(g,N),y=this.recurrentConv(y,F);let B=this.recurrentActivation.apply(pe(u,f)),j=this.recurrentActivation.apply(pe(c,m)),X=pe(K(j,a),K(B,this.activation.apply(pe(d,g)))),Y=K(this.recurrentActivation.apply(pe(h,y)),this.activation.apply(X));return[Y,Y,X]})}getConfig(){let{units:e,...t}=super.getConfig(),n={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return{...t,...n}}inputConv(e,t,n,r){let s=Ba(e,t,this.strides,r||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?hs(s,n,this.dataFormat):s}recurrentConv(e,t){return Ba(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};xm.className="ConvLSTM2DCell";ce.registerClass(xm);var Ex=class extends k8{constructor(e){let t=new xm(e);super({...e,cell:t})}static fromConfig(e,t){return new e(t)}};Ex.className="ConvLSTM2D";ce.registerClass(Ex);var bm=class extends st{constructor(e){super(e);this.rate=Math.max(Math.min(e.rate,1),0),this.noiseShape=e.noiseShape,this.seed=e.seed,this.supportsMasking=!0}getNoiseShape(e){if(this.noiseShape==null)return this.noiseShape;let t=e.shape,n=[];for(let r=0;r<this.noiseShape.length;++r)n.push(this.noiseShape[r]==null?t[r]:this.noiseShape[r]);return n}call(e,t){return Z(()=>{this.invokeCallHook(e,t);let n=Ke(e);if(0<this.rate&&this.rate<1){let r=t.training==null?!1:t.training,s=this.getNoiseShape(n);return Wd(()=>mS(n,this.rate,s,this.seed),()=>n,r)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};bm.className="Dropout";ce.registerClass(bm);var $x=class extends bm{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};$x.className="SpatialDropout1D";ce.registerClass($x);var _x=class extends st{constructor(e){super(e);if(this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.batchInputShape==null&&e.inputShape==null&&e.inputDim!=null){let t=null;e.batchSize!=null&&(t=e.batchSize),this.batchInputShape=[t,e.inputDim]}this.units=e.units,An(this.units,"units"),this.activation=Za(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=zt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=zt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=hn(e.kernelConstraint),this.biasConstraint=hn(e.biasConstraint),this.kernelRegularizer=Lt(e.kernelRegularizer),this.biasRegularizer=Lt(e.biasRegularizer),this.activityRegularizer=Lt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=At(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=At(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return Z(()=>{this.invokeCallHook(e,t);let n=Ke(e),r=sS(this.activation.getClassName()),s;return r!=null?s=Fs(n,this.kernel.read(),r,this.bias?this.bias.read():null):(s=Fs(n,this.kernel.read()),this.bias!=null&&(s=hs(s,this.bias.read())),this.activation!=null&&(s=this.activation.apply(s))),s})}getConfig(){let e={units:this.units,activation:Xa(this.activation),useBias:this.useBias,kernelInitializer:Ht(this.kernelInitializer),biasInitializer:Ht(this.biasInitializer),kernelRegularizer:kt(this.kernelRegularizer),biasRegularizer:kt(this.biasRegularizer),activityRegularizer:kt(this.activityRegularizer),kernelConstraint:dn(this.kernelConstraint),biasConstraint:dn(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};_x.className="Dense";ce.registerClass(_x);var Rx=class extends st{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=At(e);for(let t of e.slice(1))if(t==null)throw new q(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). 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Z(()=>(e=Ke(e),pee(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};Fx.className="RepeatVector";ce.registerClass(Fx);var Mx=class extends st{constructor(e){super(e);this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let n="Total size of new array must be unchanged.",r=t.slice(),s=1,a=null;for(let i=0;i<r.length;++i){let l=r[i];if(this.isUnknown(l))if(a===null)a=i;else throw new q("Can only specifiy one unknown dimension.");else s*=l}let o=ja(e);if(a!==null){if(s===0||o%s!=0)throw new q(n);r[a]=o/s}else if(o!==s)throw new q(n);return r}computeOutputShape(e){let t=!1;for(let n=0;n<e.length;++n)if(this.isUnknown(e[n])){t=!0;break}return t?e.slice(0,1).concat(this.targetShape):e.slice(0,1).concat(this.fixUnknownDimension(e.slice(1),this.targetShape))}call(e,t){return Z(()=>{this.invokeCallHook(e,t);let n=Ke(e),r=n.shape,s=r.slice(0,1).concat(this.fixUnknownDimension(r.slice(1),this.targetShape));return n.reshape(s)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};Mx.className="Reshape";ce.registerClass(Mx);var Ox=class extends st{constructor(e){super(e);if(e.dims==null)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(e.dims))throw new Error(`Permute constructor requires \`dims\` to be an Array, but received ${e.dims} instead.`);let t=ds(1,e.dims.length+1);if(!k.arraysEqual(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new tn({ndim:this.dims.length+1})]}computeOutputShape(e){e=At(e);let t=e.slice();return this.dims.forEach((n,r)=>{t[r+1]=e[n]}),t}call(e,t){return 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i;if(e.shape.length===2&&t.shape.length===2)a[0]===a[1]?i=e.mul(t).sum(a[0]):i=e.transpose([1,0]).mul(t).sum(a[1]);else{let l=a[0]!==e.shape.length-1,u=a[1]===t.shape.length-1;i=e.matMul(t,l,u)}if(o>0){let l;r>s?l=r+s-3:l=r-1;let u=[];for(let c=l;c<l+o;++c)u.push(c);i=i.squeeze(u)}return i.shape.length===1&&(i=i.expandDims(1)),i})}var Gx=class extends hi{constructor(e){super(e);this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){k.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],n=e[1];if(t.length>3||n.length>3)throw new Ge("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);if(t[r[0]]!==n[r[1]])throw new q(`Dimension incompatibility: ${t[r[0]]} !== ${n[r[1]]}`)}mergeFunction(e){if(e.length!==2)throw new q(`A \`Dot\` layer must be called on exactly 2 inputs, but 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jx=class extends st{constructor(e){super(e);this.supportsMasking=!0,this.stddev=e.stddev}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={stddev:this.stddev};return Object.assign(t,e),t}call(e,t){return Z(()=>{this.invokeCallHook(e,t);let n=Ke(e);return Wd(()=>jf(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};jx.className="GaussianNoise";ce.registerClass(jx);var qx=class extends st{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return Z(()=>{this.invokeCallHook(e,t);let n=Ke(e);return this.rate>0&&this.rate<1?Wd(()=>{let s=Math.sqrt(this.rate/(1-this.rate));return n.mul(jf(n.shape,1,s))},()=>n,t.training||!1):n})}};qx.className="GaussianDropout";ce.registerClass(qx);var Kx=class extends st{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return 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pse(a,o,i);case"evaluation":return Z(()=>fse(a,o,i));case"image":return Z(()=>Ase(a,o,i));case"graph":return Z(()=>mse(a,o,i));case"logical":return Z(()=>xse(a,o,i));case"matrices":return Z(()=>bse(a,o,i));case"normalization":return Z(()=>vse(a,o,i));case"reduction":return Z(()=>wse(a,o,i));case"slice_join":return Z(()=>kse(a,o,i));case"sparse":return Z(()=>Ise(a,o,i));case"spectral":return Z(()=>Sse(a,o,i));case"string":return Z(()=>Tse(a,o,i));case"transformation":return Z(()=>Nse(a,o,i));case"hash_table":return yse(a,o,i,r);case"custom":let l=V8(a.op);if(l&&l.customExecutor)return l.customExecutor(new nse(a,o,i));throw TypeError(`Custom op ${a.op} is not registered.`);default:throw TypeError(`Unknown op '${a.op}'. 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e?e.map(t=>t.id===0&&t.iterationId===0?"":`${t.frameName}-${t.iterationId}`).join("/"):""}enterFrame(e){this.contexts&&(this.lastId++,this.contexts=this.contexts.slice(),this.contexts.push(this.newFrame(this.lastId,e)),this._currentContextIds.unshift(this.contextIdforContexts(this.contexts)))}exitFrame(){if(this.contexts&&this.contexts.length>1)this.contexts=this.contexts.slice(),this.contexts.splice(-1),this.currentContextIds.shift();else throw new Error("Cannot exit frame, the context is empty")}nextIteration(){if(this.contexts&&this.contexts.length>0){this.contexts=this.contexts.slice(),this.lastId++;let e=Object.assign({},this.contexts[this.contexts.length-1]);e.iterationId+=1,e.id=this.lastId,this.contexts.splice(-1,1,e),this._currentContextIds.splice(0,1,this.contextIdforContexts(this.contexts))}else throw new Error("Cannot increase frame iteration, the context is empty")}getWeight(e){return this.weightMap[e]}addTensorArray(e){this.tensorArrayMap[e.id]=e}getTensorArray(e){return this.tensorArrayMap[e]}addTensorList(e){this.tensorListMap[e.id]=e}getTensorList(e){return this.tensorListMap[e]}dispose(e){for(let t in this.tensorArrayMap)this.tensorArrayMap[t].clearAndClose(e);for(let t in this.tensorListMap)this.tensorListMap[t].clearAndClose(e)}};function gT(e,t,n,r){let s=new Set,a=[],o=null,i=null,l=new Set,u=Object.keys(e).map(h=>hr(h)[0]),c=[];r!=null&&(c=r.map(h=>hr(h.name)[0]));let d=[...t];for(;d.length>0;){let h=d.pop();if((yT(h)||Rse(h)||Dse(h))&&o==null&&(o=h,i=o.children.map(p=>p.name).filter(p=>s.has(p))),s.add(h.name),n[h.name]==null&&u.indexOf(h.name)===-1&&c.indexOf(h.name)===-1){if(h.inputs.length===0){a.push(h.name);continue}h.inputs.forEach(p=>{l.has(p.name)||(l.add(p.name),d.push(p))})}}return{inputs:e,outputs:t,usedNodes:s,missingInputs:a,dynamicNode:o,syncInputs:i}}function Cse(e,t,n){let{usedNodes:r,inputs:s}=n,a=[],o=Object.keys(s).map(c=>hr(c)[0]).map(c=>e.nodes[c]),i=e.initNodes;o.forEach(c=>{r.has(c.name)&&a.push(c)}),e.weights.forEach(c=>{r.has(c.name)&&a.push(c)}),i!=null&&i.forEach(c=>{r.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(d=>{!l.has(d.name)&&r.has(d.name)&&d.inputs.every(h=>l.has(h.name))&&a.push(d)})}return u}var Ese=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],$se=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],_se=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function yT(e){return Ese.indexOf(e.op)>=0}function Rse(e){return $se.indexOf(e.op)>=0}function Dse(e){return _se.indexOf(e.op)>=0}var N5=class{constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,e.functions!=null&&Object.keys(e.functions).forEach(n=>{this._functionExecutorMap[n]=new N5(e.functions[n],this)})}get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){let t=Object.keys(e).map(n=>e[n].map(r=>r.id));this._weightIds=[].concat(...t),this._weightMap=e}set resourceManager(e){this._resourceManager=e}get inputs(){return this._inputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(e=>e.signatureKey||e.name)}get outputNodes(){return this._outputs.map(e=>{let t=e.signatureKey||e.name;return e.defaultOutput?`${t}:${e.defaultOutput}`:t})}get functions(){return Object.keys(this._functions).reduce((e,t)=>(e[t]=this._functions[t].signature,e),{})}getCompilationKey(e,t){let n=e.map(s=>s.name).sort(),r=t.map(s=>s.name).sort();return n.join(this.SEPERATOR)+"--"+r.join(this.SEPERATOR)}compile(e,t){let n=gT(e,t,this.weightMap,this._initNodes),{missingInputs:r,dynamicNode:s,syncInputs:a}=n;if(s!=null)throw new Error(`This execution contains the node '${s.name}', which has the dynamic op '${s.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${a}]`);if(r.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: [${r}]`)}return Cse(this.graph,this.weightMap,n)}execute(e,t){e=this.mapInputs(e);let n=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let r=n.map(c=>this.graph.nodes[hr(c)[0]]),s=t.map(c=>hr(c)[0]),a=s.map(c=>this.graph.nodes[c]);a.length===0&&(a=this._outputs);let o=this.getCompilationKey(r,a),i=this.compiledMap.get(o);i==null&&(i=this.compile(e,a),this.compiledMap.set(o,i));let l={},u={};return Z(()=>{let c=new mT(this.weightMap,l,u,this.functionExecutorMap),d={...this.weightMap};Object.keys(e).forEach(f=>{let[m,g]=hr(f),y=[];y[g]=e[f],d[m]=y});let h=this.getFrozenTensorIds(d),p={};for(let f=0;f<i.length;f++){let m=i[f];if(!d[m.name]){let g=fT(m,d,c,this._resourceManager);if(k.isPromise(g))throw new Error(`The execution of the op '${m.op}' returned a promise. 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You can use model.execute() instead.");let y=i.filter(A=>!yT(A)&&!Bn(A.name,p,t)).map(A=>A.name);if(y.length>0){let A="";throw c!=null&&(A=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${d}]`),new Error(`Cannot compute the outputs [${y}] from the provided inputs [${s}]. 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u}processChildNodes(e,t,n,r,s,a){e.children.forEach(o=>{let[i]=ma(o.name,n);s[i]||!a.has(o.name)||(o.op==="Merge"?o.inputNames.some(l=>!!Bn(l,r,n))&&(s[i]=!0,t.push({contexts:n.currentContext,node:o})):o.inputNames.every(l=>!!Bn(l,r,n))&&(s[i]=!0,t.push({contexts:n.currentContext,node:o})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let n=e[t],[r]=hr(t),s=this.graph.nodes[r];if(s.attrParams.shape&&s.attrParams.shape.value){let a=s.attrParams.shape.value,o=a.length===n.shape.length&&n.shape.every((i,l)=>a[l]===-1||a[l]===i);k.assert(o,()=>`The shape of dict['${s.name}'] provided in model.execute(dict) must be [${a}], but was [${n.shape}]`)}s.attrParams.dtype&&s.attrParams.dtype.value&&k.assert(n.dtype===s.attrParams.dtype.value,()=>`The dtype of dict['${s.name}'] provided in model.execute(dict) must be ${s.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(e){let t={};for(let n in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let r=this._signature.inputs[n];t[r.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[r]=hr(n);return this.graph.nodes[r]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${t}] that are not part of graph`)}mapOutputs(e){return e.map(t=>this._signature!=null&&this._signature.outputs!=null&&this._signature.outputs[t]!=null?this._signature.outputs[t].name:t,{})}checkOutputs(e){e.forEach(t=>{let[n]=hr(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}},Fse=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},Mse="?tfjs-format=file",Ose="model.json",AT=class{constructor(e,t={}){this.modelUrl=e,this.loadOptions=t,this.version="n/a",t==null&&(this.loadOptions={}),this.resourceManager=new Fse}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=ur.browserHTTPRequest(e,this.loadOptions);else{let t=ur.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(ur.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}async load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=await this.handler.load();return this.loadSync(e)}loadSync(e){this.artifacts=e;let t=this.artifacts.modelTopology,n;this.artifacts.userDefinedMetadata!=null&&this.artifacts.userDefinedMetadata.signature!=null?n=this.artifacts.userDefinedMetadata.signature:n=this.artifacts.signature,this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;let r=ur.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new N5(lT.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let s=lT.Instance.transformGraph(e.modelInitializer);this.initializer=new N5(s),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=ur.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${e}'`);if(n.length>1)throw new Error(`Found more than one (${n.length}) save handlers for URL '${e}'`);e=n[0]}if(e.save==null)throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");return e.save(this.artifacts)}predict(e,t){return this.execute(e,this.outputNodes)}normalizeInputs(e){if(!(e instanceof Ct)&&!Array.isArray(e))return e;if(e=Array.isArray(e)?e:[e],e.length!==this.inputNodes.length)throw new Error(`Input tensor count mismatch,the graph model has ${this.inputNodes.length} placeholders, while there are ${e.length} input tensors.`);return this.inputNodes.reduce((t,n,r)=>(t[n]=e[r],t),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,n)=>(t[n]=[e[n]],t),{})}dispose(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}};async function Et(e,t={}){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");t==null&&(t={}),t.fromTFHub&&e.load==null&&(e.endsWith("/")||(e=e+"/"),e=`${e}${Ose}${Mse}`);let n=new AT(e,t);return await n.load(),n}var Pse="3.7.0",xT={};De(xT,{CSVDataset:()=>DT,Dataset:()=>uu,FileDataSource:()=>BT,TextLineDataset:()=>$T,URLDataSource:()=>WT,array:()=>oae,csv:()=>yae,func:()=>Aae,generator:()=>xae,microphone:()=>vae,version_data:()=>wae,webcam:()=>bae,zip:()=>iae});var zse=Ks(z3()),Lse=Ks(z3());function Bse(e,t){return Sm(e,t)}function Sm(e,t,n=new Map,r=new Set){if(e==null)return null;if(r.has(e))throw new Error("Circular references are not supported.");if(n.has(e))return n.get(e);let s=t(e);if(s.recurse&&s.value!==null)throw new Error("A deep map function may not return both a value and recurse=true.");if(s.recurse)if(lu(e)){let a=Array.isArray(e)?[]:{};r.add(e);for(let o in e){let i=e[o],l=Sm(i,t,n,r);a[o]=l}return r.delete(e),a}else throw new Error(`Can't recurse into non-iterable type: ${e}`);else 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xn{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}},Tm;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(Tm||(Tm={}));var sae=class extends xn{constructor(e,t=0){super();this.iterators=e,this.mismatchMode=t,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(e){await e;let t=0,n=0;function r(a){return a instanceof 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Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},FT=class extends xn{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(ae().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new FT(e);return await t.start(),t}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(n){throw new Error(`Error thrown while initializing video stream: ${n.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let e=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new e,!this.sampleRateHz)this.sampleRateHz=this.audioContext.sampleRate;else if(this.audioContext.sampleRate!==this.sampleRateHz)throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);let t=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,t.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let e,t,n=await this.getAudioData();if(this.includeSpectrogram){let r=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(r,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let r=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(r,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:e,waveform:t},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let e=[],t=[],n=0;return new Promise(r=>{let s=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-Infinity&&r({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(s),r({freqDataQueue:e,timeDataQueue:t}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(e){let t=e[0].length,n=new Float32Array(e.length*t);return e.forEach((r,s)=>n.set(r,s*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(k.sizeFromShape(t));return n.set(e,n.length-e.length),$s(n,t)}},MT=class extends xn{constructor(e,t){super();if(this.webcamVideoElement=e,this.webcamConfig=t,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=_n([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,r=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,s=(1-n)/2,a=(1-r)/2,o=s+n,i=r+a;this.cropBox=Ql([a,s,i,o],[1,4])}else this.cropBox=Ql([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(ae().get("IS_NODE"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new MT(e,t);return await n.start(),n}async start(){this.webcamConfig.facingMode&&k.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);try{this.stream=await navigator.mediaDevices.getUserMedia({video:{deviceId:this.webcamConfig.deviceId,facingMode:this.webcamConfig.facingMode?this.webcamConfig.facingMode:"user",width:this.webcamVideoElement.width,height:this.webcamVideoElement.height}})}catch(e){throw e.message=`Error thrown while initializing video stream: ${e.message}`,e}if(!this.stream)throw new Error("Could not obtain video from webcam.");try{this.webcamVideoElement.srcObject=this.stream}catch(e){console.log(e),this.webcamVideoElement.src=window.URL.createObjectURL(this.stream)}return this.webcamVideoElement.play(),this.isClosed=!1,new Promise(e=>{this.webcamVideoElement.onloadedmetadata=()=>{e()}})}async next(){if(this.isClosed)return{value:null,done:!0};let e;try{e=k6.fromPixels(this.webcamVideoElement)}catch(t){throw new Error(`Error thrown converting video to pixels: ${JSON.stringify(t)}`)}if(this.resize)try{return{value:this.cropAndResizeFrame(e),done:!1}}catch(t){throw new Error(`Error thrown cropping the video: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return Z(()=>{let t=$r(ke(e,"float32"),0),n;n=ni.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let r=n.shape;return J(n,r.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(t=>t.stop());try{this.webcamVideoElement.srcObject=null}catch(t){console.log(t),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},OT=class{},PT=class extends xn{split(e){return new cae(this,e)}},cae=class extends PT{constructor(e,t){super();this.upstream=e,this.impl=new dae(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},dae=class extends E5{constructor(e,t){super();this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let n of t.slice(0,-1))this.outputQueue.push(n);return this.carryover=t[t.length-1],!0}},hae=class extends xn{decodeUTF8(){return new pae(this)}},pae=class extends PT{constructor(e){super();this.upstream=e,this.impl=new fae(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},fae=class extends E5{constructor(e){super();if(this.upstream=e,ae().get("IS_BROWSER"))this.decoder=new 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============================
Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, which binds to TensorFlow C++, by running npm i @tensorflow/tfjs-node, or npm i @tensorflow/tfjs-node-gpu if you have CUDA. Then call require('@tensorflow/tfjs-node'); (-gpu suffix for CUDA) at the start of your program. Visit https://github.com/tensorflow/tfjs-node for more details.
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dt=0;for(let bt=ze;bt<vt;bt++){let Je=Math.min(be,g-1)*X,jn=Math.min(be,y-1)*ie,Wt=N[Je+ft*Y+bt*ee],sr=F[bt*oe+mt*se+jn];dt+=Wt*sr}he[be*ne+(ft*$+mt)]+=dt}}return n.disposeIntermediateTensorInfo(I),n.disposeIntermediateTensorInfo(T),n.makeTensorInfo(b,de.dtype,de.values)}var Noe={kernelName:Qi,backendName:"cpu",kernelFunc:MN};function Coe(e){let{inputs:t,backend:n,attrs:r}=e,{a:s,b:a,bias:o,preluActivationWeights:i}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:d}=r,h,p,f,m=[];h=MN({inputs:{a:s,b:a},attrs:{transposeA:l,transposeB:u},backend:n}),o&&(p=th({inputs:{a:h,b:o},backend:n}),m.push(h),h=p),c&&(f=z5(n,h,c,i,d),m.push(h),h=f);for(let y of m)n.disposeIntermediateTensorInfo(y);return h}var Eoe={kernelName:Ll,backendName:"cpu",kernelFunc:Coe},$oe=xt(bc,e=>Math.acos(e)),_oe={kernelName:bc,backendName:"cpu",kernelFunc:$oe},Roe=xt(vc,e=>Math.acosh(e)),Doe={kernelName:vc,backendName:"cpu",kernelFunc:Roe};function Foe(e){let{inputs:t,backend:n}=e,r=t;Te(t,"addN");let s=r.map(i=>n.data.get(i.dataId).values),a=Le(r[0].shape,r[0].dtype),o=a.values;for(let i=0;i<r.length;i++){let l=s[i];for(let u=0;u<o.length;u++)o[u]+=l[u]}return n.makeTensorInfo(a.shape,a.dtype,a.values)}var Moe={kernelName:Zi,backendName:"cpu",kernelFunc:Foe};function Ooe(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{axis:a,keepDims:o}=r;Te(s,"all");let i=k.parseAxisParam(a,s.shape),l=i,u=_.getAxesPermutation(l,s.shape.length),c=s;u!=null&&(c=Pr({inputs:{x:s},backend:n,attrs:{perm:u}}),l=_.getInnerMostAxes(l.length,s.shape.length)),_.assertAxesAreInnerMostDims("all",l,c.shape.length);let[d,h]=_.computeOutAndReduceShapes(c.shape,l),p=k.sizeFromShape(h),f=k.makeZerosTypedArray(k.sizeFromShape(d),c.dtype),m=n.data.get(c.dataId).values;for(let y=0;y<f.length;++y){let A=y*p,x=m[A];for(let b=0;b<p;++b){let v=m[A+b];x=x&&v}f[y]=x}u!=null&&n.disposeIntermediateTensorInfo(c);let g=n.makeTensorInfo(d,c.dtype,f);if(o){let y=_.expandShapeToKeepDim(d,i),A=Ft({inputs:{x:g},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(g),A}return g}var Poe={kernelName:wc,backendName:"cpu",kernelFunc:Ooe};function zoe(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{axis:a,keepDims:o}=r;Te(s,"any");let i=k.parseAxisParam(a,s.shape),l=i,u=_.getAxesPermutation(l,s.shape.length),c=s;u!=null&&(c=Pr({inputs:{x:s},backend:n,attrs:{perm:u}}),l=_.getInnerMostAxes(l.length,s.shape.length)),_.assertAxesAreInnerMostDims("any",l,c.shape.length);let[d,h]=_.computeOutAndReduceShapes(c.shape,l),p=k.sizeFromShape(h),f=k.makeZerosTypedArray(k.sizeFromShape(d),c.dtype),m=n.data.get(c.dataId).values;for(let y=0;y<f.length;++y){let A=y*p,x=m[A];for(let b=0;b<p;++b){let v=m[A+b];x=x||v}f[y]=x}u!=null&&n.disposeIntermediateTensorInfo(c);let g=n.makeTensorInfo(d,c.dtype,f);if(o){let y=_.expandShapeToKeepDim(d,i),A=Ft({inputs:{x:g},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(g),A}return g}var Loe={kernelName:kc,backendName:"cpu",kernelFunc:zoe};function Boe(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{axis:a}=r;Te(s,"argMax");let o=k.parseAxisParam(a,s.shape),i=_.getAxesPermutation(o,s.shape.length),l=s,u=[];i!=null&&(l=Pr({inputs:{x:s},backend:n,attrs:{perm:i}}),u.push(l),o=_.getInnerMostAxes(o.length,l.shape.length)),o=[o[0]],_.assertAxesAreInnerMostDims("argMax",o,l.shape.length);let[c,d]=_.computeOutAndReduceShapes(l.shape,o),h=k.sizeFromShape(c),p=k.makeZerosTypedArray(h,"int32"),f=k.sizeFromShape(d),m=n.data.get(l.dataId).values;for(let g=0;g<p.length;++g){let y=g*f,A=m[y],x=0;for(let b=0;b<f;++b){let v=m[y+b];v>A&&(A=v,x=b)}p[g]=x}return u.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.makeTensorInfo(c,"int32",p)}var Woe={kernelName:Yi,backendName:"cpu",kernelFunc:Boe};function Voe(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{axis:a}=r;Te(s,"argMin");let o=k.parseAxisParam(a,s.shape),i=_.getAxesPermutation(o,s.shape.length),l=s,u=[];i!=null&&(l=Pr({inputs:{x:s},backend:n,attrs:{perm:i}}),u.push(l),o=_.getInnerMostAxes(o.length,l.shape.length)),o=[o[0]],_.assertAxesAreInnerMostDims("argMin",o,l.shape.length);let[c,d]=_.computeOutAndReduceShapes(l.shape,o),h=k.sizeFromShape(c),p=k.makeZerosTypedArray(h,"int32"),f=k.sizeFromShape(d),m=n.data.get(l.dataId).values;for(let g=0;g<p.length;++g){let y=g*f,A=m[y],x=0;for(let b=0;b<f;++b){let v=m[y+b];v<A&&(A=v,x=b)}p[g]=x}return u.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.makeTensorInfo(c,"int32",p)}var Uoe={kernelName:qp,backendName:"cpu",kernelFunc:Voe},Hoe=xt(Ic,e=>Math.asin(e)),Goe={kernelName:Ic,backendName:"cpu",kernelFunc:Hoe},joe=xt(Sc,e=>Math.asinh(e)),qoe={kernelName:Sc,backendName:"cpu",kernelFunc:joe},Koe=xt(Tc,e=>Math.atan(e)),Xoe={kernelName:Tc,backendName:"cpu",kernelFunc:Koe},Zoe=nn((e,t)=>Math.atan2(e,t)),Yoe=bn(Cc,Zoe),Joe={kernelName:Cc,backendName:"cpu",kernelFunc:Yoe},Qoe=xt(Nc,e=>Math.atanh(e)),eie={kernelName:Nc,backendName:"cpu",kernelFunc:Qoe};function L5(e,t,n,r,s,a){let o=s.strideHeight,i=s.strideWidth,l=s.dilationHeight,u=s.dilationWidth,c=s.effectiveFilterHeight,d=s.effectiveFilterWidth,h=s.padInfo.top,p=s.padInfo.left,f=a==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=Le(s.outShape,n),g=m.values,y=s.outShape[1]*s.outShape[2]*s.outShape[3],A=s.outShape[2]*s.outShape[3],x=s.outShape[3];for(let b=0;b<s.batchSize;++b){let v=b*y,w=b*r[0];for(let I=0;I<s.inChannels;++I)for(let T=0;T<s.outHeight;++T){let C=T*o-h,M=Math.max(0,C),$=Math.min(s.inHeight,c+C),R=v+T*A;for(let N=0;N<s.outWidth;++N){let F=N*i-p,B=Math.max(0,F),j=Math.min(s.inWidth,d+F),X=f,Y=0,ee=0;for(let se=M;se<$;se+=l){let ie=w+se*r[1];for(let ne=B;ne<j;ne+=u){let de=ie+ne*r[2],he=e[de+I];a==="max"&&he>X?X=he:a==="avg"&&(Y+=he,ee++)}if(isNaN(X))break}let oe=R+N*x+I;g[oe]=a==="avg"?Y/ee:X}}}return m}function ON(e,t,n,r,s=!1,a=!1){let o=Le(r.outShape,"int32"),i=r.strideHeight,l=r.strideWidth,u=r.dilationHeight,c=r.dilationWidth,d=r.effectiveFilterHeight,h=r.effectiveFilterWidth,p=r.padInfo.top,f=r.padInfo.left,m=Le(t,n,e);for(let g=0;g<r.batchSize;++g)for(let y=0;y<r.inChannels;++y)for(let A=0;A<r.outHeight;++A){let x=A*i-p,b=x;for(;b<0;)b+=u;let v=Math.min(r.inHeight,d+x);for(let w=0;w<r.outWidth;++w){let I=w*l-f,T=I;for(;T<0;)T+=c;let C=Math.min(r.inWidth,h+I),M=Number.NEGATIVE_INFINITY,$=-1;for(let R=b;R<v;R+=u){let N=R-x;for(let F=T;F<C;F+=c){let B=F-I,j=m.get(g,R,F,y);j>M&&(M=j,s?$=a?((g*r.inHeight+R)*r.inWidth+F)*r.inChannels+y:(R*r.inWidth+F)*r.inChannels+y:$=N*h+B)}}o.set($,g,A,w,y)}}return o}function PN(e,t,n,r,s,a){let o=s.strideDepth,i=s.strideHeight,l=s.strideWidth,u=s.dilationDepth,c=s.dilationHeight,d=s.dilationWidth,h=s.effectiveFilterDepth,p=s.effectiveFilterHeight,f=s.effectiveFilterWidth,m=s.padInfo.front,g=s.padInfo.top,y=s.padInfo.left,A=a==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,x=Le(s.outShape,n),b=x.values,v=s.outShape[1]*s.outShape[2]*s.outShape[3]*s.outShape[4],w=s.outShape[2]*s.outShape[3]*s.outShape[4],I=s.outShape[3]*s.outShape[4],T=s.outShape[4];for(let C=0;C<s.batchSize;++C){let M=C*v,$=C*r[0];for(let R=0;R<s.inChannels;++R)for(let N=0;N<s.outDepth;++N){let F=N*o-m,B=F;for(;B<0;)B+=u;let j=Math.min(s.inDepth,h+F),X=M+N*w;for(let Y=0;Y<s.outHeight;++Y){let ee=Y*i-g,oe=ee;for(;oe<0;)oe+=c;let se=Math.min(s.inHeight,p+ee),ie=X+Y*I;for(let ne=0;ne<s.outWidth;++ne){let de=ne*l-y,he=de;for(;he<0;)he+=d;let ge=Math.min(s.inWidth,f+de),be=ie+ne*T,Ee=A,$e=0,ze=0;for(let We=B;We<j;We+=u){let vt=$+We*r[1];for(let ft=oe;ft<se;ft+=c){let mt=vt+ft*r[2];for(let dt=he;dt<ge;dt+=d){let bt=mt+dt*r[3],Je=e[bt+R];if(a==="max"&&Je>Ee?Ee=Je:a==="avg"&&($e+=Je,ze++),isNaN(Ee))break}if(isNaN(Ee))break}if(isNaN(Ee))break}let qe=be+R;b[qe]=a==="avg"?$e/ze:Ee}}}}return x}function tie(e,t){let n=Le(t.outShape,"int32"),r=t.strideDepth,s=t.strideHeight,a=t.strideWidth,o=t.dilationDepth,i=t.dilationHeight,l=t.dilationWidth,u=t.effectiveFilterDepth,c=t.effectiveFilterHeight,d=t.effectiveFilterWidth,h=t.padInfo.front,p=t.padInfo.top,f=t.padInfo.left;for(let m=0;m<t.batchSize;++m)for(let g=0;g<t.inChannels;++g)for(let y=0;y<t.outDepth;++y){let A=y*r-h,x=A;for(;x<0;)x+=o;let b=Math.min(t.inDepth,u+A);for(let v=0;v<t.outHeight;++v){let w=v*s-p,I=w;for(;I<0;)I+=i;let T=Math.min(t.inHeight,c+w);for(let C=0;C<t.outWidth;++C){let M=C*a-f,$=M;for(;$<0;)$+=l;let R=Math.min(t.inWidth,d+M),N=Number.NEGATIVE_INFINITY,F=-1;for(let B=x;B<b;B+=o){let j=B-A;for(let X=I;X<T;X+=i){let Y=X-w;for(let ee=$;ee<R;ee+=l){let oe=ee-M,se=e.get(m,B,X,ee,g);se>=N&&(N=se,F=j*c*d+Y*c+oe)}}}n.set(F,m,y,v,C,g)}}}return n}function nie(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t;Te(s,"avgPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=r,u=1;k.assert(_.eitherStridesOrDilationsAreOne(o,u),()=>`Error in avgPool: Either strides or dilations must be 1. 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c=_.computePool3DInfo(a.shape,o,i,1,l,u),d=c.strideDepth,h=c.strideHeight,p=c.strideWidth,f=c.filterDepth,m=c.filterHeight,g=c.filterWidth,y=c.dilationDepth,A=c.dilationHeight,x=c.dilationWidth,b=c.effectiveFilterDepth,v=c.effectiveFilterHeight,w=c.effectiveFilterWidth,I=b-1-c.padInfo.front,T=w-1-c.padInfo.left,C=v-1-c.padInfo.top,M=Le(a.shape,"float32"),$=1/(f*m*g),R=n.bufferSync(s);for(let N=0;N<c.batchSize;++N)for(let F=0;F<c.inChannels;++F)for(let B=0;B<c.inDepth;++B)for(let j=0;j<c.inHeight;++j)for(let X=0;X<c.inWidth;++X){let Y=B-I,ee=j-C,oe=X-T,se=0;for(let ie=0;ie<b;ie+=y){let ne=(Y+ie)/d;if(!(ne<0||ne>=c.outDepth||Math.floor(ne)!==ne))for(let de=0;de<v;de+=A){let he=(ee+de)/h;if(!(he<0||he>=c.outHeight||Math.floor(he)!==he))for(let ge=0;ge<w;ge+=x){let be=(oe+ge)/p;if(be<0||be>=c.outWidth||Math.floor(be)!==be)continue;se+=R.get(N,ne,he,be,F)}}}M.set(se*$,N,B,j,X,F)}return n.makeTensorInfo(M.shape,M.dtype,M.values)}var iie={kernelName:ky,backendName:"cpu",kernelFunc:oie};function lie(e){let{inputs:t,backend:n,attrs:r}=e,{dy:s,input:a}=t,o=a;Te([s,a],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=r,c=_.computePool2DInfo(o.shape,i,l,1,u),d=c.strideHeight,h=c.strideWidth,p=c.filterHeight,f=c.filterWidth,m=c.dilationHeight,g=c.dilationWidth,y=c.effectiveFilterHeight,A=c.effectiveFilterWidth,x=A-1-c.padInfo.left,b=y-1-c.padInfo.top,v=Le(o.shape,"float32"),w=1/(p*f),I=n.data.get(s.dataId).values,T=Le(s.shape,"float32",I);for(let C=0;C<c.batchSize;++C)for(let M=0;M<c.inChannels;++M)for(let $=0;$<c.inHeight;++$)for(let R=0;R<c.inWidth;++R){let N=$-b,F=R-x,B=0;for(let j=0;j<y;j+=m){let X=(N+j)/d;if(!(X<0||X>=c.outHeight||Math.floor(X)!==X))for(let Y=0;Y<A;Y+=g){let ee=(F+Y)/h;if(ee<0||ee>=c.outWidth||Math.floor(ee)!==ee)continue;B+=T.get(C,X,ee,M)}}v.set(B*w,C,$,R,M)}return n.makeTensorInfo(v.shape,v.dtype,v.values)}var uie={kernelName:wy,backendName:"cpu",kernelFunc:lie};function cie(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,scale:a,offset:o,mean:i,variance:l}=t;k.assert(i.shape.length===l.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),k.assert(o==null||i.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),k.assert(a==null||i.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks."),Te([s,i,l,a,o],"batchNorm");let{varianceEpsilon:u}=r;u==null&&(u=.001);let c=n.data.get(s.dataId).values,d=n.data.get(i.dataId).values,h=n.data.get(l.dataId).values,p=a?n.data.get(a.dataId).values:new Float32Array([1]),f=o?n.data.get(o.dataId).values:new Float32Array([0]),m=new Float32Array(c.length),g=f.length,y=p.length,A=h.length,x=d.length,b=0,v=0,w=0,I=0;for(let T=0;T<c.length;++T)m[T]=f[b++]+(c[T]-d[v++])*p[w++]/Math.sqrt(h[I++]+u),b>=g&&(b=0),v>=x&&(v=0),w>=y&&(w=0),I>=A&&(I=0);return n.makeTensorInfo(s.shape,s.dtype,m)}var die={kernelName:cl,backendName:"cpu",kernelFunc:cie};function hie(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{blockShape:a,crops:o}=r;Te([s],"batchToSpaceND");let i=a.reduce((y,A)=>y*A),l=_.getReshaped(s.shape,a,i),u=_.getPermuted(l.length,a.length),c=_.getReshapedPermuted(s.shape,a,i),d=_.getSliceBeginCoords(o,a.length),h=_.getSliceSize(c,o,a.length),p=Ft({inputs:{x:s},backend:n,attrs:{shape:l}}),f=Pr({inputs:{x:p},backend:n,attrs:{perm:u}}),m=Ft({inputs:{x:f},backend:n,attrs:{shape:c}}),g=fi({inputs:{x:m},backend:n,attrs:{begin:d,size:h}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),g}var pie={kernelName:Xp,backendName:"cpu",kernelFunc:hie};function fie(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,weights:a}=t,{size:o}=r,i=n.data.get(s.dataId).values,l=n.data.get(a.dataId).values,u=D5(i,l,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,u)}var mie={kernelName:Iy,backendName:"cpu",kernelFunc:fie},gie=xt(Co,(e,t)=>{let n=t;return e>n.clipValueMax?n.clipValueMax:e<n.clipValueMin?n.clipValueMin:e}),yie={kernelName:Co,backendName:"cpu",kernelFunc:gie},Aie=e=>{let{x:t}=e.inputs,n=e.backend,r=new Float32Array(k.sizeFromShape(t.shape)),s=n.data.get(t.dataId),a=s.complexTensorInfos.real,o=s.complexTensorInfos.imag,i=n.data.get(a.dataId).values,l=n.data.get(o.dataId).values;for(let u=0;u<i.length;u++){let c=i[u],d=l[u];r[u]=Math.hypot(c,d)}return n.makeOutput(r,t.shape,"float32")},xie={kernelName:Zp,backendName:"cpu",kernelFunc:Aie};function hu(e){let{inputs:t,backend:n}=e,{input:r}=t,s=n.data.get(r.dataId).complexTensorInfos.imag,a=n.data.get(s.dataId).values;return n.makeTensorInfo(s.shape,s.dtype,a)}var bie={kernelName:Ly,backendName:"cpu",kernelFunc:hu};function pu(e){let{inputs:t,backend:n,attrs:r}=e,{axis:s}=r,a=k.parseAxisParam(s,t[0].shape)[0],o=_.computeOutShape(t.map(m=>m.shape),a);if(k.sizeFromShape(o)===0)return 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u.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var vie={kernelName:Ec,backendName:"cpu",kernelFunc:pu};function zN(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=r;Te([s,a],"conv2d");let d=_.convertConv2DDataFormat(l),h=_.computeConv2DInfo(s.shape,a.shape,o,u,i,c,!1,d),p=h.filterHeight,f=h.filterWidth,m=h.dilationHeight,g=h.dilationWidth,y=h.padInfo.left,A=h.padInfo.top,x=h.dataFormat==="channelsLast",b=new Qt(h.outShape,s.dtype),v=k.computeStrides(s.shape),w=k.computeStrides(a.shape),I=v[0],T=x?v[1]:v[2],C=x?v[2]:1,M=x?1:v[1],$=b.strides[0],R=x?b.strides[1]:b.strides[2],N=x?b.strides[2]:1,F=x?1:b.strides[1],B=n.data.get(s.dataId).values,j=n.data.get(a.dataId).values,X=b.values;for(let Y=0;Y<h.batchSize;++Y){let ee=Y*I,oe=Y*$;for(let se=0;se<h.outHeight;++se){let ie=oe+se*R,ne=se*h.strideHeight-A;for(let de=0;de<p;++de){let he=ne+de*m;if(he<0||he>=h.inHeight)continue;let ge=de*w[0],be=ee+he*T;for(let Ee=0;Ee<h.outWidth;++Ee){let $e=ie+Ee*N,ze=Ee*h.strideWidth-y;for(let qe=0;qe<f;++qe){let We=ze+qe*g;if(We<0||We>=h.inWidth)continue;let vt=ge+qe*w[1],ft=be+We*C,mt=vt;for(let dt=0;dt<h.inChannels;++dt){let bt=B[ft+dt*M];for(let Je=0;Je<h.outChannels;++Je)X[$e+Je*F]+=bt*j[mt+Je];mt+=h.outChannels}}}}}}return n.makeTensorInfo(b.shape,b.dtype,X)}var wie={kernelName:tl,backendName:"cpu",kernelFunc:zN};function kie(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,dy:a}=t,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,filterShape:c}=r;Te([s,a],"conv2dBackpropFilter");let d=_.convertConv2DDataFormat(l),h=_.computeConv2DInfo(s.shape,c,o,1,i,u,!1,d),{strideHeight:p,strideWidth:f,filterHeight:m,filterWidth:g}=h,y=h.dataFormat==="channelsLast",A=new Qt(h.filterShape,"float32"),x=h.padInfo.left,b=h.padInfo.top,v=n.data.get(s.dataId).values,w=n.data.get(a.dataId).values,I=new Qt(s.shape,s.dtype,v),T=new Qt(a.shape,a.dtype,w);for(let C=0;C<m;++C){let M=Math.max(0,Math.ceil((b-C)/p)),$=Math.min(h.outHeight,(h.inHeight+b-C)/p);for(let R=0;R<g;++R){let N=Math.max(0,Math.ceil((x-R)/f)),F=Math.min(h.outWidth,(h.inWidth+x-R)/f);for(let B=0;B<h.inChannels;++B)for(let j=0;j<h.outChannels;++j){let X=0;for(let Y=0;Y<h.batchSize;++Y)for(let ee=M;ee<$;++ee){let oe=C+ee*p-b;for(let se=N;se<F;++se){let ie=R+se*f-x;y?X+=I.get(Y,oe,ie,B)*T.get(Y,ee,se,j):X+=I.get(Y,B,oe,ie)*T.get(Y,j,ee,se)}}A.set(X,C,R,B,j)}}}return n.makeTensorInfo(A.shape,A.dtype,A.values)}var Iie={kernelName:Ty,backendName:"cpu",kernelFunc:kie};function Sie(e){let{inputs:t,backend:n,attrs:r}=e,{dy:s,filter:a}=t,{inputShape:o,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=r;Te([s,a],"conv2dBackpropInput");let d=k.computeStrides(a.shape),h=k.computeStrides(s.shape),p=_.convertConv2DDataFormat(u),f=_.computeConv2DInfo(o,a.shape,i,1,l,c,!1,p),m=new Qt(f.inShape,"float32"),g=m.values,y=n.data.get(s.dataId).values,A=n.data.get(a.dataId).values,[x,b,v]=d,{batchSize:w,filterHeight:I,filterWidth:T,inChannels:C,inHeight:M,inWidth:$,outChannels:R,outHeight:N,outWidth:F,strideHeight:B,strideWidth:j}=f;p=f.dataFormat;let X=I-1-f.padInfo.top,Y=T-1-f.padInfo.left,ee=p==="channelsLast",oe=m.strides[0],se=ee?m.strides[1]:m.strides[2],ie=ee?m.strides[2]:1,ne=ee?1:m.strides[1],de=h[0],he=ee?h[1]:h[2],ge=ee?h[2]:1,be=ee?1:h[1];for(let Ee=0;Ee<w;++Ee)for(let $e=0;$e<C;++$e)for(let ze=0;ze<M;++ze){let qe=ze-X,We=Math.max(0,Math.ceil(qe/B)),vt=Math.min(N,(I+qe)/B);for(let ft=0;ft<$;++ft){let mt=ft-Y,dt=Math.max(0,Math.ceil(mt/j)),bt=Math.min(F,(T+mt)/j),Je=0;for(let Wt=We;Wt<vt;++Wt){let sr=Wt*B-qe;for(let vn=dt;vn<bt;++vn){let Vr=vn*j-mt,Rn=de*Ee+he*Wt+ge*vn,br=x*(I-1-sr)+b*(T-1-Vr)+v*$e;for(let vr=0;vr<R;++vr){let wn=y[Rn+be*vr],wr=A[br+vr];Je+=wn*wr}}}let jn=oe*Ee+se*ze+ie*ft+ne*$e;g[jn]=Je}}return n.makeTensorInfo(m.shape,m.dtype,m.values)}var Tie={kernelName:nl,backendName:"cpu",kernelFunc:Sie};function Nie(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,filter:a}=t,{strides:o,pad:i,dilations:l}=r;Te([s,a],"conv3d");let u=_.computeConv3DInfo(s.shape,a.shape,o,l,i),{filterDepth:c,filterHeight:d,filterWidth:h,dilationDepth:p,dilationHeight:f,dilationWidth:m,padInfo:g}=u,y=g.front,A=g.left,x=g.top,b=new Qt(u.outShape,s.dtype),v=n.data.get(s.dataId).values,w=n.data.get(a.dataId).values,I=b.values,T=k.computeStrides(s.shape),C=k.computeStrides(a.shape);for(let M=0;M<u.batchSize;++M){let $=M*T[0],R=M*b.strides[0];for(let N=0;N<u.outDepth;++N){let F=R+N*b.strides[1],B=N*u.strideDepth-y;for(let j=0;j<c;++j){let X=B+j*p;if(X<0||X>=u.inDepth)continue;let Y=j*C[0],ee=$+X*T[1];for(let oe=0;oe<u.outHeight;++oe){let se=F+oe*b.strides[2],ie=oe*u.strideHeight-x;for(let ne=0;ne<d;++ne){let de=ie+ne*f;if(de<0||de>=u.inHeight)continue;let he=Y+ne*C[1],ge=ee+de*T[2];for(let be=0;be<u.outWidth;++be){let Ee=se+be*u.outChannels,$e=be*u.strideWidth-A;for(let ze=0;ze<h;++ze){let qe=$e+ze*m;if(qe<0||qe>=u.inWidth)continue;let We=he+ze*C[2],vt=ge+qe*u.inChannels,ft=We;for(let mt=0;mt<u.inChannels;++mt){let dt=v[vt+mt];for(let bt=0;bt<u.outChannels;++bt)I[Ee+bt]+=dt*w[ft+bt];ft+=u.outChannels}}}}}}}}return n.makeTensorInfo(b.shape,b.dtype,b.values)}var Cie={kernelName:Yp,backendName:"cpu",kernelFunc:Nie};function Eie(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,dy:a}=t,{strides:o,pad:i,filterShape:l}=r;Te([s,a],"conv3dBackpropFilterV2");let u=k.computeStrides(s.shape),c=k.computeStrides(a.shape),d=_.computeConv3DInfo(s.shape,l,o,1,i),h=d.strideDepth,p=d.strideHeight,f=d.strideWidth,m=d.filterDepth,g=d.filterHeight,y=d.filterWidth,A=new Qt(d.filterShape,"float32"),x=A.values,[b,v,w,I]=A.strides,T=n.data.get(a.dataId).values,[C,M,$,R]=c,N=n.data.get(s.dataId).values,[F,B,j,X]=u,Y=d.padInfo.front,ee=d.padInfo.left,oe=d.padInfo.top;for(let se=0;se<m;++se){let ie=Math.max(0,Math.ceil((Y-se)/h)),ne=Math.min(d.outDepth,(d.inDepth+Y-se)/h),de=se*b;for(let he=0;he<g;++he){let ge=Math.max(0,Math.ceil((oe-he)/p)),be=Math.min(d.outHeight,(d.inHeight+oe-he)/p),Ee=he*v+de;for(let $e=0;$e<y;++$e){let ze=Math.max(0,Math.ceil((ee-$e)/f)),qe=Math.min(d.outWidth,(d.inWidth+ee-$e)/f),We=$e*w+Ee;for(let vt=0;vt<d.inChannels;++vt){let ft=vt*I+We;for(let mt=0;mt<d.outChannels;++mt){let dt=0;for(let bt=0;bt<d.batchSize;++bt){let Je=bt*F,jn=bt*C;for(let Wt=ie;Wt<ne;++Wt){let vn=(se+Wt*h-Y)*B+Je,Vr=Wt*M+jn;for(let Rn=ge;Rn<be;++Rn){let vr=(he+Rn*p-oe)*j+vn,wn=Rn*$+Vr;for(let wr=ze;wr<qe;++wr){let ar=($e+wr*f-ee)*X+vr,ws=wr*R+wn;dt+=N[ar+vt]*T[ws+mt]}}}}x[ft+mt]=dt}}}}}return n.makeTensorInfo(A.shape,A.dtype,A.values)}var $ie={kernelName:Ny,backendName:"cpu",kernelFunc:Eie};function _ie(e){let{inputs:t,backend:n,attrs:r}=e,{dy:s,filter:a}=t,{pad:o,strides:i,inputShape:l}=r;Te([s],"conv3dBackpropInputV2");let u=k.computeStrides(s.shape),c=k.computeStrides(a.shape),d=_.computeConv3DInfo(l,a.shape,i,1,o),h=new Qt(d.inShape,"float32"),p=h.values,[f,m,g,y]=h.strides,A=n.data.get(s.dataId).values,[x,b,v,w]=u,I=n.data.get(a.dataId).values,[T,C,M,$]=c,{batchSize:R,filterDepth:N,filterHeight:F,filterWidth:B,inChannels:j,inDepth:X,inHeight:Y,inWidth:ee,outChannels:oe,outDepth:se,outHeight:ie,outWidth:ne,strideDepth:de,strideHeight:he,strideWidth:ge}=d,be=N-1-d.padInfo.front,Ee=F-1-d.padInfo.top,$e=B-1-d.padInfo.left;for(let ze=0;ze<R;++ze)for(let qe=0;qe<j;++qe)for(let We=0;We<X;++We){let vt=We-be,ft=Math.max(0,Math.ceil(vt/de)),mt=Math.min(se,(N+vt)/de);for(let dt=0;dt<Y;++dt){let bt=dt-Ee,Je=Math.max(0,Math.ceil(bt/he)),jn=Math.min(ie,(F+bt)/he);for(let Wt=0;Wt<ee;++Wt){let sr=Wt-$e,vn=Math.max(0,Math.ceil(sr/ge)),Vr=Math.min(ne,(B+sr)/ge),Rn=0;for(let br=ft;br<mt;++br){let vr=br*de-vt;for(let wn=Je;wn<jn;++wn){let wr=wn*he-bt;for(let kr=vn;kr<Vr;++kr){let ar=kr*ge-sr,ws=x*ze+b*br+v*wn+w*kr,Us=T*(N-1-vr)+C*(F-1-wr)+M*(B-1-ar)+$*qe;for(let Aa=0;Aa<oe;++Aa){let Si=A[ws+Aa],ks=I[Us+Aa];Rn+=Si*ks}}}}p[f*ze+m*We+g*dt+y*Wt+qe]=Rn}}}return n.makeTensorInfo(h.shape,h.dtype,h.values)}var Rie={kernelName:Cy,backendName:"cpu",kernelFunc:_ie},Die=xt(rl,e=>Math.cos(e)),Fie={kernelName:rl,backendName:"cpu",kernelFunc:Die},Mie=xt($c,e=>Math.cosh(e)),Oie={kernelName:$c,backendName:"cpu",kernelFunc:Mie};function Pie(e){let{inputs:t,backend:n,attrs:r}=e,{image:s,boxes:a,boxInd:o}=t,{cropSize:i,method:l,extrapolationValue:u}=r,[c,d,h,p]=s.shape,f=a.shape[0],[m,g]=i,y=Le([f,m,g,p],"float32"),A=n.data.get(a.dataId).values,x=n.data.get(o.dataId).values,b=n.data.get(s.dataId).values,v=k.computeStrides(s.shape),w=k.computeStrides(y.shape);for(let I=0;I<f;I++){let T=I*4,C=A[T],M=A[T+1],$=A[T+2],R=A[T+3],N=x[I];if(N>=c)continue;let F=m>1?($-C)*(d-1)/(m-1):0,B=g>1?(R-M)*(h-1)/(g-1):0;for(let j=0;j<m;j++){let X=m>1?C*(d-1)+j*F:.5*(C+$)*(d-1);if(X<0||X>d-1){for(let Y=0;Y<g;Y++)for(let ee=0;ee<p;ee++){let oe=ee+Y*w[2]+j*w[1]+I*w[0];y.values[oe]=u}continue}if(l==="bilinear"){let Y=Math.floor(X),ee=Math.ceil(X),oe=X-Y;for(let se=0;se<g;se++){let ie=g>1?M*(h-1)+se*B:.5*(M+R)*(h-1);if(ie<0||ie>h-1){for(let ge=0;ge<p;ge++){let be=ge+se*w[2]+j*w[1]+I*w[0];y.values[be]=u}continue}let ne=Math.floor(ie),de=Math.ceil(ie),he=ie-ne;for(let ge=0;ge<p;ge++){let be=ge+ne*v[2]+Y*v[1]+N*v[0],Ee=b[be];be=ge+de*v[2]+Y*v[1]+N*v[0];let $e=b[be];be=ge+ne*v[2]+ee*v[1]+N*v[0];let ze=b[be];be=ge+de*v[2]+ee*v[1]+N*v[0];let qe=b[be],We=Ee+($e-Ee)*he,vt=ze+(qe-ze)*he;be=ge+se*w[2]+j*w[1]+I*w[0],y.values[be]=We+(vt-We)*oe}}}else for(let Y=0;Y<g;++Y){let ee=g>1?M*(h-1)+Y*B:.5*(M+R)*(h-1);if(ee<0||ee>h-1){for(let ie=0;ie<p;ie++){let ne=ie+Y*w[2]+j*w[1]+I*w[0];y.values[ne]=u}continue}let oe=Math.round(ee),se=Math.round(X);for(let ie=0;ie<p;ie++){let ne=ie+oe*v[2]+se*v[1]+N*v[0],de=ie+Y*w[2]+j*w[1]+I*w[0];y.values[de]=b[ne]}}}}return n.makeTensorInfo(y.shape,y.dtype,y.values)}var zie={kernelName:_c,backendName:"cpu",kernelFunc:Pie};function Lie(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{axis:a,exclusive:o,reverse:i}=r;Te(s,"cumsum");let l=_.getAxesPermutation([a],s.shape.length),u=s;l!=null&&(u=Pr({inputs:{x:s},backend:n,attrs:{perm:l}}));let c=_.getInnerMostAxes(1,s.shape.length)[0];if(c!==u.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${c}`);let d=qr(u.dtype,"int32"),h=k.makeZerosTypedArray(k.sizeFromShape(u.shape),d),p=n.data.get(u.dataId).values,f=u.shape[u.shape.length-1],m=i?(y,A)=>y+f-A-1:(y,A)=>y+A;for(let y=0;y<p.length;y+=f)for(let A=0;A<f;A++){let x=m(y,A);if(A===0)h[x]=o?0:p[x];else{let b=m(y,A-1);h[x]=o?p[b]+h[b]:p[x]+h[b]}}let g=n.makeTensorInfo(u.shape,d,h);if(l!=null){let y=_.getUndoAxesPermutation(l),A=Pr({inputs:{x:g},backend:n,attrs:{perm:y}});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(u),A}return g}var Bie={kernelName:sl,backendName:"cpu",kernelFunc:Lie};function Wie(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,weights:a}=t,{size:o,binaryOutput:i}=r;if(s.shape.length===1){let l=n.data.get(s.dataId).values,u=n.data.get(a.dataId).values,c=D5(l,u,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,c)}else if(s.shape.length===2){let l=n.bufferSync(s),u=n.bufferSync(a),c=jT(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${s.shape.length}.`)}var Vie={kernelName:Ey,backendName:"cpu",kernelFunc:Wie};function Uie(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{blockSize:a,dataFormat:o}=r;k.assert(o==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. Got ${o}`),k.assert(a>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${a}`);let i=s.shape[0],l=s.shape[1],u=s.shape[2],c=s.shape[3],d=l*a,h=u*a,p=c/(a*a),f=n.data.get(s.dataId).values,m=new Float32Array(i*d*h*p),g=0;for(let y=0;y<i;++y)for(let A=0;A<d;++A){let x=Math.floor(A/a),b=A%a;for(let v=0;v<h;++v){let w=Math.floor(v/a),I=v%a,T=(b*a+I)*p;for(let C=0;C<p;++C){let $=C+T+c*(w+u*(x+l*y));m[g++]=f[$]}}}return n.makeTensorInfo([i,d,h,p],s.dtype,m)}var Hie={kernelName:Rc,backendName:"cpu",kernelFunc:Uie};function LN(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,filter:a}=t,{strides:o,pad:i,dilations:l,dimRoundingMode:u}=r;Te([s,a],"depthwiseConv2DNative");let c=k.computeStrides(s.shape),d=k.computeStrides(a.shape),h=l;h==null&&(h=[1,1]),k.assert(_.eitherStridesOrDilationsAreOne(o,h),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${o} and dilations '${h}'`);let p=_.computeConv2DInfo(s.shape,a.shape,o,h,i,u,!0),{filterHeight:f,filterWidth:m,dilationHeight:g,dilationWidth:y,padInfo:A}=p,x=A.left,b=A.top,v=p.outChannels/p.inChannels,w=new Qt(p.outShape,s.dtype),I=n.data.get(s.dataId).values,T=n.data.get(a.dataId).values,C=w.values;for(let M=0;M<p.batchSize;++M){let $=M*c[0],R=M*w.strides[0];for(let N=0;N<p.outHeight;++N){let F=R+N*w.strides[1],B=N*p.strideHeight-b;for(let j=0;j<f;++j){let X=B+j*g;if(X<0||X>=p.inHeight)continue;let Y=j*d[0],ee=$+X*c[1];for(let oe=0;oe<p.outWidth;++oe){let se=F+oe*w.strides[2],ie=oe*p.strideWidth-x;for(let ne=0;ne<m;++ne){let de=ie+ne*y;if(de<0||de>=p.inWidth)continue;let he=Y+ne*d[1],ge=ee+de*p.inChannels,be=se,Ee=he;for(let $e=0;$e<p.inChannels;++$e){let ze=I[ge+$e];for(let qe=0;qe<v;++qe)C[be+qe]+=ze*T[Ee+qe];be+=v,Ee+=v}}}}}}return n.makeTensorInfo(w.shape,w.dtype,w.values)}var Gie={kernelName:al,backendName:"cpu",kernelFunc:LN};function jie(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,dy:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,filterShape:c}=r;Te([s,a],"depthwiseConv2dNativeBackpropFilter");let d=_.computeConv2DInfo(s.shape,c,o,i,l,u,!0),{strideHeight:h,strideWidth:p,filterHeight:f,filterWidth:m}=d,g=new Qt(d.filterShape,"float32"),y=d.padInfo.left,A=d.padInfo.top,x=d.outChannels/d.inChannels,b=n.data.get(s.dataId).values,v=new Qt(s.shape,s.dtype,b),w=n.data.get(a.dataId).values,I=new Qt(a.shape,a.dtype,w);for(let T=0;T<f;++T){let C=Math.max(0,Math.ceil((A-T)/h)),M=Math.min(d.outHeight,(d.inHeight+A-T)/h);for(let $=0;$<m;++$){let R=Math.max(0,Math.ceil((y-$)/p)),N=Math.min(d.outWidth,(d.inWidth+y-$)/p);for(let F=0;F<d.outChannels;++F){let B=Math.trunc(F/x),j=F%x,X=0;for(let Y=0;Y<d.batchSize;++Y)for(let ee=C;ee<M;++ee){let oe=T+ee*h-A;for(let se=R;se<N;++se){let ie=$+se*p-y;X+=v.get(Y,oe,ie,B)*I.get(Y,ee,se,F)}}g.set(X,T,$,B,j)}}}return n.makeTensorInfo(g.shape,g.dtype,g.values)}var qie={kernelName:$y,backendName:"cpu",kernelFunc:jie};function Kie(e){let{inputs:t,backend:n,attrs:r}=e,{dy:s,filter:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=r;Te([s,a],"depthwiseConv2DNativeBackpropInput");let d=k.computeStrides(s.shape),h=k.computeStrides(a.shape),p=_.computeConv2DInfo(c,a.shape,o,i,l,u,!0),f=new Qt(p.inShape,"float32"),m=f.values,[g,y,A]=f.strides,x=n.data.get(s.dataId).values,[b,v,w]=d,I=n.data.get(a.dataId).values,[T,C,M]=h,{batchSize:$,filterHeight:R,filterWidth:N,inChannels:F,inHeight:B,inWidth:j,outChannels:X,outHeight:Y,outWidth:ee,strideHeight:oe,strideWidth:se}=p,ie=R-1-p.padInfo.top,ne=N-1-p.padInfo.left,de=X/F;for(let he=0;he<$;++he)for(let ge=0;ge<F;++ge)for(let be=0;be<B;++be){let Ee=be-ie,$e=Math.max(0,Math.ceil(Ee/oe)),ze=Math.min(Y,(R+Ee)/oe);for(let qe=0;qe<j;++qe){let We=qe-ne,vt=Math.max(0,Math.ceil(We/se)),ft=Math.min(ee,(N+We)/se),mt=0;for(let dt=$e;dt<ze;++dt){let bt=dt*oe-Ee;for(let Je=vt;Je<ft;++Je){let jn=Je*se-We,Wt=b*he+v*dt+w*Je,sr=T*(R-1-bt)+C*(N-1-jn)+M*ge;for(let vn=0;vn<de;++vn){let Vr=ge*de+vn,Rn=x[Wt+Vr],br=I[sr+vn];mt+=Rn*br}}}m[g*he+y*be+A*qe+ge]=mt}}return n.makeTensorInfo(f.shape,f.dtype,f.values)}var Xie={kernelName:_y,backendName:"cpu",kernelFunc:Kie};function Zie(e){let{inputs:t,backend:n}=e,{x:r}=t,s=k.sizeFromShape(r.shape),a=n.data.get(r.dataId).values,o=Le([s,s],r.dtype),i=o.values;for(let u=0;u<a.length;u++)i[u*s+u]=a[u];let l=[...r.shape,...r.shape];return n.makeTensorInfo(l,o.dtype,o.values)}var 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r=k.sizeFromShape(e.shape),s=n.data.get(e.dataId),a=n.data.get(s.complexTensorInfos.real.dataId).values,o=n.data.get(s.complexTensorInfos.imag.dataId).values;if(yle(r)){let i=V5(a,o,r,t,n),l=[e.shape[0],e.shape[1]];if(t){let u=n.makeTensorInfo(l,"float32",i.real),c=n.makeTensorInfo(l,"float32",i.imag),d=n.makeTensorInfo([],"float32",k.createScalarValue(r,"float32")),h=zs({inputs:{x:d},backend:n}),p=W5.kernelFunc({inputs:{a:u,b:d},backend:n}),f=W5.kernelFunc({inputs:{a:c,b:h},backend:n}),m=n.data.get(p.dataId).values,g=n.data.get(f.dataId).values;return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),{real:m,imag:g}}return i}else{let i=_.mergeRealAndImagArrays(a,o),l=Ale(i,r,t);return _.splitRealAndImagArrays(l)}}function yle(e){return(e&e-1)==0}function V5(e,t,n,r,s){if(n===1)return{real:e,imag:t};let a=_.mergeRealAndImagArrays(e,t),o=n/2,i=_.complexWithEvenIndex(a),l=i.real,u=i.imag,c=[l.length],d=s.makeTensorInfo(c,"float32",l),h=s.makeTensorInfo(c,"float32",u),p=fr({inputs:{real:d,imag:h},backend:s}),f=_.complexWithOddIndex(a),m=f.real,g=f.imag,y=[m.length],A=s.makeTensorInfo(y,"float32",m),x=s.makeTensorInfo(y,"float32",g),b=fr({inputs:{real:A,imag:x},backend:s}),v=V5(l,u,o,r,s),w=v.real,I=v.imag,T=[w.length],C=s.makeTensorInfo(T,"float32",w),M=s.makeTensorInfo(T,"float32",I),$=fr({inputs:{real:C,imag:M},backend:s}),R=V5(m,g,o,r,s),N=R.real,F=R.imag,B=[N.length],j=s.makeTensorInfo(B,"float32",N),X=s.makeTensorInfo(B,"float32",F),Y=fr({inputs:{real:j,imag:X},backend:s}),ee=_.exponents(n,r),oe=[ee.real.length],se=s.makeTensorInfo(oe,"float32",ee.real),ie=s.makeTensorInfo(oe,"float32",ee.imag),ne=fr({inputs:{real:se,imag:ie},backend:s}),de=$m({inputs:{a:ne,b:Y},backend:s}),he=th({inputs:{a:$,b:de},backend:s}),ge=P5({inputs:{a:$,b:de},backend:s}),be=pi({inputs:{input:he},backend:s}),Ee=pi({inputs:{input:ge},backend:s}),$e=hu({inputs:{input:he},backend:s}),ze=hu({inputs:{input:ge},backend:s}),qe=pu({inputs:[be,Ee],backend:s,attrs:{axis:0}}),We=pu({inputs:[$e,ze],backend:s,attrs:{axis:0}}),vt=s.data.get(qe.dataId).values,ft=s.data.get(We.dataId).values;return s.disposeIntermediateTensorInfo(d),s.disposeIntermediateTensorInfo(h),s.disposeIntermediateTensorInfo(p),s.disposeIntermediateTensorInfo(A),s.disposeIntermediateTensorInfo(x),s.disposeIntermediateTensorInfo(b),s.disposeIntermediateTensorInfo(C),s.disposeIntermediateTensorInfo(M),s.disposeIntermediateTensorInfo($),s.disposeIntermediateTensorInfo(j),s.disposeIntermediateTensorInfo(X),s.disposeIntermediateTensorInfo(Y),s.disposeIntermediateTensorInfo(se),s.disposeIntermediateTensorInfo(ie),s.disposeIntermediateTensorInfo(ne),s.disposeIntermediateTensorInfo(de),s.disposeIntermediateTensorInfo(he),s.disposeIntermediateTensorInfo(ge),s.disposeIntermediateTensorInfo(be),s.disposeIntermediateTensorInfo($e),s.disposeIntermediateTensorInfo(Ee),s.disposeIntermediateTensorInfo(ze),s.disposeIntermediateTensorInfo(qe),s.disposeIntermediateTensorInfo(We),{real:vt,imag:ft}}function Ale(e,t,n){let r=new Float32Array(t*2);for(let s=0;s<t;s++){let a=0,o=0;for(let i=0;i<t;i++){let 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kle={kernelName:Oc,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,s=n,a=k.getTypedArrayFromDType(r.dtype,k.sizeFromShape(r.shape)),[o,i,l,u]=r.shape,c=s.data.get(r.dataId).values;for(let h=0;h<o;h++){let p=h*l*i*u;for(let f=0;f<i;f++){let m=f*(l*u);for(let g=0;g<l;g++){let y=g*u;for(let A=0;A<u;A++){let b=[o,f,g,A][2],v=Math.round(l-b),w=p+m+y+A,I=c[w];if(v>=0&&v<l){let T=v*u,C=p+m+T+A;I=c[C]}a[w]=I}}}}return{dataId:s.write(a,r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}},Ile=nn((e,t)=>Math.floor(e/t)),Sle=bn(ul,Ile,null,"int32"),Tle={kernelName:ul,backendName:"cpu",kernelFunc:Sle};function Nle(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:d,dimRoundingMode:h,activation:p,leakyreluAlpha:f}=r,m=zN({inputs:{x:s,filter:a},backend:n,attrs:{strides:l,pad:u,dataFormat:c,dilations:d,dimRoundingMode:h}});if(o){let 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Mle(e){let{inputs:t,backend:n}=e,{input:r}=t,s=k.sizeFromShape(r.shape),a=r.shape[r.shape.length-1],o=s/a,i=Ft({inputs:{x:r},backend:n,attrs:{shape:[o,a]}}),l=BN(i,!0,n),u=Ft({inputs:{x:l},backend:n,attrs:{shape:r.shape}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var Ole={kernelName:zy,backendName:"cpu",kernelFunc:Mle},Ple=xt(Lc,e=>Number.isFinite(e)?1:0,"bool"),zle={kernelName:Lc,backendName:"cpu",kernelFunc:Ple},Lle=xt(Bc,e=>Math.abs(e)===Infinity?1:0,"bool"),Ble={kernelName:Bc,backendName:"cpu",kernelFunc:Lle},Wle=xt(Wc,e=>Number.isNaN(e)?1:0,"bool"),Vle={kernelName:Wc,backendName:"cpu",kernelFunc:Wle};function Ule(e){let{backend:t,attrs:n}=e,{start:r,stop:s,num:a}=n,o=iN(r,s,a);return t.makeTensorInfo([o.length],"float32",o)}var Hle={kernelName:By,backendName:"cpu",kernelFunc:Ule},Gle=xt(Vc,e=>Math.log1p(e)),jle={kernelName:Vc,backendName:"cpu",kernelFunc:Gle},qle=nn((e,t)=>e&&t),Kle=bn(Uc,qle,null,"bool"),Xle={kernelName:Uc,backendName:"cpu",kernelFunc:Kle},Zle=xt(ef,e=>e?0:1,"bool"),Yle={kernelName:ef,backendName:"cpu",kernelFunc:Zle},Jle=nn((e,t)=>e||t),Qle=bn(tf,Jle,null,"bool"),eue={kernelName:tf,backendName:"cpu",kernelFunc:Qle};function tue(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{depthRadius:a,bias:o,alpha:i,beta:l}=r;Te(s,"LRN");let u=s.shape[3],c=u-1,d=n.data.get(s.dataId).values,h=k.sizeFromShape(s.shape),p=new Float32Array(h);function f(m){let g=m%u,y=m-g+Math.max(0,g-a),A=m-g+Math.min(g+a,c),x=0;for(;y<=A;y++){let b=d[y];x+=b*b}return x}for(let m=0;m<h;m++){let g=f(m),y=d[m]*Math.pow(o+i*g,-l);p[m]=y}return n.makeTensorInfo(s.shape,s.dtype,p)}var nue={kernelName:nf,backendName:"cpu",kernelFunc:tue};function rue(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,y:a,dy:o}=t,{depthRadius:i,bias:l,alpha:u,beta:c}=r;Te(o,"LRNGrad");let d=k.sizeFromShape(o.shape),h=o.shape[3],p=n.data.get(o.dataId).values,f=n.data.get(s.dataId).values,m=n.data.get(a.dataId).values,g=new Float32Array(d),y=d;for(let A=0;A<y;A++){let x=A%h,b=A-x+Math.max(0,x-i),v=A-x+Math.min(h,x+i+1),w=0;for(let I=b;I<v;I++)w+=Math.pow(f[I],2);w=u*w+l;for(let I=b;I<v;I++){let T=-2*u*c*f[I]*m[A]/w;A===I&&(T+=Math.pow(w,-c)),T*=p[A],g[I]+=T}}return n.makeTensorInfo(o.shape,s.dtype,g)}var sue={kernelName:Wy,backendName:"cpu",kernelFunc:rue};function WN(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{reductionIndices:a,keepDims:o}=r,i=n,l=s.shape,u=l.length,c=k.parseAxisParam(a,l),d=c,h=_.getAxesPermutation(d,u),p=i.data.get(s.dataId).values;if(h!=null){let b=new Array(u);for(let v=0;v<b.length;v++)b[v]=l[h[v]];p=M5(p,l,s.dtype,h,b),d=_.getInnerMostAxes(d.length,u),l=b}Te(s,"max"),_.assertAxesAreInnerMostDims("max",d,u);let[f,m]=_.computeOutAndReduceShapes(l,d),g=k.sizeFromShape(m),y=uN(p,g,f,s.dtype),A=i.write(y,f,s.dtype),x=f;return o&&(x=_.expandShapeToKeepDim(f,c)),{dataId:A,shape:x,dtype:s.dtype}}var aue={kernelName:gl,backendName:"cpu",kernelFunc:WN};function oue(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t;Te(s,"maxPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=r,u=1;k.assert(_.eitherStridesOrDilationsAreOne(o,u),()=>`Error in maxPool: Either strides or dilations must be 1. 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c=_.computePool3DInfo(a.shape,o,i,1,l,u),d=n.bufferSync(a),h=tie(d,c),p=c.strideDepth,f=c.strideHeight,m=c.strideWidth,g=c.dilationDepth,y=c.dilationHeight,A=c.dilationWidth,x=c.effectiveFilterDepth,b=c.effectiveFilterHeight,v=c.effectiveFilterWidth,w=x-1-c.padInfo.front,I=v-1-c.padInfo.left,T=b-1-c.padInfo.top,C=Le(a.shape,"float32"),M=n.bufferSync(s);for(let $=0;$<c.batchSize;++$)for(let R=0;R<c.inChannels;++R)for(let N=0;N<c.inDepth;++N)for(let F=0;F<c.inHeight;++F)for(let B=0;B<c.inWidth;++B){let j=N-w,X=F-T,Y=B-I,ee=0;for(let oe=0;oe<x;oe+=g){let se=(j+oe)/p;if(!(se<0||se>=c.outDepth||Math.floor(se)!==se))for(let ie=0;ie<b;ie+=y){let ne=(X+ie)/f;if(!(ne<0||ne>=c.outHeight||Math.floor(ne)!==ne))for(let de=0;de<v;de+=A){let he=(Y+de)/m;if(he<0||he>=c.outWidth||Math.floor(he)!==he)continue;let ge=x*b*v-1-h.get($,se,ne,he,R),be=oe*b*v+ie*v+de,Ee=ge===be?1:0;if(Ee===0)continue;ee+=M.get($,se,ne,he,R)*Ee}}}C.set(ee,$,N,F,B,R)}return n.makeTensorInfo(C.shape,C.dtype,C.values)}var due={kernelName:Uy,backendName:"cpu",kernelFunc:cue};function hue(e){let{inputs:t,backend:n,attrs:r}=e,{dy:s,input:a,output:o}=t,i=a;Te([a,o],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:d}=r,h=_.computePool2DInfo(i.shape,l,u,1,c,d),p=n.data.get(i.dataId).values,f=Le(h.outShape,i.dtype,ON(p,i.shape,i.dtype,h).values),m=h.strideHeight,g=h.strideWidth,y=h.dilationHeight,A=h.dilationWidth,x=h.effectiveFilterHeight,b=h.effectiveFilterWidth,v=b-1-h.padInfo.left,w=x-1-h.padInfo.top,I=Le(i.shape,"float32"),T=n.data.get(s.dataId).values,C=Le(s.shape,"float32",T);for(let M=0;M<h.batchSize;++M)for(let $=0;$<h.inChannels;++$)for(let R=0;R<h.inHeight;++R)for(let N=0;N<h.inWidth;++N){let F=R-w,B=N-v,j=0;for(let X=0;X<x;X+=y){let Y=(F+X)/m;if(!(Y<0||Y>=h.outHeight||Math.floor(Y)!==Y))for(let ee=0;ee<b;ee+=A){let oe=(B+ee)/g;if(oe<0||oe>=h.outWidth||Math.floor(oe)!==oe)continue;let se=x*b-1-f.get(M,Y,oe,$),ie=X*b+ee,ne=se===ie?1:0;if(ne===0)continue;j+=C.get(M,Y,oe,$)*ne}}I.set(j,M,R,N,$)}return n.makeTensorInfo(I.shape,I.dtype,I.values)}var pue={kernelName:Vy,backendName:"cpu",kernelFunc:hue};function fue(e,t,n,r,s){let a=k.computeStrides(t),o=L5(e,t,n,a,s,"max"),i=ON(e,t,n,s,!0,r);return[o.values,i.values]}var mue={kernelName:Hy,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:s,strides:a,pad:o,includeBatchInIndex:i}=t,l=n;Te(r,"MaxPoolWithArgmax");let u=l.data.get(r.dataId).values,c=_.computePool2DInfo(r.shape,s,a,[1,1],o),[d,h]=fue(u,r.shape,r.dtype,i,c),p=l.write(d,c.outShape,r.dtype),f=l.write(h,c.outShape,r.dtype);return[{dataId:p,shape:c.outShape,dtype:r.dtype},{dataId:f,shape:c.outShape,dtype:"int32"}]}};function gue(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{axis:a,keepDims:o}=r,i=k.parseAxisParam(a,s.shape),u=_.computeOutAndReduceShapes(s.shape,i)[1],c=k.sizeFromShape(u),d=[],h=n.makeTensorInfo([],"float32",new Float32Array([c]));d.push(h);let p=Ja({inputs:{x:s},backend:n,attrs:{dtype:"float32"}});d.push(p);let f=B5({inputs:{a:p,b:h},backend:n});d.push(f);let m=nh({inputs:{x:f},backend:n,attrs:{axis:a,keepDims:o}});return d.forEach(g=>n.disposeIntermediateTensorInfo(g)),m}var yue={kernelName:Al,backendName:"cpu",kernelFunc:gue};function Aue(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{axis:a,keepDims:o}=r;Te(s,"min");let i=k.parseAxisParam(a,s.shape),l=i,u=_.getAxesPermutation(l,s.shape.length),c=s;u!=null&&(c=Pr({inputs:{x:s},backend:n,attrs:{perm:u}}),l=_.getInnerMostAxes(l.length,s.shape.length)),_.assertAxesAreInnerMostDims("min",l,c.shape.length);let[d,h]=_.computeOutAndReduceShapes(c.shape,l),p=k.sizeFromShape(h),f=k.makeZerosTypedArray(k.sizeFromShape(d),c.dtype),m=n.data.get(c.dataId).values;for(let y=0;y<f.length;++y){let A=y*p,x=m[A];for(let b=0;b<p;++b){let v=m[A+b];(Number.isNaN(v)||v<x)&&(x=v)}f[y]=x}u!=null&&n.disposeIntermediateTensorInfo(c);let g=n.makeTensorInfo(d,c.dtype,f);if(o){let y=_.expandShapeToKeepDim(d,i),A=Ft({inputs:{x:g},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(g),A}return g}var xue={kernelName:xl,backendName:"cpu",kernelFunc:Aue};function bue(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{paddings:a,mode:o}=r;Te(s,"mirrorPad");let i=a.map((x,b)=>x[0]+s.shape[b]+x[1]),l=a.map(x=>x[0]),u=a.map((x,b)=>x[0]+s.shape[b]),c=o==="reflect"?0:1,d=n.data.get(s.dataId).values,h=s.shape.length,p=k.computeStrides(s.shape),f=k.sizeFromShape(i),m=i.length,g=k.computeStrides(i),y=k.getTypedArrayFromDType(s.dtype,f);for(let x=0;x<f;x++){let b=k.indexToLoc(x,m,g);for(let w=0;w<m;w++)b[w]<l[w]?b[w]=l[w]*2-b[w]-c:b[w]>=u[w]&&(b[w]=(u[w]-1)*2-b[w]+c);b=b.map((w,I)=>w-l[I]);let v=k.locToIndex(b,h,p);y[x]=d[v]}return{dataId:n.write(y,i,s.dtype),shape:i,dtype:s.dtype}}var vue={kernelName:bl,backendName:"cpu",kernelFunc:bue},wue=nn((e,t)=>{let n=e%t;return e<0&&t<0||e>=0&&t>=0?n:(n+t)%t}),kue=bn(Hc,wue),Iue={kernelName:Hc,backendName:"cpu",kernelFunc:kue},Sue=Ks(t2());function VN(e){let{inputs:t,backend:n,attrs:r}=e,{logits:s}=t,{dim:a}=r,o=s.shape.length,i=a;if(i===-1&&(i=o-1),i!==o-1)throw Error(`Softmax along a non-last dimension is not yet supported. 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l=i?s:VN({inputs:{logits:s},backend:n,attrs:{dim:-1}}),u=l.shape[0],c=l.shape[1],d=n.data.get(l.dataId).values,h=[u,a],p=k.makeZerosTypedArray(k.sizeFromShape(h),"int32");for(let f=0;f<u;++f){let m=f*c,g=new Float32Array(c-1);g[0]=d[m];for(let x=1;x<g.length;++x)g[x]=g[x-1]+d[m+x];let y=Sue.alea(o.toString()),A=f*a;for(let x=0;x<a;++x){let b=y();p[A+x]=g.length;for(let v=0;v<g.length;v++)if(b<g[v]){p[A+x]=v;break}}}return i||n.disposeIntermediateTensorInfo(l),n.makeTensorInfo(h,"int32",p)}var Cue={kernelName:Gy,backendName:"cpu",kernelFunc:Nue},Eue=ca.nonMaxSuppressionV3Impl;function $ue(e){let{inputs:t,backend:n,attrs:r}=e,{boxes:s,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l}=r;Te(s,"NonMaxSuppression");let u=n.data.get(s.dataId).values,c=n.data.get(a.dataId).values,{selectedIndices:d}=Eue(u,c,o,i,l);return n.makeTensorInfo([d.length],"int32",new Int32Array(d))}var _ue={kernelName:jc,backendName:"cpu",kernelFunc:$ue},Rue=ca.nonMaxSuppressionV4Impl;function Due(e){let{inputs:t,backend:n,attrs:r}=e,{boxes:s,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,padToMaxOutputSize:u}=r;Te(s,"NonMaxSuppressionPadded");let c=n.data.get(s.dataId).values,d=n.data.get(a.dataId).values,{selectedIndices:h,validOutputs:p}=Rue(c,d,o,i,l,u);return[n.makeTensorInfo([h.length],"int32",new Int32Array(h)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var Fue={kernelName:qc,backendName:"cpu",kernelFunc:Due},Mue=ca.nonMaxSuppressionV5Impl;function Oue(e){let{inputs:t,backend:n,attrs:r}=e,{boxes:s,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=r;Te(s,"NonMaxSuppressionWithScore");let c=n.data.get(s.dataId).values,d=n.data.get(a.dataId).values,h=o,p=i,f=l,m=u,{selectedIndices:g,selectedScores:y}=Mue(c,d,h,p,f,m);return[n.makeTensorInfo([g.length],"int32",new Int32Array(g)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var Pue={kernelName:Kc,backendName:"cpu",kernelFunc:Oue};function zue(e){let{inputs:t,backend:n,attrs:r}=e,{indices:s}=t,{depth:a,onValue:o,offValue:i}=r;Te(s,"oneHot");let l=k.sizeFromShape(s.shape),u=new Float32Array(l*a);u.fill(i);let c=n.data.get(s.dataId).values;for(let d=0;d<l;++d)c[d]>=0&&c[d]<a&&(u[d*a+c[d]]=o);return n.makeTensorInfo([...s.shape,a],"int32",u)}var Lue={kernelName:wl,backendName:"cpu",kernelFunc:zue};function Rm(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("zerosLike is not supported for string tensors");if(r.dtype==="complex64"){let s=pi({inputs:{input:r},backend:n}),a=Rm({inputs:{x:s},backend:n}),o=hu({inputs:{input:r},backend:n}),i=Rm({inputs:{x:o},backend:n}),l=fr({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return U5({backend:n,attrs:{shape:r.shape,value:0,dtype:r.dtype}})}var Bue={kernelName:hd,backendName:"cpu",kernelFunc:Rm};function UN(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("onesLike is not supported for string tensors");if(r.dtype==="complex64"){let s=pi({inputs:{input:r},backend:n}),a=UN({inputs:{x:s},backend:n}),o=hu({inputs:{input:r},backend:n}),i=Rm({inputs:{x:o},backend:n}),l=fr({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return U5({backend:n,attrs:{shape:r.shape,value:1,dtype:r.dtype}})}var Wue={kernelName:Xc,backendName:"cpu",kernelFunc:UN};function HN(e){let{inputs:t,backend:n,attrs:r}=e,{axis:s}=r;if(t.length===1)return _m({inputs:{input:t[0]},backend:n,attrs:{dim:s}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{k.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),k.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let 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t.makeTensorInfo([i.length],a,i)}var Kue={kernelName:sf,backendName:"cpu",kernelFunc:que},Xue=xt(Jc,e=>1/e),Zue={kernelName:Jc,backendName:"cpu",kernelFunc:Xue};function Yue(e){let{inputs:t,backend:n,attrs:r}=e,{images:s}=t,{alignCorners:a,halfPixelCenters:o,size:i}=r;Te(s,"resizeBilinear");let l=k.computeStrides(s.shape),[u,c]=i,[d,h,p,f]=s.shape,m=n.data.get(s.dataId).values,g=new Float32Array(k.sizeFromShape([d,u,c,f])),y=[a&&u>1?h-1:h,a&&c>1?p-1:p],A=[a&&u>1?u-1:u,a&&c>1?c-1:c],x=0,b=y[0]/A[0],v=y[1]/A[1];for(let w=0;w<d;w++)for(let I=0;I<u;I++){let T;o?T=b*(I+.5)-.5:T=b*I;let C=Math.max(0,Math.floor(T)),M=T-C,$=Math.min(h-1,Math.ceil(T)),R=w*l[0]+C*l[1],N=w*l[0]+$*l[1];for(let F=0;F<c;F++){let B;o?B=v*(F+.5)-.5:B=v*F;let j=Math.max(0,Math.floor(B)),X=B-j,Y=Math.min(p-1,Math.ceil(B)),ee=R+j*l[2],oe=N+j*l[2],se=R+Y*l[2],ie=N+Y*l[2];for(let ne=0;ne<f;ne++){let de=m[ee+ne],he=m[oe+ne],ge=m[se+ne],be=m[ie+ne],Ee=de+(ge-de)*X,$e=he+(be-he)*X,ze=Ee+($e-Ee)*M;g[x++]=ze}}}return 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      bvec4 isnan_custom(vec4 val) {
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      #define round(value) newRound(value)
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      }
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        return (val > 0. || val < 1. || val == 0.) ? false : true;
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    return c / 255.0;
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      }

      void main() {
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        vec4 result = vec4(0.);

        for (int i=0; i<4; i++) {
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        vec4 result = vec4(0.);

        for (int i=0; i<4; i++) {
          int flatIndex = index + i;
          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
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      }
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      ${bC}

      void main() {
        ivec3 coords = getOutputCoords();
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      }
    `}},Vde=class{constructor(e,t,n=!1){this.variableNames=["A"];let r=Wn(),[s,a]=t;this.outputShape=e;let o="result";n&&(o="floor(result * 255. + 0.5)"),this.userCode=`
      ${Z5(e)}

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

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

        int r = flatIndex / ${a};
        int c = imod(flatIndex, ${a});
        vec2 uv = (vec2(c, r) + halfCR) / vec2(${a}.0, ${s}.0);
        vec4 values = ${r.texture2D}(A, uv);

        float result;

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

        ${r.output} = vec4(${o}, 0., 0., 0.);
      }
    `}},Ude=class{constructor(e,t,n=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let r=Wn(),[s,a]=t;this.outputShape=e;let o="",i="result";n&&(i="floor(result * 255. + 0.5)");for(let l=0;l<=1;l++)for(let u=0;u<=1;u++){let c=l*2+u;o+=`
          localCoords = coords;
          if(localCoords[2] + ${u} < ${e[2]}) {
            localCoords[2] += ${u};
            if(localCoords[1] + ${l} < ${e[1]}) {
              localCoords[1] += ${l};

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

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

              r = flatIndex / ${a};
              c = imod(flatIndex, ${a});
              uv = (vec2(c, r) + halfCR) / vec2(${a}.0, ${s}.0);
              values = ${r.texture2D}(A, uv);

              if(offset == 0) {
                result[${c}] = values[0];
              } else if(offset == 1) {
                result[${c}] = values[1];
              } else if(offset == 2) {
                result[${c}] = values[2];
              } else {
                result[${c}] = values[3];
              }
            }
          }
        `}this.userCode=`
      ${Z5(e)}

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

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

        ${o}

        ${r.output} = ${i};
      }
    `}},vC={};De(vC,{bindVertexProgramAttributeStreams:()=>$C,createBufferFromOutputTexture:()=>DC,createFloat16MatrixTexture:()=>TC,createFloat16PackedMatrixTexture:()=>EC,createFloat32MatrixTexture:()=>SC,createIndexBuffer:()=>IC,createPackedMatrixTexture:()=>CC,createUnsignedBytesMatrixTexture:()=>NC,createVertexBuffer:()=>kC,createVertexShader:()=>wC,downloadByteEncodedFloatMatrixFromOutputTexture:()=>MC,downloadFloat32MatrixFromBuffer:()=>FC,downloadMatrixFromPackedOutputTexture:()=>PC,downloadPackedMatrixFromBuffer:()=>OC,getInternalFormatForFloat16MatrixTexture:()=>J5,getInternalFormatForFloat16PackedMatrixTexture:()=>tb,getInternalFormatForFloat32MatrixTexture:()=>Y5,getInternalFormatForPackedMatrixTexture:()=>eb,getInternalFormatForUnsignedBytesMatrixTexture:()=>Q5,uploadDenseMatrixToTexture:()=>_C,uploadPixelDataToTexture:()=>RC});function wC(e){let t=Wn(),n=`${t.version}
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    ${t.attribute} vec3 clipSpacePos;
    ${t.attribute} vec2 uv;
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      resultUV = uv;
    }`;return JN(e,n)}function kC(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 nC(e,t)}function IC(e){let t=new Uint16Array([0,1,2,2,1,3]);return rC(e,t)}function ch(e,t,n,r,s,a){aC(t,n);let o=sC(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)),Ie(e,()=>e.texImage2D(i,0,r,t,n,0,s,a,null)),Ie(e,()=>e.bindTexture(e.TEXTURE_2D,null)),o}function Y5(e){return e.internalFormatFloat}function SC(e,t,n,r){let[s,a]=ah(t,n);return ch(e,s,a,Y5(r),r.textureFormatFloat,e.FLOAT)}function J5(e){return e.internalFormatHalfFloat}function TC(e,t,n,r){let[s,a]=ah(t,n);return ch(e,s,a,J5(r),r.textureFormatFloat,r.textureTypeHalfFloat)}function Q5(e){return e.downloadTextureFormat}function NC(e,t,n,r){let[s,a]=ah(t,n);return ch(e,s,a,Q5(r),e.RGBA,e.UNSIGNED_BYTE)}function eb(e){return e.internalFormatPackedFloat}function CC(e,t,n,r){let[s,a]=fu(t,n);return ch(e,s,a,eb(r),e.RGBA,e.FLOAT)}function tb(e){return e.internalFormatPackedHalfFloat}function EC(e,t,n,r){let[s,a]=fu(t,n);return ch(e,s,a,tb(r),e.RGBA,r.textureTypeHalfFloat)}function $C(e,t,n){let r=0,s=3*4,a=3*4+2*4;return Ie(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),j5(e,t,"clipSpacePos",n,3,a,r)&&j5(e,t,"uv",n,2,a,s)}function _C(e,t,n,r,s,a){Ie(e,()=>e.bindTexture(e.TEXTURE_2D,t));let o,i,l;s instanceof Uint8Array?(o=new Uint8Array(n*r*4),i=e.UNSIGNED_BYTE,l=e.RGBA):(o=new Float32Array(n*r*4),i=e.FLOAT,l=a.internalFormatPackedFloat),o.set(s),Ie(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,n,r,0,e.RGBA,i,o)),Ie(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function RC(e,t,n){Ie(e,()=>e.bindTexture(e.TEXTURE_2D,t)),n.data instanceof Uint8Array?Ie(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,n.width,n.height,0,e.RGBA,e.UNSIGNED_BYTE,n.data)):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 DC(e,t,n,r){let s=e.createBuffer();Ie(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,s));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)),s}function FC(e,t,n){let r=e,s=new Float32Array(n);return r.bindBuffer(r.PIXEL_PACK_BUFFER,t),r.getBufferSubData(r.PIXEL_PACK_BUFFER,0,s),r.bindBuffer(r.PIXEL_PACK_BUFFER,null),s}function MC(e,t,n,r){let[s,a]=ah(t,n),o=4,i=new Uint8Array(Sde(t*n,o));return Ie(e,()=>e.readPixels(0,0,s,a,r.downloadTextureFormat,e.UNSIGNED_BYTE,i)),new Float32Array(i.buffer)}function OC(e,t,n,r,s,a,o,i){let l=e,u=new Float32Array(Tde(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 PC(e,t,n){let r=new Float32Array(t*n*4);return Ie(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,r)),r}var Bm=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=ae().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,Dm(t,e)):this.gl=Ls(t);let n="WEBGL_color_buffer_float",r="EXT_color_buffer_half_float";if(ae().getNumber("WEBGL_VERSION")===1){let s="OES_texture_float",a="OES_texture_half_float";if(this.textureFloatExtension=ih(this.gl,s),Lr(this.gl,a))this.textureHalfFloatExtension=ih(this.gl,a);else if(ae().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),Lr(this.gl,r))this.colorBufferHalfFloatExtension=ih(this.gl,r);else if(ae().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",Lr(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(Lr(this.gl,r))this.colorBufferHalfFloatExtension=this.gl.getExtension(r);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=kC(this.gl),this.indexBuffer=IC(this.gl),this.framebuffer=oC(this.gl),this.textureConfig=G5(this.gl,this.textureHalfFloatExtension)}get debug(){return ae().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(),SC(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),TC(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),NC(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),RC(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,r){this.throwIfDisposed(),_C(this.gl,e,t,n,r,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),EC(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),CC(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(q5(this.gl,this.framebuffer),this.outputTexture=null),Ie(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>MC(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,r,s,a){return OC(this.gl,e,t,n,r,s,a,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return FC(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let r=DC(this.gl,t,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),r}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,n;if(ae().getBool("WEBGL_FENCE_API_ENABLED")){let r=e,s=r.fenceSync(r.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let a=r.clientWaitSync(s,0,0);return a===r.ALREADY_SIGNALED||a===r.CONDITION_SATISFIED},t=s}else ae().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,ae().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>PC(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl,n=QN(t,e);this.vertexShader==null&&(this.vertexShader=wC(t));let r=eC(t);return Ie(t,()=>t.attachShader(r,this.vertexShader)),Ie(t,()=>t.attachShader(r,n)),tC(t,r),this.debug&&Fm(t,r),this.vertexAttrsAreBound||(this.setProgram(r),this.vertexAttrsAreBound=$C(t,this.program,this.vertexBuffer)),r}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?lC(this.gl,e,t):uC(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(),cC(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[r,s]=fu(t,n);this.setOutputMatrixTextureDriver(e,r,s)}setOutputMatrixWriteRegion(e,t,n,r){this.setOutputMatrixWriteRegionDriver(n,e,r,t)}setOutputPackedMatrixWriteRegion(e,t,n,r){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&Fm(this.gl,this.program),lh(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=ih(this.gl,ae().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(ae().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,r=this.getQueryTimerExtensionWebGL2(),s=n.createQuery();return n.beginQuery(r.TIME_ELAPSED_EXT,s),s}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(ae().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 k.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,ae().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,ae().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let n=this.gl;return n.getQueryParameter(e,n.QUERY_RESULT)/1e6}else{let n=this.getQueryTimerExtensionWebGL1();return n.getQueryObjectEXT(e,n.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let n=this.gl,r=this.getQueryTimerExtensionWebGL2(),s=n.getQueryParameter(e,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),s&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),r=n.getQueryObjectEXT(e,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),r&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=Hde(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)&&k.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0))}bindTextureToFrameBuffer(e){this.throwIfDisposed(),Mm(this.gl,e,this.framebuffer),this.debug&&lh(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(Mm(this.gl,this.outputTexture,this.framebuffer),this.debug&&lh(this.gl)):q5(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let n=t();return this.unbindTextureToFrameBuffer(),n}setOutputMatrixTextureDriver(e,t,n){this.throwIfDisposed();let r=this.gl;Mm(r,e,this.framebuffer),this.debug&&lh(r),this.outputTexture=e,Ie(r,()=>r.viewport(0,0,t,n)),Ie(r,()=>r.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,r){this.throwIfDisposed(),Ie(this.gl,()=>this.gl.scissor(e,t,n,r))}throwIfDisposed(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")}throwIfNoProgram(){if(this.program==null)throw new Error("No GPU program is currently set.")}};function Hde(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{getBroadcastDims:zC}=_;function Gde(e,t,n,r){let s=[];e.forEach(f=>{let m=k.sizeFromShape(f.shapeInfo.logicalShape);f.shapeInfo.isUniform?s.push(`uniform float ${f.name}${m>1?`[${m}]`:""};`):(s.push(`uniform sampler2D ${f.name};`),s.push(`uniform int offset${f.name};`))});let a=s.join(`
`),o=e.map(f=>jde(f,t,r)).join(`
`),i=t.texShape,l=Wn(),u=Xde(l),c,d,h=Jde(l);return t.isPacked?(c=qde(t.logicalShape,i),d=Yde(l)):(c=Kde(t.logicalShape,i),d=Zde(l)),r&&(h+=nhe),[h,u,d,a,c,o,n].join(`
`)}function gu(e){let t=e.shapeInfo.logicalShape;switch(t.length){case 0:return fhe(e);case 1:return ghe(e);case 2:return Ahe(e);case 3:return bhe(e);case 4:return whe(e);case 5:return khe(e);case 6:return Ihe(e);default:throw new Error(`${t.length}-D input sampling is not yet supported`)}}function LC(e){switch(e.shapeInfo.logicalShape.length){case 0:return phe(e);case 1:return mhe(e);case 2:return yhe(e);case 3:return xhe(e);default:return vhe(e)}}function jde(e,t,n=!1){let r="";n?r+=LC(e):r+=gu(e);let s=e.shapeInfo.logicalShape,a=t.logicalShape;return s.length<=a.length&&(n?r+=She(e,t):r+=The(e,t)),r}function qde(e,t){switch(e.length){case 0:return BC();case 1:return rhe(e,t);case 2:return dhe(e,t);case 3:return ahe(e,t);default:return ihe(e,t)}}function Kde(e,t){switch(e.length){case 0:return BC();case 1:return she(e,t);case 2:return hhe(e,t);case 3:return ohe(e,t);case 4:return lhe(e,t);case 5:return uhe(e,t);case 6:return che(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function Xde(e){return`
    float sampleTexture(sampler2D textureSampler, vec2 uv) {
      return ${e.texture2D}(textureSampler, uv).r;
    }
  `}function Zde(e){return`
    void setOutput(float val) {
      ${e.output} = vec4(val, 0, 0, 0);
    }
  `}function Yde(e){return`
    void setOutput(vec4 val) {
      ${e.output} = val;
    }
  `}function Jde(e){return`${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);
    }

    ${Qde}
    ${ehe}
    ${the}
  `}var Qde=`
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);
}
`,ehe=`
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);
}
`,the=`
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);
}
`,nhe=`
  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 BC(){return`
    int getOutputCoords() {
      return 0;
    }
  `}function rhe(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?`
      int getOutputCoords() {
        return 2 * int(resultUV.x * ${n[1]}.0);
      }
    `:n[1]===1?`
      int getOutputCoords() {
        return 2 * int(resultUV.y * ${n[0]}.0);
      }
    `:`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${n[0]}, ${n[1]}));
      return 2 * (resTexRC.x * ${n[1]} + resTexRC.y);
    }
  `}function she(e,t){return t[0]===1?`
      int getOutputCoords() {
        return int(resultUV.x * ${t[1]}.0);
      }
    `:t[1]===1?`
      int getOutputCoords() {
        return int(resultUV.y * ${t[0]}.0);
      }
    `:`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      return resTexRC.x * ${t[1]} + resTexRC.y;
    }
  `}function ahe(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),s=r*Math.ceil(e[1]/2);return`
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${n[0]}, ${n[1]}));
      int index = resTexRC.x * ${n[1]} + resTexRC.y;

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

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

      return ivec3(b, r, c);
    }
  `}function ohe(e,t){let n=Ai(["r","c","d"],e);return`
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      ${n}
      return ivec3(r, c, d);
    }
  `}function ihe(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),s=r*Math.ceil(e[e.length-2]/2),a=s,o="",i="b, r, c";for(let l=2;l<e.length-1;l++)a*=e[e.length-l-1],o=`
      int b${l} = index / ${a};
      index -= b${l} * ${a};
    `+o,i=`b${l}, `+i;return`
    ivec${e.length} getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${n[0]}, ${n[1]}));
      int index = resTexRC.x * ${n[1]} + resTexRC.y;

      ${o}

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

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

      return ivec${e.length}(${i});
    }
  `}function lhe(e,t){let n=Ai(["r","c","d","d2"],e);return`
    ivec4 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      ${n}
      return ivec4(r, c, d, d2);
    }
  `}function uhe(e,t){let n=Ai(["r","c","d","d2","d3"],e);return`
    ivec5 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
                             ${t[1]}));

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

      ${n}

      ivec5 outShape = ivec5(r, c, d, d2, d3);
      return outShape;
    }
  `}function che(e,t){let n=Ai(["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 dhe(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(k.arraysEqual(e,t))return`
      ivec2 getOutputCoords() {
        return 2 * ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]}));
      }
    `;let r=Math.ceil(e[1]/2);return`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${n[0]}, ${n[1]}));

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

      return ivec2(r, c);
    }
  `}function hhe(e,t){return k.arraysEqual(e,t)?`
      ivec2 getOutputCoords() {
        return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
      }
    `:e[1]===1?`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(${t[0]}, ${t[1]}));
        int index = resTexRC.x * ${t[1]} + resTexRC.y;
        return ivec2(index, 0);
      }
    `:e[0]===1?`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(${t[0]}, ${t[1]}));
        int index = resTexRC.x * ${t[1]} + resTexRC.y;
        return ivec2(0, index);
      }
    `:`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      int r = index / ${e[1]};
      int c = index - r * ${e[1]};
      return ivec2(r, c);
    }
  `}function xi(e){return`offset${e}`}function phe(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=Wn();return`
    vec4 ${n}() {
      return ${r.texture2D}(${t}, halfCR);
    }
  `}function fhe(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${t};}`;let[r,s]=e.shapeInfo.texShape;if(r===1&&s===1)return`
      float ${n}() {
        return sampleTexture(${t}, halfCR);
      }
    `;let[a,o]=e.shapeInfo.texShape,i=xi(t);return`
    float ${n}() {
      vec2 uv = uvFromFlat(${a}, ${o}, ${i});
      return sampleTexture(${t}, uv);
    }
  `}function mhe(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=e.shapeInfo.texShape,s=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],a=Wn();return`
    vec4 ${n}(int index) {
      vec2 uv = packedUVfrom1D(
        ${s[0]}, ${s[1]}, index);
      return ${a.texture2D}(${t}, uv);
    }
  `}function ghe(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`
      float ${n}(int index) {
        ${yu(e)}
      }
    `;let r=e.shapeInfo.texShape,s=r[0],a=r[1];if(a===1&&s===1)return`
      float ${n}(int index) {
        return sampleTexture(${t}, halfCR);
      }
    `;let o=xi(t);return a===1?`
      float ${n}(int index) {
        vec2 uv = vec2(0.5, (float(index + ${o}) + 0.5) / ${s}.0);
        return sampleTexture(${t}, uv);
      }
    `:s===1?`
      float ${n}(int index) {
        vec2 uv = vec2((float(index + ${o}) + 0.5) / ${a}.0, 0.5);
        return sampleTexture(${t}, uv);
      }
    `:`
    float ${n}(int index) {
      vec2 uv = uvFromFlat(${s}, ${a}, index + ${o});
      return sampleTexture(${t}, uv);
    }
  `}function yhe(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e.shapeInfo.texShape,a=s[0],o=s[1],i=Wn();if(s!=null&&k.arraysEqual(t,s))return`
      vec4 ${r}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${o}.0, ${a}.0);

        return ${i.texture2D}(${n}, uv);
      }
    `;let l=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],u=Math.ceil(t[1]/2);return`
    vec4 ${r}(int row, int col) {
      vec2 uv = packedUVfrom2D(${u}, ${l[0]}, ${l[1]}, row, col);
      return ${i.texture2D}(${n}, uv);
    }
  `}function Ahe(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e.shapeInfo.texShape;if(s!=null&&k.arraysEqual(t,s)){let d=s[0],h=s[1];return`
    float ${r}(int row, int col) {
      vec2 uv = (vec2(col, row) + halfCR) / vec2(${h}.0, ${d}.0);
      return sampleTexture(${n}, uv);
    }
  `}let{newShape:a,keptDims:o}=k.squeezeShape(t),i=a;if(i.length<t.length){let d=Au(e,i),h=["row","col"];return`
      ${gu(d)}
      float ${r}(int row, int col) {
        return ${r}(${xu(h,o)});
      }
    `}if(e.shapeInfo.isUniform)return`
      float ${r}(int row, int col) {
        int index = round(dot(vec2(row, col), vec2(${t[1]}, 1)));
        ${yu(e)}
      }
    `;let l=s[0],u=s[1],c=xi(n);return u===1?`
    float ${r}(int row, int col) {
      float index = dot(vec3(row, col, ${c}), vec3(${t[1]}, 1, 1));
      vec2 uv = vec2(0.5, (index + 0.5) / ${l}.0);
      return sampleTexture(${n}, uv);
    }
  `:l===1?`
    float ${r}(int row, int col) {
      float index = dot(vec3(row, col, ${c}), vec3(${t[1]}, 1, 1));
      vec2 uv = vec2((index + 0.5) / ${u}.0, 0.5);
      return sampleTexture(${n}, uv);
    }
  `:`
  float ${r}(int row, int col) {
    // Explicitly use integer operations as dot() only works on floats.
    int index = row * ${t[1]} + col + ${c};
    vec2 uv = uvFromFlat(${l}, ${u}, index);
    return sampleTexture(${n}, uv);
  }
`}function xhe(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e.shapeInfo.texShape,a=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)];if(t[0]===1){let d=t.slice(1),h=[1,2],p=Au(e,d),f=["b","row","col"];return`
        ${LC(p)}
        vec4 ${r}(int b, int row, int col) {
          return ${r}(${xu(f,h)});
        }
      `}let o=a[0],i=a[1],l=Math.ceil(t[2]/2),u=l*Math.ceil(t[1]/2),c=Wn();return`
    vec4 ${r}(int b, int row, int col) {
      vec2 uv = packedUVfrom3D(
        ${o}, ${i}, ${u}, ${l}, b, row, col);
      return ${c.texture2D}(${n}, uv);
    }
  `}function bhe(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),s=t[1]*t[2],a=t[2],{newShape:o,keptDims:i}=k.squeezeShape(t),l=o;if(l.length<t.length){let f=Au(e,l),m=["row","col","depth"];return`
        ${gu(f)}
        float ${r}(int row, int col, int depth) {
          return ${r}(${xu(m,i)});
        }
      `}if(e.shapeInfo.isUniform)return`
      float ${r}(int row, int col, int depth) {
        int index = round(dot(vec3(row, col, depth),
                          vec3(${s}, ${a}, 1)));
        ${yu(e)}
      }
    `;let u=e.shapeInfo.texShape,c=u[0],d=u[1],h=e.shapeInfo.flatOffset;if(d===s&&h==null)return`
        float ${r}(int row, int col, int depth) {
          float texR = float(row);
          float texC = dot(vec2(col, depth), vec2(${a}, 1));
          vec2 uv = (vec2(texC, texR) + halfCR) /
                     vec2(${d}.0, ${c}.0);
          return sampleTexture(${n}, uv);
        }
      `;if(d===a&&h==null)return`
    float ${r}(int row, int col, int depth) {
      float texR = dot(vec2(row, col), vec2(${t[1]}, 1));
      float texC = float(depth);
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${d}.0, ${c}.0);
      return sampleTexture(${n}, uv);
    }
  `;let p=xi(n);return`
      float ${r}(int row, int col, int depth) {
        // Explicitly use integer operations as dot() only works on floats.
        int index = row * ${s} + col * ${a} + depth + ${p};
        vec2 uv = uvFromFlat(${c}, ${d}, index);
        return sampleTexture(${n}, uv);
      }
  `}function vhe(e){let t=e.shapeInfo.logicalShape,n=t.length,r=e.name,s="get"+r.charAt(0).toUpperCase()+r.slice(1),a=e.shapeInfo.texShape,o=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],i=o[0],l=o[1],u=Math.ceil(t[n-1]/2),c=u*Math.ceil(t[n-2]/2),d="int b, int row, int col",h=`b * ${c} + (row / 2) * ${u} + (col / 2)`;for(let f=2;f<n-1;f++)d=`int b${f}, `+d,c*=t[n-f-1],h=`b${f} * ${c} + `+h;let p=Wn();return`
    vec4 ${s}(${d}) {
      int index = ${h};
      int texR = index / ${l};
      int texC = index - texR * ${l};
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${l}, ${i});
      return ${p.texture2D}(${r}, uv);
    }
  `}function whe(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),s=t[3],a=t[2]*s,o=t[1]*a,{newShape:i,keptDims:l}=k.squeezeShape(t);if(i.length<t.length){let f=Au(e,i),m=["row","col","depth","depth2"];return`
      ${gu(f)}
      float ${r}(int row, int col, int depth, int depth2) {
        return ${r}(${xu(m,l)});
      }
    `}if(e.shapeInfo.isUniform)return`
      float ${r}(int row, int col, int depth, int depth2) {
        int index = round(dot(vec4(row, col, depth, depth2),
                          vec4(${o}, ${a}, ${s}, 1)));
        ${yu(e)}
      }
    `;let u=e.shapeInfo.flatOffset,c=e.shapeInfo.texShape,d=c[0],h=c[1];if(h===o&&u==null)return`
      float ${r}(int row, int col, int depth, int depth2) {
        float texR = float(row);
        float texC =
            dot(vec3(col, depth, depth2),
                vec3(${a}, ${s}, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${h}.0, ${d}.0);
        return sampleTexture(${n}, uv);
      }
    `;if(h===s&&u==null)return`
      float ${r}(int row, int col, int depth, int depth2) {
        float texR = dot(vec3(row, col, depth),
                         vec3(${t[1]*t[2]}, ${t[2]}, 1));
        float texC = float(depth2);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${h}.0, ${d}.0);
        return sampleTexture(${n}, uv);
      }
    `;let p=xi(n);return`
    float ${r}(int row, int col, int depth, int depth2) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${o} + col * ${a} +
          depth * ${s} + depth2;
      vec2 uv = uvFromFlat(${d}, ${h}, index + ${p});
      return sampleTexture(${n}, uv);
    }
  `}function khe(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),s=t[4],a=t[3]*s,o=t[2]*a,i=t[1]*o,{newShape:l,keptDims:u}=k.squeezeShape(t);if(l.length<t.length){let m=Au(e,l),g=["row","col","depth","depth2","depth3"];return`
      ${gu(m)}
      float ${r}(int row, int col, int depth, int depth2, int depth3) {
        return ${r}(${xu(g,u)});
      }
    `}if(e.shapeInfo.isUniform)return`
      float ${r}(int row, int col, int depth, int depth2, int depth3) {
        float index = dot(
          vec4(row, col, depth, depth2),
          vec4(${i}, ${o}, ${a}, ${s})) +
          depth3;
        ${yu(e)}
      }
    `;let c=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,h=d[0],p=d[1];if(p===i&&c==null)return`
      float ${r}(int row, int col, int depth, int depth2, int depth3) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
                         vec4(${o}, ${a}, ${s}, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${p}.0, ${h}.0);
        return sampleTexture(${n}, uv);
      }
    `;if(p===s&&c==null)return`
      float ${r}(int row, int col, int depth, int depth2, int depth3) {
        float texR = dot(
          vec4(row, col, depth, depth2),
          vec4(${t[1]*t[2]*t[3]},
               ${t[2]*t[3]}, ${t[3]}, 1));
        int texC = depth3;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${p}.0, ${h}.0);
        return sampleTexture(${n}, uv);
      }
    `;let f=xi(n);return`
    float ${r}(int row, int col, int depth, int depth2, int depth3) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${i} + col * ${o} + depth * ${a} +
          depth2 * ${s} + depth3 + ${f};
      vec2 uv = uvFromFlat(${h}, ${p}, index);
      return sampleTexture(${n}, uv);
    }
  `}function Ihe(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:s,keptDims:a}=k.squeezeShape(t);if(s.length<t.length){let g=Au(e,s),y=["row","col","depth","depth2","depth3","depth4"];return`
      ${gu(g)}
      float ${r}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        return ${r}(${xu(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 ${r}(int row, int col, int depth,
                  int depth2, int depth3, int depth4) {
        int index = round(dot(
          vec4(row, col, depth, depth2),
          vec4(${c}, ${u}, ${l}, ${i})) +
          dot(
            vec2(depth3, depth4),
            vec2(${o}, 1)));
        ${yu(e)}
      }
    `;let d=e.shapeInfo.flatOffset,h=e.shapeInfo.texShape,p=h[0],f=h[1];if(f===c&&d==null)return`
      float ${r}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
          vec4(${u}, ${l}, ${i}, ${o})) +
               float(depth4);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${f}.0, ${p}.0);
        return sampleTexture(${n}, uv);
      }
    `;if(f===o&&d==null)return`
      float ${r}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        float texR = dot(vec4(row, col, depth, depth2),
          vec4(${t[1]*t[2]*t[3]*t[4]},
               ${t[2]*t[3]*t[4]},
               ${t[3]*t[4]},
               ${t[4]})) + float(depth3);
        int texC = depth4;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${f}.0, ${p}.0);
        return sampleTexture(${n}, uv);
      }
    `;let m=xi(n);return`
    float ${r}(int row, int col, int depth,
                  int depth2, int depth3, int depth4) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${c} + col * ${u} + depth * ${l} +
          depth2 * ${i} + depth3 * ${o} + depth4 + ${m};
      vec2 uv = uvFromFlat(${p}, ${f}, index);
      return sampleTexture(${n}, uv);
    }
  `}function yu(e){let t=e.name,n=k.sizeFromShape(e.shapeInfo.logicalShape);return n<2?`return ${t};`:`
    for (int i = 0; i < ${n}; i++) {
      if (i == index) {
        return ${t}[i];
      }
    }
  `}function She(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),s="get"+r+"AtOutCoords",a=e.shapeInfo.logicalShape.length,o=t.logicalShape.length,i=zC(e.shapeInfo.logicalShape,t.logicalShape),l=It(o),u=o-a,c,d=["x","y","z","w","u","v"];a===0?c="":o<2&&i.length>=1?c="coords = 0;":c=i.map(A=>`coords.${d[A+u]} = 0;`).join(`
`);let h="";o<2&&a>0?h="coords":h=e.shapeInfo.logicalShape.map((A,x)=>`coords.${d[x+u]}`).join(", ");let p="return outputValue;",m=k.sizeFromShape(e.shapeInfo.logicalShape)===1,y=k.sizeFromShape(t.logicalShape)===1;if(a===1&&!m&&!y)p=`
      return vec4(outputValue.xy, outputValue.xy);
    `;else if(m&&!y)o===1?p=`
        return vec4(outputValue.x, outputValue.x, 0., 0.);
      `:p=`
        return vec4(outputValue.x);
      `;else if(i.length){let A=a-2,x=a-1;i.indexOf(A)>-1&&i.indexOf(x)>-1?p="return vec4(outputValue.x);":i.indexOf(A)>-1?p="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":i.indexOf(x)>-1&&(p="return vec4(outputValue.xx, outputValue.zz);")}return`
    vec4 ${s}() {
      ${l} coords = getOutputCoords();
      ${c}
      vec4 outputValue = get${r}(${h});
      ${p}
    }
  `}function The(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),s="get"+r+"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&&k.arraysEqual(o,a))return`
      float ${s}() {
        return sampleTexture(${n}, resultUV);
      }
    `;let u=It(l),c=zC(e.shapeInfo.logicalShape,t.logicalShape),d=l-i,h,p=["x","y","z","w","u","v"];i===0?h="":l<2&&c.length>=1?h="coords = 0;":h=c.map(m=>`coords.${p[m+d]} = 0;`).join(`
`);let f="";return l<2&&i>0?f="coords":f=e.shapeInfo.logicalShape.map((m,g)=>`coords.${p[g+d]}`).join(", "),`
    float ${s}() {
      ${u} coords = getOutputCoords();
      ${h}
      return get${r}(${f});
    }
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          setOutput(vec4(getA(), 0., 0., 0.));
        }
      `;else{let n=Vn("rc",t),r=It(t),s=Wpe(t,e,n),a=Vpe(t,e[e.length-1],e[e.length-2],n),o=Upe(e,n);this.userCode=`
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          ${r} rc = getOutputCoords();

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

            setOutput(vec4(${o}));
          }
        }
      `}}};function Bpe(e,t){let n=[];for(let r=0;r<=1;r++)for(let s=0;s<=1;s++){let a=`${r===0?"r":"rp1"}, ${s===0?"c":"cp1"}`;for(let o=2;o<e;o++)a=`${t[t.length-1-o]},`+a;n.push(a)}return n}function Wpe(e,t,n){if(e===1)return`rc > ${t[0]}`;let r="";for(let s=e-2;s<e;s++)r+=`${n[s]} >= ${t[s]}`,s<e-1&&(r+="||");return r}function Vpe(e,t,n,r){if(e===1)return"";let s=r.slice(-2);return`
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    int c = ${s[1]};
    int rp1 = r + 1;
    int cp1 = c + 1;

    bool cEdge = cp1 >= ${t};
    bool rEdge = rp1 >= ${n};
  `}function Upe(e,t){let n=e.length,r=Bpe(n,t);return n===1?`getA(rc),
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            0, 0`:`getA(${r[0]}),
          cEdge ? 0. : getA(${r[1]}),
          rEdge ? 0. : getA(${r[2]}),
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        ${s}
        ${r>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
          int flatIndex = getFlatIndex(thisRC);

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

          result[${r}] =
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      `}this.userCode=`
      ${Hpe(t)}
      ${Z5(e)}

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

        vec4 result = vec4(0.);

        ivec3 thisRC;
        int rows = ${e[1]};
        int cols = ${e[2]};

        ${n}

        setOutput(result);
      }
    `}};function Hpe(e){return`
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      ${Ai(["r","c","d"],e)}
      return ivec3(r, c, d);
    }
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      float unaryOperation(float x) {
        ${t}
      }

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

        setOutput(y);
      }
    `}},ys="if (isnan(x)) return x;",Xpe="return x;",AE="return abs(x);",Zpe="return (x >= 0.0) ? x : (exp(x) - 1.0);",Ype=ys+`
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`,Jpe=ys+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,Vm="return x;",Qpe="return 1.0 / (1.0 + exp(-1.0 * x));",efe="return x;",tfe=`
  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;
`,nfe=`
  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;
`,rfe=`
  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;
`,sfe="return 1.0 / (1.0 + exp(-1.0 * x));",wu=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
      vec4 unaryOperation(vec4 x) {
        ${t}
      }

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

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

        setOutput(getChannel(packedInput, ${o}));
      }
    `}},ofe=ca.whereImpl,ife=1e-7,lfe=1e-4,Um={};function ufe(e){return e in Um||(Um[e]={}),Um[e]}var cfe=ae().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),dfe=600;function hfe(){return ae().global.screen==null?1024:ae().global.screen.height*ae().global.screen.width*window.devicePixelRatio*dfe/1024/1024}var xE=class extends Bp{constructor(e){super();if(this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.pendingDeletes=0,this.disposed=!1,!ae().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Ls(ae().getNumber("WEBGL_VERSION"));this.binaryCache=ufe(ae().getNumber("WEBGL_VERSION")),this.gpgpu=new Bm(t),this.canvas=t.canvas,this.gpgpuCreatedLocally=!0}else this.gpgpu=e,this.binaryCache={},this.gpgpuCreatedLocally=!1,this.canvas=e.gl.canvas;this.textureManager=new Gpe(this.gpgpu),this.numMBBeforeWarning=hfe(),this.texData=new my(this,za())}nextDataId(){return xE.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}write(e,t,n){if((ae().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||ae().getBool("DEBUG"))&&this.checkNumericalProblems(e),n==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let r={id:this.nextDataId()};return this.texData.set(r,{shape:t,dtype:n,values:e,usage:zr.UPLOAD,refCount:1}),r}refCount(e){return this.texData.has(e)?this.texData.get(e).refCount:0}incRef(e){let t=this.texData.get(e);t.refCount++}decRef(e){if(this.texData.has(e)){let t=this.texData.get(e);t.refCount--}}move(e,t,n,r,s){if(ae().getBool("DEBUG")&&this.checkNumericalProblems(t),r==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:r,values:t,usage:zr.UPLOAD,refCount:s})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:r,complexTensorInfos:s,slice:a,shape:o,isPacked:i}=t;if(a!=null){let d;i?d=new wu(o,Vm):d=new Qa(o,Vm);let h=this.runWebGLProgram(d,[{dataId:e,shape:o,dtype:r}],r),p=this.readSync(h.dataId);return this.disposeIntermediateTensorInfo(h),p}if(n!=null)return this.convertAndCacheOnCPU(e);if(r==="string")return n;let l=this.activeTimers!=null,u;l&&(u=k.now());let c;if(r==="complex64"){let d=this.readSync(s.real.dataId),h=this.readSync(s.imag.dataId);c=_.mergeRealAndImagArrays(d,h)}else c=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=k.now()-u),this.convertAndCacheOnCPU(e,c)}async read(e){if(this.pendingRead.has(e)){let p=this.pendingRead.get(e);return new Promise(f=>p.push(f))}let t=this.texData.get(e),{values:n,shape:r,slice:s,dtype:a,complexTensorInfos:o,isPacked:i}=t;if(s!=null){let p;i?p=new wu(r,Vm):p=new Qa(r,Vm);let f=this.runWebGLProgram(p,[{dataId:e,shape:r,dtype:a}],a),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(!ae().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&ae().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"&&ae().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let p=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...oh(r))}this.pendingRead.set(e,[]),a!=="complex64"&&await this.gpgpu.createAndWaitForFence();let c;if(a==="complex64"){let p=await Promise.all([this.read(o.real.dataId),this.read(o.imag.dataId)]),f=p[0],m=p[1];c=_.mergeRealAndImagArrays(f,m)}else if(l==null)c=this.getValuesFromTexture(e);else{let p=k.sizeFromShape(r);c=this.gpgpu.downloadFloat32MatrixFromBuffer(l,p)}u!=null&&this.disposeIntermediateTensorInfo(u);let d=this.convertAndCacheOnCPU(e,c),h=this.pendingRead.get(e);return this.pendingRead.delete(e),h.forEach(p=>p(d)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&za().removeDataId(e,this),this.pendingDeletes--),d}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(r=>k.decodeString(r))}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return Le(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!ZN(n))throw ae().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:r}=this.texData.get(e),s=k.sizeFromShape(t);if(ae().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let d=this.decode(e),h=this.texData.get(d.dataId),p=this.gpgpu.downloadMatrixFromPackedTexture(h.texture,...oh(t)).subarray(0,s);return this.disposeIntermediateTensorInfo(d),p}let a=ae().getBool("WEBGL_PACK")&&r===!0,o=a?Om(t):t,i=a?new Wde(o):new Bde(o),l=this.runWebGLProgram(i,[{shape:o,dtype:n,dataId:e}],"float32"),u=this.texData.get(l.dataId),c=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture,u.texShape[0],u.texShape[1]).subarray(0,s);return this.disposeIntermediateTensorInfo(l),c}timerAvailable(){return ae().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,e();let s=k.flatten(this.activeTimers.map(i=>i.query)).filter(i=>i!=null),a=k.flatten(this.activeTimers.map(i=>i.name)).filter(i=>i!=null);this.activeTimers=t,r&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(ae().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let i=await Promise.all(s);o.kernelMs=k.sum(i),o.getExtraProfileInfo=()=>i.map((l,u)=>({name:a[u],ms:l})).map(l=>`${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 ae().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:k.now(),endMs:null}}endTimer(e){return ae().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=k.now(),e)}async getQueryTime(e){if(ae().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:r,usage:s,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(r,n),this.textureManager.releaseTexture(t,r,s,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}getDataInfo(e){return this.texData.get(e)}shouldExecuteOnCPU(e,t=cfe){return ae().getBool("WEBGL_CPU_FORWARD")&&e.every(n=>this.texData.get(n.dataId).texture==null&&k.sizeFromShape(n.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){_.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return ofe(e.shape,t)}packedUnaryOp(e,t,n){let r=new wu(e.shape,t),s=this.compileAndRun(r,[e],n);return za().makeTensorFromDataId(s.dataId,s.shape,s.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let r=dE(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,r)}if(ae().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,AE,e.dtype);let t=new Qa(e.shape,AE),n=this.compileAndRun(t,[e]);return za().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(e,t,n){let r;if(t==="string"&&n!=null&&n.length>0&&k.isString(n[0])){let s=n.map(a=>k.encodeString(a));r=this.write(s,e,t)}else r=this.write(n,e,t);return this.texData.get(r).usage=null,{dataId:r,shape:e,dtype:t}}makeOutput(e,t,n){let{dataId:r}=this.makeTensorInfo(e,t,n);return za().makeTensorFromDataId(r,e,t,this)}unpackTensor(e){let t=new afe(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new Lpe(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[gi(e.shape),...yi(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},s=[gi(t),...yi(t)],a=new fE(s,n),o=!0,i=this.runWebGLProgram(a,[r],e.dtype,null,o);return{dataId:i.dataId,shape:t,dtype:i.dtype}}decode(e){let t=this.texData.get(e),{isPacked:n,shape:r,dtype:s}=t,a=Om(r),o;n?o=new Lde(a):o=new zde(a);let i=!0,l=this.runWebGLProgram(o,[{shape:a,dtype:s,dataId:e}],s,null,i);return{dtype:s,shape:r,dataId:l.dataId}}runWebGLProgram(e,t,n,r,s=!1){let a=this.makeTensorInfo(e.outputShape,n),o=this.texData.get(a.dataId);if(e.packedOutput&&(o.isPacked=!0),e.outPackingScheme===sh.DENSE){let m=oh(e.outputShape);o.texShape=m.map(g=>g*2)}if(e.outTexUsage!=null&&(o.usage=e.outTexUsage),k.sizeFromShape(a.shape)===0)return o.values=k.getTypedArrayFromDType(a.dtype,0),a;let i=[],l=t.map(m=>{if(m.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let g=this.texData.get(m.dataId);if(g.texture==null){if(!e.packedInputs&&k.sizeFromShape(m.shape)<=ae().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:m.shape,texData:null,isUniform:!0,uniformValues:g.values};e.packedInputs&&(g.isPacked=!0,g.shape=m.shape)}else if(!!g.isPacked!=!!e.packedInputs)m=g.isPacked?this.unpackTensor(m):this.packTensor(m),i.push(m),g=this.texData.get(m.dataId);else if(g.isPacked&&!uh(g.shape,m.shape)){let y=m,A=m.shape;m.shape=g.shape,m=this.packedReshape(m,A),i.push(m),g=this.texData.get(m.dataId),y.shape=A}return this.uploadToGPU(m.dataId),{shape:m.shape,texData:g,isUniform:!1}});this.uploadToGPU(a.dataId);let u={shape:a.shape,texData:o,isUniform:!1},c=Ehe(e,l,u),d=this.getAndSaveBinary(c,()=>Nhe(this.gpgpu,e,l,u)),h=this.activeTimers!=null,p;h&&(p=this.startTimer()),Che(this.gpgpu,d,l,u,r),i.forEach(m=>this.disposeIntermediateTensorInfo(m)),h&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)}));let f=ae().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let m=k.now();m-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=m)}if(!ae().getBool("WEBGL_LAZILY_UNPACK")&&o.isPacked&&s===!1){let m=this.unpackTensor(a);return this.disposeIntermediateTensorInfo(a),m}return a}compileAndRun(e,t,n,r,s=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,r,s)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(ae().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=Z(()=>{if(!ae().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=ae().getBool("DEBUG");ae().set("DEBUG",!1);let t=this.abs(Fe(1e-8)).dataSync()[0];if(ae().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?ife:lfe}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:r,values:s,texture:a,usage:o,isPacked:i}=t;if(a!=null)return;let l=this.activeTimers!=null,u;l&&(u=k.now());let c=t.texShape;if(c==null&&(c=pC(n,i),t.texShape=c),s!=null){let d=Om(n),h,p=c[1],f=c[0],m=s instanceof Uint8Array;i?([p,f]=fu(c[0],c[1]),h=new Ude(d,[f,p],m)):h=new Vde(d,[f,p],m);let g=this.makeTensorInfo([f,p],r);m?this.texData.get(g.dataId).usage=zr.PIXELS:this.texData.get(g.dataId).usage=zr.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(g.dataId),p,f,s);let y=!0,A=this.runWebGLProgram(h,[g],r,null,y),x=this.texData.get(A.dataId);t.texture=x.texture,t.texShape=x.texShape,t.isPacked=x.isPacked,t.usage=x.usage,this.disposeIntermediateTensorInfo(g),this.texData.delete(A.dataId),t.values=null,l&&(this.uploadWaitMs+=k.now()-u)}else{let d=this.acquireTexture(c,o,r,i);t.texture=d}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:r}=n;return this.releaseGPUData(e),t!=null&&(n.values=pfe(t,r)),n.values}acquireTexture(e,t,n,r){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let s=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${s} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,r)}computeBytes(e,t){return e[0]*e[1]*k.bytesPerElement(t)}},dh=xE;dh.nextDataId=0;function pfe(e,t){if(t==="float32"||t==="complex64")return e;if(t==="int32"||t==="bool"){let n=t==="int32"?new Int32Array(e.length):new Uint8Array(e.length);for(let r=0;r<n.length;++r)n[r]=Math.round(e[r]);return n}else throw new Error(`Unknown dtype ${t}`)}var ffe="3.7.0";function bE(){ae().set("WEBGL_FORCE_F16_TEXTURES",!0)}yf.isBrowser()&&_A("webgl",()=>new dh,2);var mfe={forceHalfFloat:bE},vE=`
  if (isnan(a)) return a;
  if (isnan(b)) return b;
`,ku=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=_.assertAndGetBroadcastShape(t,n),this.userCode=`
      float binaryOperation(float a, float b) {
        ${e}
      }

      void main() {
        float a = getAAtOutCoords();
        float b = getBAtOutCoords();
        setOutput(binaryOperation(a, b));
      }
    `}},Hm=`
  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;
`,hh=class{constructor(e,t,n,r=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=_.assertAndGetBroadcastShape(t,n);let s=this.outputShape.length,a="";if(r)if(s===0||k.sizeFromShape(this.outputShape)===1)a=`
          result.y = 0.;
          result.z = 0.;
          result.w = 0.;
        `;else if(a=`
          ${It(s)} coords = getOutputCoords();
        `,s===1)a+=`
            result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
            result.z = 0.;
            result.w = 0.;
          `;else{let i=Vn("coords",s);a+=`
            bool nextRowOutOfBounds =
              (${i[s-2]} + 1) >= ${this.outputShape[s-2]};
            bool nextColOutOfBounds =
              (${i[s-1]} + 1) >= ${this.outputShape[s-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 mr(e){let{inputs:t,backend:n}=e,{x:r}=t;return n.incRef(r.dataId),{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}var gfe={kernelName:hl,backendName:"webgl",kernelFunc:mr};function eo(e){let{inputs:t,backend:n}=e,{real:r,imag:s}=t,a=n.makeTensorInfo(r.shape,"complex64"),o=n.texData.get(a.dataId),i=mr({inputs:{x:r},backend:n}),l=mr({inputs:{x:s},backend:n});return o.complexTensorInfos={real:i,imag:l},a}var yfe={kernelName:Sy,backendName:"webgl",kernelFunc:eo},wE="return (a < 0.) ? b * a : a;",kE=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function Afe(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{alpha:a}=r,o=n.makeTensorInfo([],"float32",k.createScalarValue(a,"float32")),i=ae().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new hh(kE,s.shape,o.shape):new ku(wE,s.shape,o.shape),l=n.runWebGLProgram(i,[s,o],s.dtype);return n.disposeIntermediateTensorInfo(o),l}var xfe={kernelName:pl,backendName:"webgl",kernelFunc:Afe},IE="return (a < 0.) ? b * a : a;",SE=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function bfe(e){let{inputs:t,backend:n}=e,{x:r,alpha:s}=t,a=ae().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new hh(SE,r.shape,s.shape):new ku(IE,r.shape,s.shape);return n.runWebGLProgram(a,[r,s],r.dtype)}var vfe={kernelName:Sl,backendName:"webgl",kernelFunc:bfe},TE="if (isnan(x)) return x;",wfe=`
  if (isnan(a)) return a;
  if (isnan(b)) return b;
`,kfe=`
  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 it({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:r}){return({inputs:s,backend:a})=>{let{x:o}=s,i=a,l=r||o.dtype;if(i.shouldExecuteOnCPU([o])&&n!=null){let d=i.texData.get(o.dataId),h=n(d.values,l);return i.makeTensorInfo(o.shape,l,h)}let u=ae().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return u?c=new wu(o.shape,t):c=new Qa(o.shape,e),i.runWebGLProgram(c,[o],l)}}function Nn({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:r=!1,cpuKernelImpl:s,dtype:a}){return({inputs:o,backend:i})=>{let{a:l,b:u}=o,c=i;if(r&&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(x=>{let[b,v]=x,w={dataId:b.dataId,dtype:b.dtype,shape:l.shape},I={dataId:v.dataId,dtype:v.dtype,shape:u.shape},T=new ku(e,l.shape,u.shape);return c.runWebGLProgram(T,[w,I],qr(b.dtype,v.dtype))}),A=eo({inputs:{real:g,imag:y},backend:c});return c.disposeIntermediateTensorInfo(g),c.disposeIntermediateTensorInfo(y),A}let d=a||qr(l.dtype,u.dtype);if((l.dtype==="string"||u.dtype==="string"||c.shouldExecuteOnCPU([l,u]))&&s!=null){let f=c.texData.get(l.dataId).values,m=c.texData.get(u.dataId).values,g=l.dtype==="string"?_.fromUint8ToStringArray(f):f,y=l.dtype==="string"?_.fromUint8ToStringArray(m):m,[A,x]=s(l.shape,u.shape,g,y,d),b=c.makeTensorInfo(x,d),v=c.texData.get(b.dataId);return v.values=A,b}let h=ae().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return h?p=new hh(t,l.shape,u.shape,n):p=new ku(e,l.shape,u.shape),c.runWebGLProgram(p,[l,u],d)}}function Gm(e,t=!1){if(e==="linear")return t?efe:Xpe;if(e==="relu")return t?nfe:Ype;if(e==="elu")return t?tfe:Zpe;if(e==="relu6")return t?rfe:Jpe;if(e==="prelu")return t?SE:IE;if(e==="leakyrelu")return t?kE:wE;if(e==="sigmoid")return t?sfe:Qpe;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var NE=class{constructor(e,t,n,r=!1,s=!1,a=!1,o=null,i=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n;let u=r?e[1]:e[2],c=Math.ceil(u/2),d=r?"i * 2, rc.y":"rc.y, i * 2",h=s?"rc.z, i * 2":"i * 2, rc.z",p=r?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=s?["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 A="rc.x",x="rc.x";e[0]<t[0]?A=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(x=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
      ${m}

      const float sharedDimension = ${c}.0;

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

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

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

        ${y}

        ${g}

        setOutput(result);
      }
    `}},CE={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},EE=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=_.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));
      }
    `}},$E="return a * b;";function lb(e){let{inputs:t,backend:n}=e,{a:r,b:s}=t,a=_.upcastType(r.dtype,s.dtype);if(r.dtype==="complex64"){let i=n.texData.get(r.dataId),l=n.texData.get(s.dataId),u=new EE(CE.REAL,r.shape,s.shape),c=new EE(CE.IMAG,r.shape,s.shape),d=[{dataId:i.complexTensorInfos.real.dataId,dtype:i.complexTensorInfos.real.dtype,shape:r.shape},{dataId:i.complexTensorInfos.imag.dataId,dtype:i.complexTensorInfos.imag.dtype,shape:r.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:s.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:s.shape}],h=n.runWebGLProgram(u,d,"float32"),p=n.runWebGLProgram(c,d,"float32"),f=eo({inputs:{real:h,imag:p},backend:n});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p),f}if(n.shouldExecuteOnCPU([r,s])){let i=n.texData.get(r.dataId),l=n.texData.get(s.dataId),[u,c]=vpe(r.shape,s.shape,i.values,l.values,a),d=n.makeTensorInfo(c,a),h=n.texData.get(d.dataId);return h.values=u,d}let o;return ae().getBool("WEBGL_PACK_BINARY_OPERATIONS")?o=new hh($E,r.shape,s.shape):o=new ku($E,r.shape,s.shape),n.runWebGLProgram(o,[r,s],a)}var Ife={kernelName:Mo,backendName:"webgl",kernelFunc:lb};function Sfe(e,t,n){let r=[gi(e.shape),...yi(e.shape)],s={dtype:e.dtype,shape:r,dataId:e.dataId},a=[gi(t),...yi(t)],o=new fE(a,r),i=!0,l=n.runWebGLProgram(o,[s],e.dtype,null,i);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function ve(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{shape:a}=r,o=n,i=k.sizeFromShape(s.shape),l=k.inferFromImplicitShape(a,i),u=k.sizeFromShape(l);k.assert(i===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${s.shape}) has ${i} elements. The new shape and old shape must have the same number of elements.`);let c=o.texData.get(s.dataId);return c.isPacked&&!uh(s.shape,l)&&!(c.texture!==null&&uh(c.shape,l))?Sfe(s,l,o):(o.incRef(s.dataId),{dataId:s.dataId,shape:l,dtype:s.dtype})}var Tfe={kernelName:Qc,backendName:"webgl",kernelFunc:ve},_E=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:s,outSize:a}=e;this.outputShape=[r,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 * ${k.isInt(c)?c.toPrecision(2):c}, ones);`}let u="";s%n>0&&(u=`
        if (inIdx < 0 || inIdx >= ${s}) {
          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);

          ${l}
        }
        setOutput(sumValue);
      }
    `}},Nfe=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:s,outSize:a}=e;this.outputShape=[r,a];let o="0.0",i="";t==="prod"?o="1.0":t==="min"?(o="1.0 / 1e-20",i="min"):t==="max"&&(o="-1.0 / 1e-20",i="max");let l=`${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,d=`
      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);
          }
        }
      }
    `,h="vec4";t==="all"?(o="1.0",d=`
        bool reducedAllValue = all(values);
        float floatedReducedAllValue = float(reducedAllValue);
        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
      `,h="bvec4"):t==="any"&&(o="0.0",d=`
        bool reducedAnyValue = any(values);
        float floatedReducedAnyValue = float(reducedAnyValue);
        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
      `,h="bvec4");let p="";s%n>0&&(p=`
        if (inIdx < 0 || inIdx >= ${s}) {
          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) {
        ${p}
        return getX(batch, inIdx);
      }

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

        vec4 minMaxValue = vec4(${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;
          ${h} values = ${h}(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          ${d}
        }

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

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

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

          ${d}
        }
        setOutput(${l});
      }
    `}};function Cfe(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let n=t.length?t[t.length-1].outSize:e[1],r=_.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}function bi(e,t,n,r){let s=Cfe(e.shape),a=e;for(let o=0;o<s.length;o++){let{inSize:i,windowSize:l,outSize:u}=s[o],c,d;n==="mean"?c=o===0?new _E({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u},i):new _E({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u}):c=new Nfe({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u},n),d=a,a=r.runWebGLProgram(c,[a],t),d.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(d)}return a}var Efe=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 r=It(this.rank),s=$fe(t);this.userCode=`
    void main() {
      ${r} resRC = getOutputCoords();
      setOutput(getA(${s}));
    }
    `}};function $fe(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(t);for(let s=0;s<e.length;s++)r[e[s]]=n[s];return r.join()}var _fe=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(e.length);for(let u=0;u<n.length;u++)n[u]=e[t[u]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let r=It(this.rank),s=pE("rc",this.rank),a=new Array(this.rank);for(let u=0;u<t.length;u++)a[t[u]]=s[u];let o=`vec2(${a.slice(-2).join()})`,i=`++${s[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${a.join()}), ${o})`;this.userCode=`
    void main() {
      ${r} rc = getOutputCoords();
      vec4 result = vec4(0.);
      result[0] = ${l};
      if(${i}) {
        result[1] = ${l};
      }
      --${s[this.rank-1]};
      if(++${s[this.rank-2]} < ${n[this.rank-2]}) {
        result[2] = ${l};
        if(${i}) {
          result[3] = ${l};
        }
      }
      setOutput(result);
    }
    `}};function jm(e,t,n){let r=ae().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new _fe(e.shape,t):new Efe(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function Rfe(e,t,n,r){let s=t,a=e.shape.length,o=k.parseAxisParam(s,e.shape),i=o,l=_.getAxesPermutation(i,a),u=l!=null,c=e;u&&(c=jm(e,l,r),i=_.getInnerMostAxes(i.length,a)),_.assertAxesAreInnerMostDims("sum",i,a);let[d,h]=_.computeOutAndReduceShapes(c.shape,i),p=d;n&&(p=_.expandShapeToKeepDim(d,o));let f=k.sizeFromShape(h),g=k.sizeFromShape(e.shape)/f,y=ve({inputs:{x:c},attrs:{shape:[g,f]},backend:r}),A=fA(e.dtype),x=bi(y,A,"sum",r),b=ve({inputs:{x},attrs:{shape:p},backend:r});return r.disposeIntermediateTensorInfo(y),r.disposeIntermediateTensorInfo(x),u&&r.disposeIntermediateTensorInfo(c),b}function qm(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{axis:a,keepDims:o}=r;return Rfe(s,a,o,n)}var Dfe={kernelName:Fl,backendName:"webgl",kernelFunc:qm};function Un(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{perm:a}=r,o=n,i=s.shape.length,l=new Array(i);for(let c=0;c<l.length;c++)l[c]=s.shape[a[c]];let u;if(o.shouldExecuteOnCPU([s])){let d=o.texData.get(s.dataId).values,h=ib(d,s.shape,s.dtype,a,l);u=o.makeTensorInfo(l,s.dtype);let p=o.texData.get(u.dataId);p.values=h}else u=jm(s,a,o);return u}var Ffe={kernelName:zl,backendName:"webgl",kernelFunc:Un},RE=1e3;function Km({a:e,b:t,transposeA:n,transposeB:r,backend:s,bias:a=null,preluActivationWeights:o=null,leakyreluAlpha:i=0,activation:l=null}){let u=e.shape.length,c=t.shape.length,d=n?e.shape[u-2]:e.shape[u-1],h=r?t.shape[c-1]:t.shape[c-2],p=n?e.shape[u-1]:e.shape[u-2],f=r?t.shape[c-2]:t.shape[c-1],m=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=k.sizeFromShape(m),A=k.sizeFromShape(g),x=y===A||y===1||A===1;k.assert(u>=2&&c>=2&&x,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${m}) and (${g}).`);let v=(y>A?e.shape.slice(0,-2):t.shape.slice(0,-2)).concat([p,f]);k.assert(d===h,()=>`Error in matMul: inner shapes (${d}) and (${h}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${r} must match.`);let w=n?[y,d,p]:[y,p,d],I=r?[A,f,h]:[A,h,f],T=ve({inputs:{x:e},backend:s,attrs:{shape:w}}),C=ve({inputs:{x:t},backend:s,attrs:{shape:I}}),M=[T,C],$=Math.max(y,A),R=n?T.shape[1]:T.shape[2],N=a!=null,F=o!=null,B=l==="leakyrelu",j=l!=null?Gm(l,!0):null,X=N||F||B||j!=null,Y;if((p===1||f===1)&&R>RE&&X===!1){let oe=T,se=C;n&&(oe=Un({inputs:{x:T},backend:s,attrs:{perm:[0,2,1]}}),M.push(oe)),r&&(se=Un({inputs:{x:C},backend:s,attrs:{perm:[0,2,1]}}),M.push(se));let ie=f!==1,ne=f===1,de=oe;ie&&(de=ve({inputs:{x:oe},backend:s,attrs:{shape:[$,R,1]}}),M.push(de));let he=f===1?2:1,ge=se;ne&&(ge=ve({inputs:{x:se},backend:s,attrs:{shape:[$,1,R]}}),M.push(ge));let be=lb({inputs:{a:de,b:ge},backend:s});Y=qm({inputs:{x:be},backend:s,attrs:{axis:he,keepDims:!0}}),M.push(be)}else{let oe=qr(e.dtype,t.dtype),se=new NE(w,I,[$,p,f],n,r,N,j,F,B),ie=[T,C];if(a!=null&&ie.push(a),F&&ie.push(o),B){let ne=s.makeTensorInfo([],"float32",k.createScalarValue(i,"float32"));ie.push(ne),M.push(ne)}Y=s.runWebGLProgram(se,ie,oe)}let ee=ve({inputs:{x:Y},backend:s,attrs:{shape:v}});M.push(Y);for(let oe of M)s.disposeIntermediateTensorInfo(oe);return ee}function Mfe(e){let{inputs:t,backend:n,attrs:r}=e,{a:s,b:a,bias:o,preluActivationWeights:i}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:d}=r;return Km({a:s,b:a,transposeA:l,transposeB:u,backend:n,bias:o,preluActivationWeights:i,leakyreluAlpha:d,activation:c})}var Ofe={kernelName:Ll,backendName:"webgl",kernelFunc:Mfe},DE="return abs(x);";function Pfe(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])&&r.dtype!=="complex64"){let a=n.texData.get(r.dataId),o=dE(a.values);return n.makeTensorInfo(r.shape,r.dtype,o)}let s;return ae().getBool("WEBGL_PACK_UNARY_OPERATIONS")?s=new wu(r.shape,DE):s=new Qa(r.shape,DE),n.runWebGLProgram(s,[r],r.dtype)}var zfe={kernelName:xc,backendName:"webgl",kernelFunc:Pfe},Lfe=ys+`
  if (abs(x) > 1.) {
    return NAN;
  }
  return acos(x);
`,Bfe=it({opSnippet:Lfe}),Wfe={kernelName:bc,backendName:"webgl",kernelFunc:Bfe},Vfe=ys+`
  if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,Ufe=it({opSnippet:Vfe}),Hfe={kernelName:vc,backendName:"webgl",kernelFunc:Ufe},FE="return a + b;",Gfe=Nn({opSnippet:FE,packedOpSnippet:FE,supportsComplex:!0,cpuKernelImpl:npe}),jfe={kernelName:Fa,backendName:"webgl",kernelFunc:Gfe},qfe=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((s,a)=>`T${a}`);let n=[];this.variableNames.forEach(s=>{n.push(`float v${s} = get${s}AtOutCoords();`)});let r=this.variableNames.map(s=>`v${s}`).join(" + ");this.userCode=`
      void main() {
        ${n.join(`
        `)}

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

        vec4 result = ${r};
        setOutput(result);
      }
    `}};function Xm(e){let{inputs:t,backend:n}=e,r=t;if(r.length===1)return mr({inputs:{x:r[0]},backend:n});if(r.length>ae().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let l=Math.floor(r.length/2),u=Xm({inputs:r.slice(0,l),backend:n}),c=Xm({inputs:r.slice(l),backend:n});return Xm({inputs:[u,c],backend:n})}let s=r.map(l=>l.dtype).reduce((l,u)=>qr(l,u)),a=r.map(l=>l.shape),i=ae().getBool("WEBGL_PACK")?new Kfe(r[0].shape,a):new qfe(r[0].shape,a);return n.runWebGLProgram(i,r,s)}var Xfe={kernelName:Zi,backendName:"webgl",kernelFunc:Xm};function Zfe(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{axis:a,keepDims:o}=r,i=s.shape.length,l=k.parseAxisParam(a,s.shape),u=l,c=_.getAxesPermutation(u,i),d=s;c!=null&&(d=Un({inputs:{x:s},backend:n,attrs:{perm:c}}),u=_.getInnerMostAxes(u.length,i)),_.assertAxesAreInnerMostDims("all",u,i);let[h,p]=_.computeOutAndReduceShapes(d.shape,u),f=k.sizeFromShape(p),m=ve({inputs:{x:d},backend:n,attrs:{shape:[-1,f]}}),g=bi(m,m.dtype,"all",n),y;if(o){let A=_.expandShapeToKeepDim(h,l);y=ve({inputs:{x:g},backend:n,attrs:{shape:A}})}else y=ve({inputs:{x:g},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(d),y}var Yfe={kernelName:wc,backendName:"webgl",kernelFunc:Zfe};function Jfe(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{axis:a,keepDims:o}=r,i=s.shape.length,l=k.parseAxisParam(a,s.shape),u=l,c=_.getAxesPermutation(u,i),d=s;c!=null&&(d=Un({inputs:{x:s},backend:n,attrs:{perm:c}}),u=_.getInnerMostAxes(u.length,i)),_.assertAxesAreInnerMostDims("any",u,i);let[h,p]=_.computeOutAndReduceShapes(d.shape,u),f=k.sizeFromShape(p),m=ve({inputs:{x:d},backend:n,attrs:{shape:[-1,f]}}),g=bi(m,m.dtype,"any",n),y;if(o){let A=_.expandShapeToKeepDim(h,l);y=ve({inputs:{x:g},backend:n,attrs:{shape:A}})}else y=ve({inputs:{x:g},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(d),y}var Qfe={kernelName:kc,backendName:"webgl",kernelFunc:Jfe},eme=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:r,batchSize:s,outSize:a}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[s,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 * ${r};

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

        for (int i = 0; i < ${r}; i++) {
          int inIdx = ${i};
          float candidate = getA(batch, inIdx);
          if (candidate ${o} bestValue) {
            bestValue = candidate;
            bestIndex = inIdx;
          }
        }
        setOutput(float(bestIndex));
      }
    `}},tme=class{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,k.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let s=e[e.length-1],a=Math.ceil(s/t);this.outputShape=e.slice(0,-1),a>1&&this.outputShape.push(a),r||this.variableNames.push("bestIndicesA");let o=this.outputShape,i=o.length,l=It(i),u=Vn("coords",i),c,d;if(a===1){d=i+1;let I=It(d);c=`
        ${I} sourceLocR = ${I}(${u.join()}, 0);
        ++${u[i-1]};
        ${I} sourceLocG = ${I}(${u.join()}, 0);
        ++${u[i-2]};
        ${I} sourceLocA = ${I}(${u.join()}, 0);
        --${u[i-1]};
        ${I} sourceLocB = ${I}(${u.join()}, 0);
        --${u[i-2]};`}else d=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 h=["x","y","z","w","u","v"].slice(0,d),p="."+h[d-1],f=h.map(I=>"int "+I),m=Vn("sourceLocR",d-1).concat("inIdx.r"),g=Vn("sourceLocG",d-1).concat("inIdx.g"),y=Vn("sourceLocB",d-1).concat("inIdx.b"),A=Vn("sourceLocA",d-1).concat("inIdx.a"),x=n==="max"?"greaterThan":"lessThan",b=r?"":`
          inIdx = round(vec4(getBestIndicesAChannel(${m.join()}),
                             getBestIndicesAChannel(${g.join()}),
                             getBestIndicesAChannel(${y.join()}),
                             getBestIndicesAChannel(${A.join()})));`,v=`vec4(
            getAChannel(${m.join()}),
            hasNextCol ? getAChannel(${g.join()}) : 0.,
            hasNextRow ? getAChannel(${y.join()}) : 0.,
            hasNextRow && hasNextCol ? getAChannel(${A.join()}) : 0.)`,w=r?"":`
      float getBestIndicesAChannel(${f.join()}) {
        return getChannel(getBestIndicesA(${h.join()}),
                                          vec2(${h.slice(-2).join()}));
      }`;this.userCode=`
      float getAChannel(${f.join()}) {
        return getChannel(getA(${h.join()}),
                               vec2(${h.slice(-2).join()}));
      }
      ${w}
      void main() {
        ${l} coords = getOutputCoords();
        bool hasNextCol = ${u[i-1]} < ${o[i-1]-1};
        bool hasNextRow = ${u[i-2]} < ${o[i-2]-1};
        ${c}
        ivec4 srcIdx = ivec4(sourceLocR${p}, sourceLocG${p},
          sourceLocB${p}, sourceLocA${p}) * ${t};
        ivec4 inIdx = srcIdx;
        vec4 bestIndex = vec4(inIdx);
        vec4 bestValue = ${v};

        for (int i = 0; i < ${t}; i++) {
          inIdx = srcIdx;
          ${b}
          vec4 candidate = ${v};
          bvec4 nan = isnan(candidate);
          bvec4 replace = bvec4(
            vec4(${x}(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 ME(e,t,n,r=null){let s=t.shape[0],a=t.shape[1];r!=null&&(s=r.shape[0],a=r.shape[1]);let o=_.computeOptimalWindowSize(a),i={windowSize:o,inSize:a,batchSize:s,outSize:Math.ceil(a/o)},l=new eme(i,n,r==null),u=[t];r!=null&&u.push(r);let c=e.runWebGLProgram(l,u,"int32");if(c.shape[1]===1)return c;let d=ME(e,t,n,c);return e.disposeIntermediateTensorInfo(c),d}function OE(e,t,n,r=null){let s=r!=null?r.shape:t.shape,a=s[s.length-1],o=_.computeOptimalWindowSize(a),i=new tme(s,o,n,r==null),l=r==null?[t]:[t,r],u=e.runWebGLProgram(i,l,"int32");if(u.shape.length===t.shape.length){let c=OE(e,t,n,u);return e.disposeIntermediateTensorInfo(u),c}return u}function PE(e,t,n,r){let s=[n];if(_.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),s,t.shape.length),!ae().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let a=[],[o,i]=_.computeOutAndReduceShapes(t.shape,s),l=k.sizeFromShape(i),u=ve({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});a.push(u);let c=ME(e,u,r);a.push(c);let d=ve({inputs:{x:c},backend:e,attrs:{shape:o}});return a.forEach(h=>e.disposeIntermediateTensorInfo(h)),d}return OE(e,t,r)}function nme(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{axis:a}=r,o=k.parseAxisParam(a,s.shape),i=_.getAxesPermutation(o,s.shape.length),l=s,u=[];i!=null&&(l=Un({inputs:{x:s},backend:n,attrs:{perm:i}}),u.push(l),o=_.getInnerMostAxes(o.length,l.shape.length)),_.assertAxesAreInnerMostDims("argMax",[o[0]],l.shape.length);let c=PE(n,l,o[0],"max");return u.forEach(d=>n.disposeIntermediateTensorInfo(d)),c}var rme={kernelName:Yi,backendName:"webgl",kernelFunc:nme};function sme(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{axis:a}=r,o=k.parseAxisParam(a,s.shape),i=_.getAxesPermutation(o,s.shape.length),l=s,u=[];i!=null&&(l=Un({inputs:{x:s},backend:n,attrs:{perm:i}}),u.push(l),o=_.getInnerMostAxes(o.length,l.shape.length)),_.assertAxesAreInnerMostDims("argMin",[o[0]],l.shape.length);let c=PE(n,l,o[0],"min");return u.forEach(d=>n.disposeIntermediateTensorInfo(d)),c}var ame={kernelName:qp,backendName:"webgl",kernelFunc:sme},ome=ys+`
  if (abs(x) > 1.) {
    return NAN;
  }
  return asin(x);
`,ime=it({opSnippet:ome}),lme={kernelName:Ic,backendName:"webgl",kernelFunc:ime},ume=ys+"return log(x + sqrt(x * x + 1.0));",cme=it({opSnippet:ume}),dme={kernelName:Sc,backendName:"webgl",kernelFunc:cme},hme=ys+`
  return atan(x);
`,pme=it({opSnippet:hme}),fme={kernelName:Tc,backendName:"webgl",kernelFunc:pme},mme=wfe+`
  return atan(a, b);
`,gme=`
  vec4 result = atan(a, b);
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  `+kfe+`
  return result;
`,yme=Nn({opSnippet:mme,packedOpSnippet:gme}),Ame={kernelName:Cc,backendName:"webgl",kernelFunc:yme},xme=ys+`
  if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,bme=it({opSnippet:xme}),vme={kernelName:Nc,backendName:"webgl",kernelFunc:bme},ph=class{constructor(e,t,n,r=!1,s=!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,d=e.effectiveFilterWidth,h=e.padInfo.top,p=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,g=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let I=">=";this.userCode=`
        const ivec2 strides = ivec2(${o}, ${i});
        const ivec2 pads = ivec2(${h}, ${p});

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

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

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

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

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

            for (int wC = 0; wC < ${d};
                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 ${I} currMinMaxValue) {
                minMaxValue = value;
                minMaxValueFound = 1.0;
                minMaxPosition = ${r?s?m:g:`wR * ${d} + wC`};
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;return}let A="max",x=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(x="avgValue / count");let b=Math.floor(a/4)*4,v=a%4,w=`
      if (${f}) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ${A}(values, minMaxValue);
      }
    `;this.userCode=`
      const ivec2 strides = ivec2(${o}, ${i});
      const ivec2 pads = ivec2(${h}, ${p});
      const float initializationValue = ${y};
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float count = 0.0;

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

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

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

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

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

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

          for (int wC = 0; wC < ${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)
            );

            ${w}
          }

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

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

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

            ${w}
          }
        }
        setOutput(${x});
      }
    `}},ub=class{constructor(e,t,n,r=!1,s=!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,d=e.dilationWidth,h=e.effectiveFilterDepth,p=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,g=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let A=t==="avg",x="0.0";if(A||(x="-1.0 / 1e-20"),n){let C=">=";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 < ${h};
              wD += ${u}) {
            int xD = xDCorner + wD;

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

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

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

              for (int wC = 0; wC < ${f};
                  wC += ${d}) {
                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 ${C} currMinMaxValue) {
                  minMaxValue = value;
                  minMaxValueFound = 1.0;
                  minMaxPosition = ${r?s?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${p} * ${f} +
                      wR * ${f} + wC`};
                }
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;return}let b="max",v=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(v="avgValue / count");let w=Math.floor(a/4)*4,I=a%4,T=`
      if (${A}) {
        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 = ${x};
      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(${x});
        float avgValue = 0.0;
        count = 0.0;

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

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

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

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

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

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

              ${T}
            }

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

              ${T}
            } else if (${I===2}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ${d}, ch),
                initializationValue,
                initializationValue
              );

              ${T}
            } else if (${I===3}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ${d}, ch),
                getValue(batch, xD, xR, xC + 2 * ${d}, ch),
                initializationValue
              );

              ${T}
            }
          }
          setOutput(${v});
        }
      }
    `}};function wme(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t;mu(s,"avgPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=r,u=1;k.assert(_.eitherStridesOrDilationsAreOne(o,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=_.computePool2DInfo(s.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&k.arraysEqual(c.inShape,c.outShape))return mr({inputs:{x:s},backend:n});let d=new ph(c,"avg",!1);return n.runWebGLProgram(d,[s],"float32")}var kme={kernelName:Ji,backendName:"webgl",kernelFunc:wme};function Ime(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l,dataFormat:u}=r,c=[1,1,1],d=_.computePool3DInfo(s.shape,a,o,c,i,l,u),h=new ub(d,"avg",!1);return n.runWebGLProgram(h,[s],"float32")}var Sme={kernelName:Kp,backendName:"webgl",kernelFunc:Ime},Tme=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,s=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,d=1/(t*n);this.userCode=`
      const ivec2 pads = ivec2(${u}, ${c});
      const float avgMultiplier = float(${d});

      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) / ${r}.0;

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

          for (int wC = 0; wC < ${l};
            wC+= ${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(b, idyR, idyC, d);

            dotProd += dyValue * avgMultiplier;
          }
        }
        setOutput(dotProd);
      }
    `}},Nme=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,s=e.strideDepth,a=e.strideHeight,o=e.strideWidth,i=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,d=e.effectiveFilterHeight,h=e.effectiveFilterWidth,p=c-1-e.padInfo.front,f=d-1-e.padInfo.top,m=h-1-e.padInfo.left,g=1/(t*n*r);this.userCode=`
      const ivec3 pads = ivec3(${p}, ${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) / ${s}.0;

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

          for (int wR = 0; wR < ${d};
              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 < ${h};
                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 Cme(e){let{inputs:t,backend:n,attrs:r}=e,{dy:s,input:a}=t,o=a,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=r,d=[1,1,1],h=_.computePool3DInfo(o.shape,i,l,d,u,c),p=new Nme(h);return n.runWebGLProgram(p,[s],o.dtype)}var Eme={kernelName:ky,backendName:"webgl",kernelFunc:Cme};function $me(e){let{inputs:t,backend:n,attrs:r}=e,{dy:s,input:a}=t,o=a;mu([s,a],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=r,c=_.computePool2DInfo(o.shape,i,l,1,u),d=new Tme(c);return n.runWebGLProgram(d,[s],o.dtype)}var _me={kernelName:wy,backendName:"webgl",kernelFunc:$me};function Rme(e){let{inputs:t,backend:n,attrs:r}=e,{a:s,b:a}=t,{transposeA:o,transposeB:i}=r;return Km({a:s,b:a,transposeA:o,transposeB:i,backend:n})}var Dme={kernelName:Qi,backendName:"webgl",kernelFunc:Rme},Fme=class{constructor(e,t,n,r,s,a){this.outputShape=[],this.variableNames=["x","mean","variance"],_.assertAndGetBroadcastShape(e,t),_.assertAndGetBroadcastShape(e,n);let o="0.0";r!=null&&(_.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),o="getOffsetAtOutCoords()");let i="1.0";s!=null&&(_.assertAndGetBroadcastShape(e,s),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)));
      }
    `}},Mme=class{constructor(e,t,n,r,s,a){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],_.assertAndGetBroadcastShape(e,t),_.assertAndGetBroadcastShape(e,n);let o="vec4(0.0)";r!=null&&(_.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),o="getOffsetAtOutCoords()");let i="vec4(1.0)";s!=null&&(_.assertAndGetBroadcastShape(e,s),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);
      }
    `}},Ome=({inputs:e,backend:t,attrs:n})=>{let{x:r,mean:s,variance:a,offset:o,scale:i}=e;k.assert(s.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),k.assert(o==null||s.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),k.assert(i==null||s.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=[r,s,a],c=null;o!=null&&(c=o.shape,u.push(o));let d=null;i!=null&&(d=i.shape,u.push(i));let h=ae().getBool("WEBGL_PACK_NORMALIZATION")?new Mme(r.shape,s.shape,a.shape,c,d,l):new Fme(r.shape,s.shape,a.shape,c,d,l);return t.runWebGLProgram(h,u,u[0].dtype)},Pme={kernelName:cl,backendName:"webgl",kernelFunc:Ome},zme=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=It(this.rank),n=`uniform int start[${this.rank}];`,r=Lme(this.rank),s,a=e.map((o,i)=>`sourceLoc.${cb[i]} = start[${i}] + coords.${cb[i]};`);s=`
        ${t} sourceLoc;
        ${t} coords = getOutputCoords();
        ${a.join(`
`)}
      `,this.userCode=`
      ${n}
      void main() {
        ${s}
        setOutput(getSource(${r}));
      }
    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}},cb=["x","y","z","w","u","v"];function Lme(e){if(e===1)return"sourceLoc";if(e<=6)return cb.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var Bme=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=It(this.rank),n=Vn("coords",this.rank),r=Vn("sourceLoc",this.rank),s=this.rank===1?"sourceLoc":`vec2(${r.slice(-2).join()})`,a=`getChannel(getSource(${r.join()}), ${s})`,o=`
      result.x = ${a};
      if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
        ++${r[this.rank-1]};
        result.y = ${a};
        --${r[this.rank-1]};
      }
    `,i=this.rank===1?"":`
      --${n[this.rank-1]};
      if (++${n[this.rank-2]} < ${e[this.rank-2]}) {
        ++${r[this.rank-2]};
        result.z = ${a};
        if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
          ++${r[this.rank-1]};
          result.w = ${a};
        }
      }
    `,l=this.rank<=4?`sourceLoc = coords +
            ${t}(${e.map((u,c)=>`start[${c}]`).join()});`:e.map((u,c)=>`${r[c]} = ${n[c]} + start[${c}];`).join(`
`);this.userCode=`
      uniform int start[${this.rank}];
      void main() {
        ${t} coords = getOutputCoords();
        ${t} sourceLoc;
        ${l}
        vec4 result = vec4(0.);
        ${o}
        ${i}
        setOutput(result);
      }
    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}};function Wme(e,t,n,r){let s=r.texData.get(e.dataId),a=r.makeTensorInfo(n,e.dtype),o=r.texData.get(a.dataId);Object.assign(o,s),o.refCount=1,o.shape=n,o.dtype=e.dtype;let i=En.computeFlatOffset(t,k.computeStrides(e.shape));s.slice&&(i+=s.slice.flatOffset),o.slice={flatOffset:i,origDataId:s.slice&&s.slice.origDataId||e.dataId};let l=r.dataRefCount.get(o.slice.origDataId)||1;return r.dataRefCount.set(o.slice.origDataId,l+1),a}function fh(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{begin:a,size:o}=r,[i,l]=En.parseSliceParams(s,a,o);if(En.assertParamsValid(s,i,l),k.sizeFromShape(l)===0)return n.makeTensorInfo(l,s.dtype,[]);if(n.shouldExecuteOnCPU([s])||s.dtype==="string"){let d=n.texData.get(s.dataId),h=Npe(d.values,i,l,s.shape,s.dtype);return n.makeTensorInfo(l,s.dtype,h)}let{isPacked:u}=n.texData.get(s.dataId),c=En.isSliceContinous(s.shape,i,l);if(u||!c){let d=ae().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Bme(l):new zme(l),h=d.getCustomSetupFunc(i);return n.runWebGLProgram(d,[s],s.dtype,h)}return n.uploadToGPU(s.dataId),Wme(s,i,l,n)}var Vme={kernelName:rd,backendName:"webgl",kernelFunc:fh},Ume=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{blockShape:a,crops:o}=r;k.assert(s.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let i=a.reduce((A,x)=>A*x),l=_.getReshaped(s.shape,a,i),u=_.getPermuted(l.length,a.length),c=_.getReshapedPermuted(s.shape,a,i),d=_.getSliceBeginCoords(o,a.length),h=_.getSliceSize(c,o,a.length),p=[],f=ve({inputs:{x:s},backend:n,attrs:{shape:l}}),m=Un({inputs:{x:f},backend:n,attrs:{perm:u}}),g=ve({inputs:{x:m},backend:n,attrs:{shape:c}}),y=fh({inputs:{x:g},backend:n,attrs:{begin:d,size:h}});return p.push(f),p.push(m),p.push(g),p.forEach(A=>n.disposeIntermediateTensorInfo(A)),y},Hme={kernelName:Xp,backendName:"webgl",kernelFunc:Ume};function Gme(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,weights:a}=t,{size:o}=r,i=n.readSync(s.dataId),l=n.readSync(a.dataId),u=cE(i,l,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,u)}var jme={kernelName:Iy,backendName:"webgl",kernelFunc:Gme},qme="return float(a != b);",zE=Nn({opSnippet:qme,cpuKernelImpl:kpe,dtype:"bool"}),Kme={kernelName:vl,backendName:"webgl",kernelFunc:zE};function mh(e){let{inputs:t,backend:n}=e,{input:r}=t,s=n.texData.get(r.dataId);return mr({inputs:{x:s.complexTensorInfos.real},backend:n})}var Xme={kernelName:jy,backendName:"webgl",kernelFunc:mh},Zme="return float(int(x));";function Yme(e,t){let n=new Qa(e.shape,Zme),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}function db(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{dtype:a}=r;if(a==="complex64"){if(s.dtype==="complex64")return mr({inputs:{x:s},backend:n});let o=un(s.shape),i=db({inputs:{x:s},backend:n,attrs:{dtype:"float32"}}),l=eo({inputs:{real:i,imag:o},backend:n});return o.dispose(),n.disposeIntermediateTensorInfo(i),l}if(s.dtype==="complex64"){let o=mh({inputs:{input:s},backend:n}),i=db({inputs:{x:o},backend:n,attrs:{dtype:a}});return n.disposeIntermediateTensorInfo(o),i}if(!k.hasEncodingLoss(s.dtype,a)){let o=mr({inputs:{x:s},backend:n});return{dataId:o.dataId,shape:o.shape,dtype:a}}if(a==="int32")return Yme(s,n);if(a==="bool"){let o=n.makeTensorInfo([],"bool",k.getTypedArrayFromDType("bool",1)),l=zE({inputs:{a:s,b:o},backend:n});return n.disposeIntermediateTensorInfo(o),l}throw new Error(`Error in Cast: failed to cast ${s.dtype} to ${a}`)}var Jme={kernelName:el,backendName:"webgl",kernelFunc:db},LE="return ceil(x);",Qme=it({opSnippet:LE,packedOpSnippet:LE,cpuKernelImpl:spe}),e0e={kernelName:No,backendName:"webgl",kernelFunc:Qme},t0e=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
      uniform float minVal;
      uniform float maxVal;

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

        setOutput(clamp(value, minVal, maxVal));
      }
    `}getCustomSetupFunc(e,t){return(n,r)=>{this.minLoc==null&&(this.minLoc=n.getUniformLocationNoThrow(r,"minVal"),this.maxLoc=n.getUniformLocationNoThrow(r,"maxVal")),n.gl.uniform1f(this.minLoc,e),n.gl.uniform1f(this.maxLoc,t)}}},n0e=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
      uniform float minVal;
      uniform float maxVal;

      void main() {
        vec4 value = getAAtOutCoords();

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

        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
      }
    `}getCustomSetupFunc(e,t){return(n,r)=>{this.minLoc==null&&(this.minLoc=n.getUniformLocationNoThrow(r,"minVal"),this.maxLoc=n.getUniformLocationNoThrow(r,"maxVal")),n.gl.uniform1f(this.minLoc,e),n.gl.uniform1f(this.maxLoc,t)}}};function r0e(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{clipValueMin:a,clipValueMax:o}=r,i;ae().getBool("WEBGL_PACK_CLIP")?i=new n0e(s.shape):i=new t0e(s.shape);let l=i.getCustomSetupFunc(a,o);return n.runWebGLProgram(i,[s],s.dtype,l)}var s0e={kernelName:Co,backendName:"webgl",kernelFunc:r0e},a0e=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 BE(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function o0e(e){let{inputs:t,backend:n}=e,{x:r}=t,s=n.texData.get(r.dataId),a=new a0e(r.shape),o=[BE(r,s.complexTensorInfos.real),BE(r,s.complexTensorInfos.imag)];return n.runWebGLProgram(a,o,o[0].dtype)}var i0e={kernelName:Zp,backendName:"webgl",kernelFunc:o0e},l0e=class{constructor(e){this.outputShape=[],this.outputShape=_.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-${o}));`)}let r=t.length,s=t[t.length-1];n.push(`else setOutput(getT${r}(yR, yC-${s}));`),this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int yR = coords.x;
        int yC = coords.y;

        ${n.join(`
        `)}
      }
    `}},u0e=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=_.computeOutShape(e,t);let n=this.outputShape,r=n.length,s=It(r),a=Vn("coords",r),o=["x","y","z","w","u","v"].slice(0,r);this.variableNames=e.map((f,m)=>`T${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(),d=`if (${l} < ${i[0]}) {
        return getChannel(
            getT0(${c}), vec2(${u.join()}));
        }`;for(let f=1;f<i.length;f++){let m=i[f-1];d+=`
        if (${l} < ${i[f]}  && ${l} >= ${i[f-1]}) {
          return getChannel(
            getT${f}(${Zm(o,l,m)}),
            vec2(${Zm(u,l,m)}));
        }`}let h=i.length,p=i[i.length-1];d+=`
        return getChannel(
          getT${h}(${Zm(o,l,p)}),
          vec2(${Zm(u,l,p)}));`,this.userCode=`
      float getValue(${o.map(f=>"int "+f)}) {
        ${d}
      }

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

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

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

        ${a[r-1]} = ${a[r-1]} - 1;
        if (${a[r-2]} < ${n[r-2]} &&
            ${a[r-1]} < ${n[r-1]}) {
          result.b = getValue(${a});
        }
        setOutput(result);
      }
    `}};function Zm(e,t,n){let r=e.indexOf(t);return e.map((a,o)=>o===r?`${a} - ${n}`:a).join()}function Ym(e){let{inputs:t,backend:n}=e,{input:r}=t,s=n.texData.get(r.dataId);return mr({inputs:{x:s.complexTensorInfos.imag},backend:n})}var c0e={kernelName:Ly,backendName:"webgl",kernelFunc:Ym};function Iu(e,t,n){let r=e[0].dtype;if(r==="complex64"){let c=e.map(m=>mh({inputs:{input:m},backend:n})),d=e.map(m=>Ym({inputs:{input:m},backend:n})),h=Iu(c,t,n),p=Iu(d,t,n),f=eo({inputs:{real:h,imag:p},backend:n});return c.forEach(m=>n.disposeIntermediateTensorInfo(m)),d.forEach(m=>n.disposeIntermediateTensorInfo(m)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p),f}let s=n.shouldExecuteOnCPU(e);if(r==="string"&&(s=!0),s){let c=e.map(y=>{let A=k.sizeFromShape(y.shape.slice(t));return ve({inputs:{x:y},backend:n,attrs:{shape:[-1,A]}})}),d=c.map(y=>({vals:n.readSync(y.dataId),shape:y.shape})),h=_.computeOutShape(c.map(y=>y.shape),1),p=c[0].shape[0]===1,f=ape(d,h,r,p),m=_.computeOutShape(e.map(y=>y.shape),t),g=n.makeTensorInfo(m,r,f);return c.forEach(y=>n.disposeIntermediateTensorInfo(y)),g}if(e.length>ae().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let c=Math.floor(e.length/2),d=Iu(e.slice(0,c),t,n),h=Iu(e.slice(c),t,n),p=Iu([d,h],t,n);return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),p}if(ae().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let c=new u0e(e.map(d=>d.shape),t);return n.runWebGLProgram(c,e,r)}let{tensors2D:a,outShape:o}=d0e(e,t,n),i=new l0e(a.map(c=>c.shape)),l=n.runWebGLProgram(i,a,r);a.forEach(c=>n.disposeIntermediateTensorInfo(c));let u=ve({inputs:{x:l},attrs:{shape:o},backend:n});return n.disposeIntermediateTensorInfo(l),u}function d0e(e,t,n){let r=_.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>ve({inputs:{x:a},attrs:{shape:[-1,k.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:r}}function WE(e){let{inputs:t,backend:n,attrs:r}=e,{axis:s}=r,a=k.parseAxisParam(s,t[0].shape)[0],o=_.computeOutShape(t.map(u=>u.shape),a);if(k.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let i=t.filter(u=>k.sizeFromShape(u.shape)>0);if(i.length===1)return mr({inputs:{x:i[0]},backend:n});let l=i.map(u=>u.shape);return _.assertParamsConsistent(l,a),Iu(i,a,n)}var h0e={kernelName:Ec,backendName:"webgl",kernelFunc:WE},VE=class{constructor(e,t=!1,n=null,r=!1,s=!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,d=e.filterHeight,h=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",g=m?1:2,y=m?2:3,A=m?3:1,x="",b="";n&&(r?x=`float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ${n}
        }`:s?x=`float activation(float a) {
          float b = getLeakyreluAlphaAtOutCoords();
          ${n}
        }`:x=`
          float activation(float x) {
            ${n}
          }
        `,b="result = activation(result);");let v=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${x}

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

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

        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 < ${d}; wR++) {
          int xR = xRCorner + wR * ${u};

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

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

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

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

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

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

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

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

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

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

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

            }
          }
        }

        float result = dotProd;
        ${v}
        ${b}
        setOutput(result);
      }
    `}},p0e=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,s=e.strideDepth,a=e.strideHeight,o=e.strideWidth,i=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.filterDepth,d=e.filterHeight,h=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
      const ivec3 strides = ivec3(${s}, ${a}, ${o});
      const ivec3 pads = ivec3(${t}, ${n}, ${r});

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

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

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

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

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

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

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

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

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

                dotProd += dot(xValues, wValues);
              }

              if (${f===1}) {
                dotProd +=
                  getX(batch, xF, xR, xC, ${p}) *
                  getW(wF, wR, wC, ${p}, d2);
              } else if (${f===2}) {
                vec2 xValues = vec2(
                  getX(batch, xF, xR, xC, ${p}),
                  getX(batch, xF, xR, xC, ${p} + 1)
                );
                vec2 wValues = vec2(
                  getW(wF, wR, wC, ${p}, d2),
                  getW(wF, wR, wC, ${p} + 1, d2)
                );
                dotProd += dot(xValues, wValues);
              } else if (${f===3}) {
                vec3 xValues = vec3(
                  getX(batch, xF, xR, xC, ${p}),
                  getX(batch, xF, xR, xC, ${p} + 1),
                  getX(batch, xF, xR, xC, ${p} + 2)
                );
                vec3 wValues = vec3(
                  getW(wF, wR, wC, ${p}, d2),
                  getW(wF, wR, wC, ${p} + 1, d2),
                  getW(wF, wR, wC, ${p} + 2, d2)
                );
                dotProd += dot(xValues, wValues);
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}},f0e=class{constructor(e,t,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:r,inChannels:s,strideWidth:a,strideHeight:o,padInfo:i,outWidth:l,dilationWidth:u,dilationHeight:c,dataFormat:d}=n,{left:h,top:p}=i,f=s*r,m=Wn(),g=d==="channelsLast",y=g?0:1,A=g?1:2,x="";for(let b=0;b<=1;b++)for(let v=0;v<=1;v++)x+=`
          blockIndex = rc.y + ${v};
          pos = rc.x + ${b};

          if(blockIndex < ${e[1]} && pos < ${e[0]}) {
            offsetY = int(blockIndex / (${l})) * ${o} - ${p};
            d0 = offsetY + ${c} * (pos / ${f});

            if(d0 < ${t[y]} && d0 >= 0) {

              offsetX = int(mod(float(blockIndex), ${l}.) * ${a}. - ${h}.);
              d1 = offsetX + ${u} * (int(mod(float(pos), ${f}.) / ${s}.));

              if(d1 < ${t[A]} && d1 >= 0) {

                ch = int(mod(float(pos), ${s}.));

                if (${g}) {
                  innerDims = vec2(d1, ch);
                  result[${b*2+v}] = getChannel(
                    getA(d0, int(innerDims.x),
                    int(innerDims.y)), innerDims);
                } else {
                  innerDims = vec2(d0, d1);
                  result[${b*2+v}] = getChannel(
                    getA(ch, int(innerDims.x),
                    int(innerDims.y)), innerDims);
                }
              }
            }
          }
        `;this.userCode=`
      void main() {
        ivec2 rc = getOutputCoords();

        vec4 result = vec4(0);

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

        ${x}

        ${m.output} = result;
      }
    `}};function UE({x:e,filter:t,convInfo:n,backend:r,bias:s=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let l=e.shape,u=r.texData.get(e.dataId),c=n.inChannels,d=l[0]*l[1]*l[2],h=n.outChannels,p=n.dataFormat==="channelsLast",f=!1,m=!1,g,y=[],A=(d===1||h===1)&&c>RE,x=l[2]%2!=0&&!!u.isPacked;if(A||!ae().getBool("WEBGL_LAZILY_UNPACK")||!ae().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!x){let b=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],v=ve({inputs:{x:e},backend:r,attrs:{shape:[1,b,n.inChannels]}}),w=ve({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),I=Km({a:v,b:w,transposeA:f,transposeB:m,backend:r,bias:s,activation:i,preluActivationWeights:a,leakyreluAlpha:o});g=ve({inputs:{x:I},backend:r,attrs:{shape:n.outShape}}),y.push(v),y.push(w),y.push(I)}else{let b=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),v={dataId:e.dataId,shape:[1,b,n.inChannels],dtype:e.dtype},w=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,k.assert(uh(u.shape,v.shape),()=>`packed reshape ${u.shape} to ${v.shape} isn't free`);let I=ve({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(I);let T=Km({a:v,b:I,backend:r,transposeA:f,transposeB:m,bias:s,activation:i,preluActivationWeights:a,leakyreluAlpha:o}),C=r.texData.get(T.dataId);k.assert(C.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=w,C.shape=n.outShape,g=mr({inputs:{x:T},backend:r}),g.shape=n.outShape,y.push(T)}for(let b of y)r.disposeIntermediateTensorInfo(b);return g}function HE({x:e,filter:t,convInfo:n,backend:r,bias:s=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let{filterWidth:l,filterHeight:u,inChannels:c,outWidth:d,outHeight:h,dataFormat:p}=n,f=p==="channelsLast",m=l*u*c,g=h*d,y=[m,g],A=!0,x=!1,b=[],v=ve({inputs:{x:e},backend:r,attrs:{shape:e.shape.slice(1)}}),w=ve({inputs:{x:t},backend:r,attrs:{shape:[1,m,k.sizeFromShape(t.shape)/m]}});b.push(v),b.push(w);let I=new f0e(y,v.shape,n),T=r.runWebGLProgram(I,[v],"float32"),C=ve({inputs:{x:T},backend:r,attrs:{shape:[1,y[0],y[1]]}});b.push(T),b.push(C);let M=s!=null,$=a!=null,R=i==="leakyrelu",N=i?Gm(i,!0):null,F=new NE(C.shape,w.shape,[1,g,n.outChannels],A,x,M,N,$,R),B=[C,w];if(s&&B.push(s),$&&B.push(a),R){let ee=r.makeTensorInfo([],"float32",k.createScalarValue(o,"float32"));B.push(ee),b.push(ee)}let j=r.runWebGLProgram(F,B,"float32"),X=f?[1,h,d,n.outChannels]:[1,n.outChannels,h,d],Y=ve({inputs:{x:j},backend:r,attrs:{shape:X}});b.push(j);for(let ee of b)r.disposeIntermediateTensorInfo(ee);return Y}function m0e(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=r,d=_.convertConv2DDataFormat(l),h=_.computeConv2DInfo(s.shape,a.shape,o,u,i,c,!1,d),p;if(h.filterHeight===1&&h.filterWidth===1&&h.dilationHeight===1&&h.dilationWidth===1&&h.strideHeight===1&&h.strideWidth===1&&(h.padInfo.type==="SAME"||h.padInfo.type==="VALID"))p=UE({x:s,filter:a,convInfo:h,backend:n});else if(ae().getBool("WEBGL_CONV_IM2COL")&&s.shape[0]===1)p=HE({x:s,filter:a,convInfo:h,backend:n});else{let m=new VE(h);p=n.runWebGLProgram(m,[s,a],"float32")}let f=ve({inputs:{x:p},backend:n,attrs:{shape:h.outShape}});return n.disposeIntermediateTensorInfo(p),f}var g0e={kernelName:tl,backendName:"webgl",kernelFunc:m0e},y0e=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,s=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} - ${r};

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

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

              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);
      }
    `}},A0e=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,s=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) / ${r}.0;

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

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

          for (int wC = 0; wC < ${n}; wC++) {
            float dyC = float(dyCCorner + wC) / ${s}.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);
      }
    `}},x0e=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,s=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} - ${s};

            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 * ${r} - ${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);
      }
    `}},b0e=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,s=e.strideDepth,a=e.strideHeight,o=e.strideWidth,i=t-1-e.padInfo.front,l=n-1-e.padInfo.top,u=r-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) / ${s}.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 < ${r}; 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 = ${r} - 1 - wC;

              for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
                float xValue = getDy(batch, idyF, idyR, idyC, d2);
                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function v0e(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,dy:a}=t,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,filterShape:c}=r,d=_.convertConv2DDataFormat(l),h=_.computeConv2DInfo(s.shape,c,o,1,i,u,!1,d),p=new y0e(h);return n.runWebGLProgram(p,[s,a],"float32")}var w0e={kernelName:Ty,backendName:"webgl",kernelFunc:v0e};function k0e(e){let{inputs:t,backend:n,attrs:r}=e,{dy:s,filter:a}=t,{inputShape:o,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=r,d=_.convertConv2DDataFormat(u),h=_.computeConv2DInfo(o,a.shape,i,1,l,c,!1,d),p=new A0e(h);return n.runWebGLProgram(p,[s,a],"float32")}var I0e={kernelName:nl,backendName:"webgl",kernelFunc:k0e};function S0e(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,filter:a}=t,{strides:o,pad:i,dilations:l}=r,u=_.computeConv3DInfo(s.shape,a.shape,o,l,i),c=new p0e(u);return n.runWebGLProgram(c,[s,a],"float32")}var T0e={kernelName:Yp,backendName:"webgl",kernelFunc:S0e};function N0e(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,dy:a}=t,{strides:o,pad:i,filterShape:l}=r,u=_.computeConv3DInfo(s.shape,l,o,1,i),c=new x0e(u);return n.runWebGLProgram(c,[s,a],"float32")}var C0e={kernelName:Ny,backendName:"webgl",kernelFunc:N0e};function E0e(e){let{inputs:t,backend:n,attrs:r}=e,{dy:s,filter:a}=t,{pad:o,strides:i,inputShape:l}=r,u=_.computeConv3DInfo(l,a.shape,i,1,o),c=new b0e(u);return n.runWebGLProgram(c,[s,a],"float32")}var $0e={kernelName:Cy,backendName:"webgl",kernelFunc:E0e},_0e=TE+`
  return cos(x);
`,R0e=it({opSnippet:_0e}),D0e={kernelName:rl,backendName:"webgl",kernelFunc:R0e},F0e=`
  float e2x = exp(-x);
  return (e2x + 1.0 / e2x) / 2.0;
`,M0e=it({opSnippet:F0e}),O0e={kernelName:$c,backendName:"webgl",kernelFunc:M0e},P0e=class{constructor(e,t,n,r,s){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[a,o,i,l]=e,[u]=t,[c,d]=n;this.outputShape=[u,c,d,l];let h=r==="bilinear"?1:0,[p,f]=[`${o-1}.0`,`${i-1}.0`],[m,g,y]=c>1?[`${(o-1)/(c-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[A,x,b]=d>1?[`${(i-1)/(d-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(${A});
      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 = ${x};

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

        vec2 sourceFracIndexCR = vec2(in_x,in_y);
        if(${h} == 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);
        }
      }
    `}},z0e=e=>{let{inputs:t,backend:n,attrs:r}=e,{image:s,boxes:a,boxInd:o}=t,{cropSize:i,method:l,extrapolationValue:u}=r,c=new P0e(s.shape,a.shape,i,l,u);return n.runWebGLProgram(c,[s,a,o],"float32")},L0e={kernelName:_c,backendName:"webgl",kernelFunc:z0e},GE=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let r=e.length,s=t?"0.0":`getX(${jE(r,"coords")})`,a=e[e.length-1],o="",i="";t?(o=n?`end != ${a-1}`:"end != 0",i=n?"end + 1":"end - 1"):(o=n?`end + pow2 < ${a}`:"end >= pow2",i=n?"end + pow2":"end - pow2"),this.userCode=`
      uniform float index;
      void main() {
        ${It(r)} coords = getOutputCoords();
        int end = ${qE(r,"coords")};
        float val = ${s};
        int pow2 = int(pow(2.0, index));
        if (${o}) {
          int idx = ${i};
          ${qE(r,"coords")} = idx;
          val += getX(${jE(r,"coords")});
        }
        setOutput(val);
      }
    `}getCustomSetupFunc(e){return(t,n)=>{this.index==null&&(this.index=t.getUniformLocation(n,"index")),t.gl.uniform1f(this.index,e)}}};function jE(e,t){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw Error(`Cumulative sum for rank ${e} is not yet supported`)}function qE(e,t){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw Error(`Cumulative sum for rank ${e} is not yet supported`)}function B0e(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{axis:a,exclusive:o,reverse:i}=r,l=s.shape.length,u=_.getAxesPermutation([a],l),c=s;u!=null&&(c=Un({inputs:{x:s},backend:n,attrs:{perm:u}}));let d=_.getInnerMostAxes(1,l)[0];if(d!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${s.shape.length-1} but got axis=${a}`);let h=c.shape[d],p=mr({inputs:{x:c},backend:n});for(let f=0;f<=Math.ceil(Math.log2(h))-1;f++){let m=new GE(c.shape,!1,i),g=m.getCustomSetupFunc(f),y=p;p=n.runWebGLProgram(m,[p],p.dtype,g),n.disposeIntermediateTensorInfo(y)}if(o){let f=new GE(c.shape,o,i),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(u!=null){let f=_.getUndoAxesPermutation(u),m=Un({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(c),m}return p}var W0e={kernelName:sl,backendName:"webgl",kernelFunc:B0e};function V0e(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,weights:a}=t,{size:o,binaryOutput:i}=r;if(s.shape.length===1){let l=n.readSync(s.dataId),u=n.readSync(a.dataId),c=cE(l,u,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,c)}else if(s.shape.length===2){let l=n.bufferSync(s),u=n.bufferSync(a),c=rpe(l,u,o,i);return n.makeTensorInfo(c.shape,a.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${s.shape.length}.`)}var U0e={kernelName:Ey,backendName:"webgl",kernelFunc:V0e},H0e=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 G0e(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{blockSize:a,dataFormat:o}=r;k.assert(a>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${a}`);let i=s.shape[0],l=o==="NHWC"?s.shape[1]:s.shape[2],u=o==="NHWC"?s.shape[2]:s.shape[3],c=o==="NHWC"?s.shape[3]:s.shape[1],d=l*a,h=u*a,p=c/(a*a),f=o==="NHWC"?[i,d,h,p]:[i,p,d,h],m=new H0e(f,a,o);return n.runWebGLProgram(m,[s],s.dtype)}var j0e={kernelName:Rc,backendName:"webgl",kernelFunc:G0e},KE=class{constructor(e,t=!1,n=null,r=!1,s=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let a=e.inHeight,o=e.inWidth,i=e.padInfo.top,l=e.padInfo.left,u=e.strideHeight,c=e.strideWidth,d=e.dilationHeight,h=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=e.outChannels/e.inChannels,g="",y="";n&&(r?g=`float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ${n}
        }`:s?g=`float activation(float a) {
          float b = getLeakyreluAlphaAtOutCoords();
          ${n}
        }`:g=`
          float activation(float x) {
            ${n}
          }
        `,y="result = activation(result);");let A=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${g}

      const ivec2 strides = ivec2(${u}, ${c});
      const ivec2 pads = ivec2(${i}, ${l});

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

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

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

          if (xR < 0 || xR >= ${a}) {
            continue;
          }

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

            if (xC < 0 || xC >= ${o}) {
              continue;
            }

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

        float result = dotProd;
        ${A}
        ${y}
        setOutput(result);
      }
    `}},XE=class{constructor(e,t=!1,n=null,r=!1,s=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let a=e.outChannels/e.inChannels,o=e.inHeight,i=e.inWidth,l=e.padInfo.top,u=e.padInfo.left,c=e.strideHeight,d=e.strideWidth,h=e.dilationHeight,p=e.dilationWidth,f=e.filterHeight,m=e.filterWidth,g=m,y=`
      int xR; int xC; int xCOffset;
      vec4 wTexel; vec4 previous; vec4 final;`;for(let v=0;v<m;v++)y+=`
          vec4 xTexelC${v*2};
          int xTexelC${v*2}Ready;
          vec4 xC${v};`;for(let v=0;v<f;v++){for(let w=0;w<m;w++)y+=`
          xTexelC${w*2} = vec4(0.0);
          xTexelC${w*2}Ready = 0;
          xC${w} = vec4(0.0);`;y+=`
        xR = xRCorner + ${v*h};
        if (xR >=0 && xR < ${o}) {
      `;for(let w=0;w<(g+1)/2;w++){let I=w*2,T=I*p;if(y+=`
          xC = xCCorner + ${T};
          `,d===1){if(I<m&&(u%2==1?(y+=`
                xCOffset = xC + 1;
                if (xCOffset >= 0 && xCOffset < ${i} && xTexelC${T}Ready == 0) {
                  xTexelC${T} = getX(batch, xR, xCOffset, d1);

                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if (xCOffset + 1 >= ${i}) {
                    xTexelC${T}.zw = vec2(0.0);
                  }
                  xTexelC${T}Ready = 1;
                }
              `,p===1&&T>0?y+=`
                xC${I} = vec4(xTexelC${T-2}.zw, xTexelC${T}.xy);
                `:y+=`
                  xCOffset = xC + 1 - 2;

                  if (xCOffset >= 0 && xCOffset < ${i}) {
                    previous = getX(batch, xR, xCOffset, d1);

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

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

                xC${I} = xTexelC${T};
                `,T+1<m)){let C=u%2==0?k.nearestLargerEven(p):p;p%2==0&&u%2==1||p%2!=0&&u%2!=1?(y+=`
                  xCOffset = xC + ${u%2} + ${C};

                  if (xCOffset >= 0 && xCOffset < ${i} && xTexelC${T+2}Ready == 0) {
                    xTexelC${T+2} = getX(batch, xR, xCOffset, d1);

                    // Need to manually clear unused channels in case
                    // we're reading from recycled texture.
                    if (xCOffset + 1 >= ${i}) {
                      xTexelC${T+2}.zw = vec2(0.0);
                    }
                    xTexelC${T+2}Ready = 1;
                  }
                  `,p>1&&(y+=`
                    xCOffset -= 2;
                    if (xCOffset >= 0 && xCOffset < ${i} && xTexelC${T}Ready == 0) {
                      xTexelC${T} = getX(batch, xR, xCOffset, d1);
                      xTexelC${T}Ready = 1;
                    }
                    `),y+=`
                  xC${I+1} = vec4(xTexelC${T}.zw, xTexelC${T+2}.xy);
                  `):C===1?y+=`
                    xC${I+1} = xTexelC${T};
                    `:y+=`
                    xCOffset = xC + ${C};

                    if (xCOffset >= 0 && xCOffset < ${i} && xTexelC${T+2}Ready == 0) {
                      xTexelC${T+2} = getX(batch, xR, xCOffset, d1);
                      if (xCOffset + 1 >= ${i}) {
                        xTexelC${T+2}.zw = vec2(0.0);
                      }
                      xTexelC${T+2}Ready = 1;
                    }

                    xC${I+1} = xTexelC${T+2};
                    `}}else T<m&&(u%2==1?(y+=`
                xCOffset = xC + 1 - ${d};
                if(xCOffset >= 0 && xCOffset < ${i} && xTexelC${T}Ready == 0) {
                  xTexelC${T} = getX(batch, xR, xCOffset, d1);
                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if (xCOffset + 1 >= ${i}) {
                    xTexelC${T}.zw = vec2(0.0);
                  }
                  xTexelC${T}Ready = 1;
                }

                if(xC + 1 >= 0 && xC + 1 < ${i} && xTexelC${T+2}Ready == 0) {
                  xTexelC${T+2} = getX(batch, xR, xC + 1, d1);
                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if (xC + 2 >= ${i}) {
                    xTexelC${T+2}.zw = vec2(0.0);
                  }
                  xTexelC${T+2}Ready = 1;
                }

                xC${I} = vec4(xTexelC${T}.zw, xTexelC${T+2}.zw);
              `,T+1<m&&(y+=`
                  final = vec4(0.0);
                  xCOffset = xC + 1 + ${d};
                  if(xCOffset >= 0 && xCOffset < ${i}) {
                    final = getX(batch, xR, xCOffset, d1);
                  }
                  xC${I+1} = vec4(xTexelC${T+2}.xy, final.xy);
                `)):(y+=`
                if(xC >= 0 && xC < ${i} && xTexelC${T}Ready == 0) {
                  xTexelC${T} = getX(batch, xR, xC, d1);
                  if (xC + 1 >= ${i}) {
                    xTexelC${T}.zw = vec2(0.0);
                  }
                  xTexelC${T}Ready = 1;
                }

                xCOffset = xC + ${d};
                if(xCOffset >= 0 && xCOffset < ${i} && xTexelC${T+2}Ready == 0) {
                  xTexelC${T+2} = getX(batch, xR, xCOffset, d1);
                  if (xCOffset + 1 >= ${i}) {
                    xTexelC${T+2}.zw = vec2(0.);
                  }
                  xTexelC${T+2}Ready = 1;
                }

                xC${I} = vec4(
                  xTexelC${T}.xy, xTexelC${T+2}.xy);
              `,T+1<m&&(y+=`
                  xC${I+1} = vec4(xTexelC${T}.zw, xTexelC${T+2}.zw);
                `)));I<m&&(y+=`
            wTexel = getW(${v}, ${T}, d1, q);
            dotProd += xC${I} * vec4(wTexel.xz, wTexel.xz);
          `,T+1<m&&(y+=`
              wTexel = getW(${v}, ${T+1}, d1, q);
              dotProd += xC${I+1} * vec4(wTexel.xz, wTexel.xz);
            `))}y+=`
        }
      `}let A="",x="";n&&(r?A=`vec4 activation(vec4 a) {
          vec4 b = getPreluActivationWeightsAtOutCoords();
          ${n}
        }`:s?A=`vec4 activation(vec4 a) {
          vec4 b = getLeakyreluAlphaAtOutCoords();
          ${n}
        }`:A=`vec4 activation(vec4 x) {
          ${n}
        }`,x="result = activation(result);");let b=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${A}

      const ivec2 strides = ivec2(${c}, ${d});
      const ivec2 pads = ivec2(${l}, ${u});

      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);

        ${y}

        vec4 result = dotProd - vec4(0.000000000000001);
        ${b}
        ${x}
        setOutput(result);
      }
    `}};function q0e(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,filter:a}=t,{strides:o,pad:i,dilations:l,dimRoundingMode:u}=r,c=l;c==null&&(c=[1,1]),k.assert(_.eitherStridesOrDilationsAreOne(o,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${o} and dilations '${c}'`);let d=_.computeConv2DInfo(s.shape,a.shape,o,c,i,u,!0),h;return ae().getBool("WEBGL_PACK_DEPTHWISECONV")&&d.strideWidth<=2&&d.outChannels/d.inChannels==1?h=new XE(d):h=new KE(d),n.runWebGLProgram(h,[s,a],"float32")}var K0e={kernelName:al,backendName:"webgl",kernelFunc:q0e},X0e=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,s=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} - ${r};

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

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

              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);
      }
    `}},Z0e=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,s=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) / ${r}.0;

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

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

          for (int wC = 0; wC < ${n}; wC++) {
            float dyC = float(dyCCorner + wC) / ${s}.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 * ${i} + dm;
              float xValue = getDy(batch, idyR, idyC, d2);
              float wValue = getW(wRPerm, wCPerm, d1, dm);
              dotProd += xValue * wValue;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function Y0e(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,dy:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,filterShape:c}=r,d=_.computeConv2DInfo(s.shape,c,o,i,l,u,!0),h=new X0e(d);return n.runWebGLProgram(h,[s,a],"float32")}var J0e={kernelName:$y,backendName:"webgl",kernelFunc:Y0e};function Q0e(e){let{inputs:t,backend:n,attrs:r}=e,{dy:s,filter:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=r,d=_.computeConv2DInfo(c,a.shape,o,i,l,u,!0),h=new Z0e(d);return n.runWebGLProgram(h,[s,a],"float32")}var ege={kernelName:_y,backendName:"webgl",kernelFunc:Q0e},tge=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 nge(e){let{inputs:t,backend:n}=e,{x:r}=t,s=[...r.shape,...r.shape],a=k.sizeFromShape(r.shape),o=ve({inputs:{x:r},backend:n,attrs:{shape:[a]}}),i=new tge(a),l=n.runWebGLProgram(i,[o],o.dtype),u=ve({inputs:{x:l},backend:n,attrs:{shape:s}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(l),u}var rge={kernelName:Ry,backendName:"webgl",kernelFunc:nge},sge=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:r,strideHeight:s,strideWidth:a,filterHeight:o,filterWidth:i,dilationHeight:l,dilationWidth:u}=e,{top:c,left:d}=r;this.userCode=`
      const ivec2 strides = ivec2(${s}, ${a});
      const ivec2 pads = ivec2(${c}, ${d});
      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 age(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,filter:a}=t,{strides:o,pad:i,dilations:l}=r,u=_.computeDilation2DInfo(s.shape,a.shape,o,i,"NHWC",l),c,d=new sge(u);c=n.runWebGLProgram(d,[s,a],"float32");let h=ve({inputs:{x:c},backend:n,attrs:{shape:u.outShape}});return n.disposeIntermediateTensorInfo(c),h}var oge={kernelName:Jp,backendName:"webgl",kernelFunc:age};function ige(e){let{inputs:t,backend:n,attrs:r}=e,{equation:s}=r,a=t,{allDims:o,summedDims:i,idDims:l}=_.decodeEinsumEquation(s,a.length);_.checkEinsumDimSizes(o.length,l,a);let{path:u,steps:c}=_.getEinsumComputePath(i,l),d=c.length,h=null,p=o.length,f=[];for(let m=0;m<d;++m){for(let g of c[m]){let{permutationIndices:y,expandDims:A}=_.getEinsumPermutation(p,l[g]),x;_.isIdentityPermutation(y)?x=a[g]:(x=Un({inputs:{x:a[g]},backend:n,attrs:{perm:y}}),f.push(x));let b=x.shape.slice();for(let v=0;v<A.length;++v)b.splice(A[v],0,1);k.arraysEqual(x.shape,b)||(x=ve({inputs:{x},backend:n,attrs:{shape:b}}),f.push(x)),h===null?h=x:(h=lb({inputs:{a:x,b:h},backend:n}),f.push(h))}m<d-1&&(u[m]>=0&&(h=qm({inputs:{x:h},backend:n,attrs:{axis:u[m]-(o.length-p),keepDims:!1}}),f.push(h)),p--)}for(let m of f)m!==h&&n.disposeIntermediateTensorInfo(m);return h}var lge={kernelName:My,backendName:"webgl",kernelFunc:ige},uge="return (x >= 0.0) ? x : (exp(x) - 1.0);",cge=`
  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;
`,dge=it({opSnippet:uge,packedOpSnippet:cge}),hge={kernelName:Dc,backendName:"webgl",kernelFunc:dge},pge="return (b >= 1.0) ? a : a * (b + 1.0);",fge=`
  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,mge=e=>{let{inputs:t,backend:n}=e,{dy:r,y:s}=t,a=ae().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new hh(fge,r.shape,s.shape):new ku(pge,r.shape,s.shape);return n.runWebGLProgram(a,[r,s],r.dtype)},gge={kernelName:Oy,backendName:"webgl",kernelFunc:mge},yge=`
  return vec4(equal(a, b));
`,Age="return float(a == b);",xge=Nn({opSnippet:Age,packedOpSnippet:yge,dtype:"bool",cpuKernelImpl:ope}),bge={kernelName:il,backendName:"webgl",kernelFunc:xge},vge=`
  // Error function is calculated approximately with elementary function.
  // See "Handbook of Mathematical Functions with Formulas,
  // Graphs, and Mathematical Tables", Abramowitz and Stegun.
  float p = ${_.ERF_P};
  float a1 = ${_.ERF_A1};
  float a2 = ${_.ERF_A2};
  float a3 = ${_.ERF_A3};
  float a4 = ${_.ERF_A4};
  float a5 = ${_.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));
`,wge=it({opSnippet:vge}),kge={kernelName:Fc,backendName:"webgl",kernelFunc:wge},ZE="return exp(x);",YE=it({opSnippet:ZE,packedOpSnippet:ZE,cpuKernelImpl:ipe}),Ige={kernelName:Eo,backendName:"webgl",kernelFunc:YE};function hb(e){let{inputs:t,attrs:n,backend:r}=e,{dim:s}=n,{input:a}=t,o=a.shape.length,i=a.shape.slice(),l=s;return s<0&&(k.assert(-(o+1)<=s,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+s+1),i.splice(l,0,1),ve({inputs:{x:a},backend:r,attrs:{shape:i}})}var Sge={kernelName:Mc,backendName:"webgl",kernelFunc:hb},JE="return exp(x) - 1.0;",Tge=it({opSnippet:JE,packedOpSnippet:JE,cpuKernelImpl:lpe}),Nge={kernelName:ll,backendName:"webgl",kernelFunc:Tge},QE=class{constructor(e,t,n){this.variableNames=["real","imag"];let r=t[1];this.outputShape=t;let s=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,a=n?`${r}.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 = ${s};

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

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

        float result = 0.0;

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

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

        return result;
      }

      void main() {
        ivec2 coords = getOutputCoords();
        setOutput(mulMatDFT(coords[0], coords[1]));
      }
    `}};function e9(e,t,n){let r=n.texData.get(e.dataId),s=k.sizeFromShape(e.shape),a=e.shape[e.shape.length-1],o=s/a,i=ve({inputs:{x:e},backend:n,attrs:{shape:[o,a]}}),l=i.shape,u=new QE("real",l,t),c=new QE("imag",l,t),d=[{dataId:r.complexTensorInfos.real.dataId,dtype:r.complexTensorInfos.real.dtype,shape:l},{dataId:r.complexTensorInfos.imag.dataId,dtype:r.complexTensorInfos.imag.dtype,shape:l}],h=n.runWebGLProgram(u,d,"float32"),p=n.runWebGLProgram(c,d,"float32"),f=eo({inputs:{real:h,imag:p},backend:n});n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p);let m=ve({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(f),m}function Cge(e){let{inputs:t,backend:n}=e,{input:r}=t;return e9(r,!1,n)}var Ege={kernelName:Py,backendName:"webgl",kernelFunc:Cge},$ge=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.outputShape=e,this.userCode=`
      uniform float value;
      void main() {
        // Input can be obtained from uniform value.
        setOutput(value);
      }
    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}};function pb(e){let{backend:t,attrs:n}=e,{shape:r,value:s}=n,{dtype:a}=n;if(a=a||k.inferDtype(s),a==="string"){let o=k.getArrayFromDType(a,k.sizeFromShape(r));return o.fill(s),t.makeTensorInfo(r,a,o)}else{let o=new $ge(r,s),i=o.getCustomSetupFunc(s);return t.runWebGLProgram(o,[],a,i)}}var _ge={kernelName:Qp,backendName:"webgl",kernelFunc:pb},Rge=class{constructor(e){this.variableNames=["Image"],this.outputShape=[];let t=e[2];this.outputShape=e,this.userCode=`
        void main() {
          ivec4 coords = getOutputCoords();
          int x = coords[2];

          int coordX = ${t} - x;
          float outputValue;
          if(coordX >= 0 && coordX < ${t}) {
            outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
          } else {
            outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
          }
          setOutput(outputValue);
        }
    `}},Dge={kernelName:Oc,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,r=t,s=new Rge(n.shape);return r.runWebGLProgram(s,[n],n.dtype)}},t9="return floor(x);",Fge=it({opSnippet:t9,packedOpSnippet:t9,cpuKernelImpl:upe}),Mge={kernelName:$o,backendName:"webgl",kernelFunc:Fge},Oge=`
  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;
  }
`,Pge=`
  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);
`,zge=Nn({opSnippet:Oge,packedOpSnippet:Pge,dtype:"int32"}),Lge={kernelName:ul,backendName:"webgl",kernelFunc:zge},Bge=class{constructor(e){this.variableNames=["A"];let t=Wn(),[n,r]=e;this.outputShape=e,this.userCode=`
      void main() {
        ivec3 coords = getOutputCoords();
        int texR = coords[0];
        int texC = coords[1];
        int depth = coords[2];
        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${r}.0, ${n}.0);

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

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

        vec4 result = vec4(0.);

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

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

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

        ${t.output} = result;
      }
    `}},Vge={kernelName:sA,backendName:"webgl",kernelFunc:Uge},Su;function Uge(e){let{inputs:t,backend:n,attrs:r}=e,{pixels:s}=t,{numChannels:a}=r,o=typeof HTMLVideoElement!="undefined"&&s instanceof HTMLVideoElement,i=typeof HTMLImageElement!="undefined"&&s instanceof HTMLImageElement,[l,u]=o?[s.videoWidth,s.videoHeight]:[s.width,s.height],c=[u,l],d=[u,l,a];(i||o)&&(Su==null&&(Su=document.createElement("canvas").getContext("2d")),Su.canvas.width=l,Su.canvas.height=u,Su.drawImage(s,0,0,l,u),s=Su.canvas);let h=n.makeTensorInfo(c,"int32");n.texData.get(h.dataId).usage=zr.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(h.dataId),s);let p=ae().getBool("WEBGL_PACK")?new Wge(d):new Bge(d),f=n.runWebGLProgram(p,[h],"int32");return n.disposeData(h.dataId),f}function Hge(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:d,dimRoundingMode:h,activation:p,leakyreluAlpha:f}=r,m=_.convertConv2DDataFormat(c),g=_.computeConv2DInfo(s.shape,a.shape,l,d,u,h,!1,m),y,A=[];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=UE({x:s,filter:a,convInfo:g,backend:n,bias:o,activation:p,preluActivationWeights:i,leakyreluAlpha:f});else if(ae().getBool("WEBGL_CONV_IM2COL")&&s.shape[0]===1)y=HE({x:s,filter:a,convInfo:g,backend:n,bias:o,activation:p,preluActivationWeights:i,leakyreluAlpha:f});else{let b=o!=null,v=i!=null,w=p==="leakyrelu",I=p?Gm(p,!1):null,T=new VE(g,b,I,v,w),C=[s,a];if(o&&C.push(o),i&&C.push(i),w){let M=n.makeTensorInfo([],"float32",k.createScalarValue(f,"float32"));C.push(M),A.push(M)}y=n.runWebGLProgram(T,C,"float32")}let x=ve({inputs:{x:y},backend:n,attrs:{shape:g.outShape}});return A.push(y),A.forEach(b=>n.disposeIntermediateTensorInfo(b)),x}var Gge={kernelName:Bl,backendName:"webgl",kernelFunc:Hge};function jge(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dimRoundingMode:d,activation:h,leakyreluAlpha:p}=r,f=[],m=c;m==null&&(m=[1,1]),k.assert(_.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let g=_.computeConv2DInfo(s.shape,a.shape,l,m,u,d,!0),y=ae().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels==1,A=h?Gm(h,y):null,x=[s,a],b=o!=null,v=i!=null,w=h==="leakyrelu";if(b&&x.push(o),v&&x.push(i),w){let C=n.makeTensorInfo([],"float32",k.createScalarValue(p,"float32"));x.push(C),f.push(C)}let I;y?I=new XE(g,b,A,v,w):I=new KE(g,b,A,v,w);let T=n.runWebGLProgram(I,x,"float32");return f.forEach(C=>n.disposeIntermediateTensorInfo(C)),T}var qge={kernelName:Wl,backendName:"webgl",kernelFunc:jge},Kge=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let r=It(t.length),s=It(n.length),a=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
        ${r} strides = ${r}(${this.strides});
         void main() {
          ${s} coords = getOutputCoords();
          int flattenIndex = 0;
          for (int j = 0; j < ${this.sliceDim}; j++) {
            int index = round(getIndices(coords[0], j));
            flattenIndex += index * ${a};
          }
          setOutput(getX(flattenIndex, coords[1]));
        }
      `}};function Xge(e){let{inputs:t,backend:n}=e,{params:r,indices:s}=t,a=s.shape,o=a[a.length-1],i=k.sizeFromShape(r.shape),[l,u,c,d]=_.prepareAndValidate(r,s),h=ve({inputs:{x:s},backend:n,attrs:{shape:[u,o]}}),p=ve({inputs:{x:r},backend:n,attrs:{shape:[k.sizeFromShape(r.shape)/c,c]}});if(n.shouldExecuteOnCPU([r,s])||r.dtype==="string"){let y=n.readSync(s.dataId),A=n.bufferSync(r),x=cpe(y,A,r.dtype,u,o,c,d,r.shape,i);return n.makeTensorInfo(l,r.dtype,x.values)}let f=new Kge(o,d,[u,c]),m=n.runWebGLProgram(f,[p,h],p.dtype),g=ve({inputs:{x:m},backend:n,attrs:{shape:l}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(m),g}var Zge={kernelName:zc,backendName:"webgl",kernelFunc:Xge},Yge=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=It(this.rank),r=Jge(e,2);this.userCode=`
      void main() {
        ${n} resRC = getOutputCoords();
        setOutput(getA(${r}));
      }
    `}};function Jge(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[];for(let s=0;s<e.length;s++)s===2?r.push("int(getIndices(resRC.x, resRC.z))"):r.push(`${n[s]}`);return r.join()}function Qge(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,indices:a}=t,{axis:o,batchDims:i}=r,l=k.parseAxisParam(o,s.shape)[0],u=_.segment_util.collectGatherOpShapeInfo(s,a,l,i),c=k.sizeFromShape(a.shape),d=[],h=ve({inputs:{x:s},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),p=ve({inputs:{x:a},backend:n,attrs:{shape:[u.batchSize,c/u.batchSize]}});d.push(h),d.push(p);let f=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([s,a])||s.dtype==="string"){let A=n.bufferSync(p),x=n.bufferSync(h),b=dpe(x,A,f);return d.forEach(v=>n.disposeIntermediateTensorInfo(v)),n.makeTensorInfo(u.outputShape,b.dtype,b.values)}let m=new Yge(h.shape,f),g=n.runWebGLProgram(m,[h,p],h.dtype);d.push(g);let y=ve({inputs:{x:g},backend:n,attrs:{shape:u.outputShape}});return d.forEach(A=>n.disposeIntermediateTensorInfo(A)),y}var e2e={kernelName:Pc,backendName:"webgl",kernelFunc:Qge},t2e="return float(a > b);",n2e=`
  return vec4(greaterThan(a, b));
`,r2e=Nn({opSnippet:t2e,packedOpSnippet:n2e,cpuKernelImpl:hpe,dtype:"bool"}),s2e={kernelName:dl,backendName:"webgl",kernelFunc:r2e},a2e="return float(a >= b);",o2e=`
  return vec4(greaterThanEqual(a, b));
`,i2e=Nn({opSnippet:a2e,packedOpSnippet:o2e,dtype:"bool",cpuKernelImpl:ppe}),l2e={kernelName:_o,backendName:"webgl",kernelFunc:i2e};function u2e(e){let{inputs:t,backend:n}=e,{input:r}=t;return e9(r,!0,n)}var c2e={kernelName:zy,backendName:"webgl",kernelFunc:u2e},d2e="return float(!isnan(x) && !isinf(x));",h2e=it({opSnippet:d2e,dtype:"bool"}),p2e={kernelName:Lc,backendName:"webgl",kernelFunc:h2e},f2e="return float(isinf(x));",m2e=it({opSnippet:f2e,dtype:"bool"}),g2e={kernelName:Bc,backendName:"webgl",kernelFunc:m2e},y2e="return float(isnan(x));",A2e=it({opSnippet:y2e,dtype:"bool"}),x2e={kernelName:Wc,backendName:"webgl",kernelFunc:A2e},b2e="return float(a < b);",v2e=`
  return vec4(lessThan(a, b));
`,w2e=Nn({opSnippet:b2e,packedOpSnippet:v2e,cpuKernelImpl:fpe,dtype:"bool"}),k2e={kernelName:fl,backendName:"webgl",kernelFunc:w2e},I2e="return float(a <= b);",S2e=`
  return vec4(lessThanEqual(a, b));
`,T2e=Nn({opSnippet:I2e,packedOpSnippet:S2e,cpuKernelImpl:mpe,dtype:"bool"}),N2e={kernelName:ml,backendName:"webgl",kernelFunc:T2e};function C2e(e){let{backend:t,attrs:n}=e,{start:r,stop:s,num:a}=n,o=gpe(r,s,a);return t.makeTensorInfo([o.length],"float32",o)}var E2e={kernelName:By,backendName:"webgl",kernelFunc:C2e},$2e=`if (x < 0.0) return NAN;
  return log(x);`,_2e=`
  vec4 result = log(x);
  vec4 isNaN = vec4(lessThan(x, vec4(0.0)));
  result.r = isNaN.r == 1.0 ? NAN : result.r;
  result.g = isNaN.g == 1.0 ? NAN : result.g;
  result.b = isNaN.b == 1.0 ? NAN : result.b;
  result.a = isNaN.a == 1.0 ? NAN : result.a;

  return result;
`,R2e=it({opSnippet:$2e,packedOpSnippet:_2e,cpuKernelImpl:ype}),D2e={kernelName:Ro,backendName:"webgl",kernelFunc:R2e},F2e="return log(1.0 + x);",M2e=it({opSnippet:F2e}),O2e={kernelName:Vc,backendName:"webgl",kernelFunc:M2e},P2e="return float(a >= 1.0 && b >= 1.0);",z2e=`
  return vec4(
    vec4(greaterThanEqual(a, vec4(1.0))) *
    vec4(greaterThanEqual(b, vec4(1.0))));
`,L2e=Nn({opSnippet:P2e,packedOpSnippet:z2e,dtype:"bool"}),B2e={kernelName:Uc,backendName:"webgl",kernelFunc:L2e},W2e="return float(!(x >= 1.0));",V2e=it({opSnippet:W2e}),U2e={kernelName:ef,backendName:"webgl",kernelFunc:V2e},H2e="return float(a >= 1.0 || b >= 1.0);",G2e=`
  return min(
    vec4(greaterThanEqual(a, vec4(1.0))) +
    vec4(greaterThanEqual(b, vec4(1.0))),
    vec4(1.0));
`,j2e=Nn({opSnippet:H2e,packedOpSnippet:G2e,dtype:"bool"}),q2e={kernelName:tf,backendName:"webgl",kernelFunc:j2e},K2e=class{constructor(e,t,n,r,s){this.variableNames=["x"],this.outputShape=[];let a=t,o=e[3]-1;this.outputShape=e;let i,l=`float(${n}) + float(${r}) * sum`;s===.5?i=`inversesqrt(${l})`:s===1?i=`1.0/(${l})`:i=`exp(log(${l}) * float(-${s}));`,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int r = coords[1];
        int c = coords[2];
        int d = coords[3];
        float x = getX(b, r, c, d);
        float sum = 0.0;
        for (int j = -${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 * ${i};
        setOutput(val);
      }
    `}},X2e=class{constructor(e,t,n,r,s){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let a=t,o=e[3]-1;this.outputShape=e;let i,l=`float(${n}) + float(${r}) * sum`;s===.5?i=`inversesqrt(${l})`:s===1?i=`1.0/(${l})`:i=`exp(log(${l}) * float(-${s}));`,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);
      }
    `}},Z2e=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{depthRadius:a,bias:o,alpha:i,beta:l}=r,u=ae().getBool("WEBGL_PACK_NORMALIZATION")?new X2e(s.shape,a,o,i,l):new K2e(s.shape,a,o,i,l);return n.runWebGLProgram(u,[s],s.dtype)},Y2e={kernelName:nf,backendName:"webgl",kernelFunc:Z2e},J2e=class{constructor(e,t,n,r,s){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=r,this.beta=s,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int r = coords[1];
        int c = coords[2];

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

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

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

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

          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
            if (k < depthBegin){
              continue;
            }
            else if (k >= depthBegin && k < depthEnd){
              float dyi = -2.0 * float(${r})
                * float(${s})
                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
                / norm;
              if (k == d) {
                dyi += pow(norm, -1.0 * ${s});
              }
              if (k == coords[3]) {
                dyi *= getDy(b, r, c, d);
                result += dyi;
              }
            }
            else {
              break;
            }
          }
      }
      setOutput(result);
      }
    `}},Q2e=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:s,y:a,dy:o}=t,{depthRadius:i,bias:l,alpha:u,beta:c}=r,d=new J2e(s.shape,i,l,u,c);return n.runWebGLProgram(d,[s,a,o],s.dtype)},eye={kernelName:Wy,backendName:"webgl",kernelFunc:Q2e};function tye(e,t,n,r){let s=k.sizeFromShape(t),o=k.sizeFromShape(e.shape)/s,i=ve({inputs:{x:e},attrs:{shape:[o,s]},backend:r}),l=bi(i,e.dtype,"max",r),u=ve({inputs:{x:l},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(l),u}function n9(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{reductionIndices:a,keepDims:o}=r,i=s.shape.length,l=k.parseAxisParam(a,s.shape),u=l,c=_.getAxesPermutation(u,i),d=c!=null,h=n.shouldExecuteOnCPU([s]),p=s;if(d){if(h){let x=n.texData.get(p.dataId).values,b=new Array(i);for(let I=0;I<b.length;I++)b[I]=s.shape[c[I]];let v=ib(x,s.shape,s.dtype,c,b);p=n.makeTensorInfo(b,s.dtype);let w=n.texData.get(p.dataId);w.values=v}else p=jm(s,c,n);u=_.getInnerMostAxes(u.length,i)}_.assertAxesAreInnerMostDims("max",u,i);let[f,m]=_.computeOutAndReduceShapes(p.shape,u),g=f;o&&(g=_.expandShapeToKeepDim(f,l));let y;if(h){let x=n.texData.get(p.dataId).values,b=Ape(x,k.sizeFromShape(m),g,s.dtype);y=n.makeTensorInfo(g,s.dtype);let v=n.texData.get(y.dataId);v.values=b}else y=tye(p,m,g,n);return d&&n.disposeIntermediateTensorInfo(p),y}var nye={kernelName:gl,backendName:"webgl",kernelFunc:n9},rye=vE+`
  return max(a, b);
`,sye=`
  vec4 result = vec4(max(a, b));
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  `+Hm+`
  return result;
`,aye=Nn({opSnippet:rye,packedOpSnippet:sye,cpuKernelImpl:xpe}),oye={kernelName:Do,backendName:"webgl",kernelFunc:aye};function iye(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t;mu(s,"maxPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=r,u=1;k.assert(_.eitherStridesOrDilationsAreOne(o,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=_.computePool2DInfo(s.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&k.arraysEqual(c.inShape,c.outShape))return mr({inputs:{x:s},backend:n});let d=new ph(c,"max",!1);return n.runWebGLProgram(d,[s],s.dtype)}var lye={kernelName:yl,backendName:"webgl",kernelFunc:iye};function uye(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{filterSize:a,strides:o,pad:i,dataFormat:l,dimRoundingMode:u}=r,c=[1,1,1],d=_.computePool3DInfo(s.shape,a,o,c,i,u,l),h=new ub(d,"max",!1);return n.runWebGLProgram(h,[s],s.dtype)}var cye={kernelName:rf,backendName:"webgl",kernelFunc:uye},dye=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,r=e.dilationHeight,s=e.effectiveFilterHeight,a=e.effectiveFilterWidth,o=s-1-e.padInfo.top,i=a-1-e.padInfo.left,l=s*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 < ${s};
          wR += ${r}) {
          float dyR = float(dyRCorner + wR) / ${t}.0;

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

          for (int wC = 0; wC < ${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);
      }
    `}},hye=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,s=e.dilationDepth,a=e.dilationHeight,o=e.dilationWidth,i=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=i-1-e.padInfo.front,d=l-1-e.padInfo.top,h=u-1-e.padInfo.left,p=i*l*u-1;this.userCode=`
      const ivec3 pads = ivec3(${c}, ${d}, ${h});

      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 += ${s}) {
          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) / ${r}.0;

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

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

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

              dotProd += dyValue * mask;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function pye(e){let{inputs:t,backend:n,attrs:r}=e,{dy:s,input:a}=t,o=a,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=r,d=[1,1,1],h=_.computePool3DInfo(o.shape,i,l,d,u,c),p=new ub(h,"max",!0),f=n.runWebGLProgram(p,[o],o.dtype),m=new hye(h),g=n.runWebGLProgram(m,[s,f],o.dtype);return n.disposeIntermediateTensorInfo(f),g}var fye={kernelName:Uy,backendName:"webgl",kernelFunc:pye};function mye(e){let{inputs:t,backend:n,attrs:r}=e,{dy:s,input:a,output:o}=t,i=a;mu([a,o],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:d}=r,h=_.computePool2DInfo(i.shape,l,u,1,c,d),p=!0,f=new ph(h,"max",p),m=n.runWebGLProgram(f,[i],i.dtype),g=new dye(h),y=n.runWebGLProgram(g,[s,m],i.dtype);return n.disposeIntermediateTensorInfo(m),y}var gye={kernelName:Vy,backendName:"webgl",kernelFunc:mye};function yye(e,t,n,r){let s=new ph(n,"max",!1),a=r.runWebGLProgram(s,[e],"float32");s=new ph(n,"max",!0,!0,t);let o=r.runWebGLProgram(s,[e],"float32");return[a,o]}var Aye={kernelName:Hy,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:s,strides:a,pad:o,includeBatchInIndex:i}=t,l=n;k.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let u=[1,1];k.assert(_.eitherStridesOrDilationsAreOne(a,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${u}'`);let c=_.computePool2DInfo(r.shape,s,a,u,o),[d,h]=yye(r,i,c,l);return[d,h]}};function xye(e,t,n,r){let s=k.sizeFromShape(t),o=k.sizeFromShape(e.shape)/s,i=ve({inputs:{x:e},attrs:{shape:[o,s]},backend:r}),l=bi(i,"float32","mean",r),u=ve({inputs:{x:l},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(l),u}var bye={kernelName:Al,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{keepDims:s,axis:a}=t,o=n,i=r.shape.length,l=k.parseAxisParam(a,r.shape),u=l,c=_.getAxesPermutation(u,i),d=c!=null,h=o.shouldExecuteOnCPU([r]),p=[],f=r;if(d){if(h){let b=o.texData.get(f.dataId).values,v=new Array(i);for(let T=0;T<v.length;T++)v[T]=r.shape[c[T]];let w=ib(b,r.shape,r.dtype,c,v);f=o.makeTensorInfo(v,r.dtype);let I=o.texData.get(f.dataId);I.values=w}else f=jm(r,c,o);p.push(f),u=_.getInnerMostAxes(u.length,i)}_.assertAxesAreInnerMostDims("sum",u,i);let[m,g]=_.computeOutAndReduceShapes(f.shape,u),y=m;s&&(y=_.expandShapeToKeepDim(m,l));let A=xye(f,g,y,o);for(let x of p)o.disposeIntermediateTensorInfo(x);return A}};function vye(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{axis:a,keepDims:o}=r,i=s.shape.length,l=k.parseAxisParam(a,s.shape),u=l,c=_.getAxesPermutation(u,i),d=s;c!=null&&(d=Un({inputs:{x:s},backend:n,attrs:{perm:c}}),u=_.getInnerMostAxes(u.length,s.shape.length)),_.assertAxesAreInnerMostDims("min",u,i);let[h,p]=_.computeOutAndReduceShapes(d.shape,u),f=k.sizeFromShape(p),m=ve({inputs:{x:d},backend:n,attrs:{shape:[-1,f]}}),g=bi(m,m.dtype,"min",n),y;if(o){let A=_.expandShapeToKeepDim(h,l);y=ve({inputs:{x:g},backend:n,attrs:{shape:A}})}else y=ve({inputs:{x:g},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(d),y}var wye={kernelName:xl,backendName:"webgl",kernelFunc:vye},kye=vE+`
  return min(a, b);
`,Iye=`
  vec4 result = vec4(min(a, b));
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  `+Hm+`
  return result;
`,Sye=Nn({opSnippet:kye,packedOpSnippet:Iye,cpuKernelImpl:bpe}),Tye={kernelName:Fo,backendName:"webgl",kernelFunc:Sye},Nye=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let r=e.length,s=It(r),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,r),l=n==="reflect"?0:1;if(r===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=`
      ${s} start = ${s}(${a});
      ${s} end = ${s}(${o});

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

      void main() {
        ${s} outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ${h}
        setOutput(result);
      }
    `}},Eye=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{paddings:s,mode:a}=n,o=ae().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Cye(r.shape,s,a):new Nye(r.shape,s,a);return t.runWebGLProgram(o,[r],r.dtype)},$ye={kernelName:bl,backendName:"webgl",kernelFunc:Eye},_ye=`if (b == 0.0) return NAN;
  return mod(a, b);`,Rye=`
  vec4 result = mod(a, b);
  vec4 isNaN = vec4(equal(b, vec4(0.0)));
  `+Hm+`
  return result;
`,Dye=Nn({opSnippet:_ye,packedOpSnippet:Rye}),Fye={kernelName:Hc,backendName:"webgl",kernelFunc:Dye},Mye=class{constructor(e,t,n){this.variableNames=["probs"],this.outputShape=[e,n],this.userCode=`
      uniform float seed;

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

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

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

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

        // If no other event happened, last event happened.
        setOutput(float(${t-1}));
      }
    `}getCustomSetupFunc(e){return(t,n)=>{this.seedLoc==null&&(this.seedLoc=t.getUniformLocation(n,"seed")),t.gl.uniform1f(this.seedLoc,e)}}},Oye=`
if (a == b) {
  return 1.0;
};
return a / b;`,Pye=`
  // vec4 one = vec4(equal(a, b));
  // return one + (vec4(1.0) - one) * a / b;
  vec4 result = a / b;
  if(a.x == b.x) {
    result.x = 1.;
  }
  if(a.y == b.y) {
    result.y = 1.;
  }
  if(a.z == b.z) {
    result.z = 1.;
  }
  if(a.w == b.w) {
    result.w = 1.;
  }

  return result;
`,r9=Nn({opSnippet:Oye,packedOpSnippet:Pye,checkOutOfBounds:!0}),zye={kernelName:ol,backendName:"webgl",kernelFunc:r9},s9="return a - b;",a9=Nn({opSnippet:s9,packedOpSnippet:s9,supportsComplex:!0,cpuKernelImpl:Fpe}),Lye={kernelName:zo,backendName:"webgl",kernelFunc:a9};function o9(e){let{inputs:t,backend:n,attrs:r}=e,{logits:s}=t,{dim:a}=r,o=k.parseAxisParam([a],s.shape),i=n9({inputs:{x:s},backend:n,attrs:{reductionIndices:o,keepDims:!1}}),l=_.expandShapeToKeepDim(i.shape,o),u=ve({inputs:{x:i},backend:n,attrs:{shape:l}}),c=a9({inputs:{a:s,b:u},backend:n}),d=YE({inputs:{x:c},backend:n}),h=qm({inputs:{x:d},backend:n,attrs:{axis:o,keepDims:!1}}),p=ve({inputs:{x:h},backend:n,attrs:{shape:l}}),f=r9({inputs:{a:d,b:p},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p),f}var Bye={kernelName:Ml,backendName:"webgl",kernelFunc:o9};function Wye(e){let{inputs:t,backend:n,attrs:r}=e,{logits:s}=t,{numSamples:a,seed:o,normalized:i}=r,l=i?s:o9({inputs:{logits:s},backend:n,attrs:{dim:s.shape.length-1}}),u=l.shape[0],c=l.shape[1],d=new Mye(u,c,a),h=d.getCustomSetupFunc(o),p=n.runWebGLProgram(d,[l],"int32",h);return i||n.disposeIntermediateTensorInfo(l),p}var Vye={kernelName:Gy,backendName:"webgl",kernelFunc:Wye},i9="return -x;";function Uye(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){let a=n.texData.get(r.dataId),[o,i]=wpe(a.values,r.shape,r.dtype);return n.makeTensorInfo(i,r.dtype,o)}let s;return ae().getBool("WEBGL_PACK_UNARY_OPERATIONS")?s=new wu(r.shape,i9):s=new Qa(r.shape,i9),n.runWebGLProgram(s,[r],r.dtype)}var Hye={kernelName:Gc,backendName:"webgl",kernelFunc:Uye},Gye=ca.nonMaxSuppressionV3Impl;function jye(e){_.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:s,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l}=r,u=n.readSync(s.dataId),c=n.readSync(a.dataId),{selectedIndices:d}=Gye(u,c,o,i,l);return n.makeTensorInfo([d.length],"int32",new Int32Array(d))}var qye={kernelName:jc,backendName:"webgl",kernelFunc:jye},Kye=ca.nonMaxSuppressionV4Impl;function Xye(e){_.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:s,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,padToMaxOutputSize:u}=r,c=n.readSync(s.dataId),d=n.readSync(a.dataId),{selectedIndices:h,validOutputs:p}=Kye(c,d,o,i,l,u);return[n.makeTensorInfo([h.length],"int32",new Int32Array(h)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var Zye={kernelName:qc,backendName:"webgl",kernelFunc:Xye},Yye=ca.nonMaxSuppressionV5Impl;function Jye(e){_.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:s,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=r,c=n.readSync(s.dataId),d=n.readSync(a.dataId),h=o,p=i,f=l,m=u,{selectedIndices:g,selectedScores:y}=Yye(c,d,h,p,f,m);return[n.makeTensorInfo([g.length],"int32",new Int32Array(g)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var Qye={kernelName:Kc,backendName:"webgl",kernelFunc:Jye},eAe=class{constructor(e,t,n,r){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int index = round(getIndices(coords.x));
        setOutput(mix(float(${r}), float(${n}),
                      float(index == coords.y)));
      }
    `}},tAe=e=>{let{inputs:t,backend:n,attrs:r}=e,{indices:s}=t,{depth:a,onValue:o,offValue:i}=r,l=k.sizeFromShape(s.shape),u=new eAe(l,a,o,i),c=ve({inputs:{x:s},backend:n,attrs:{shape:[l]}}),d=n.runWebGLProgram(u,[c],s.dtype);n.disposeIntermediateTensorInfo(c);let h=[...s.shape,a],p=ve({inputs:{x:d},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(d),p},nAe={kernelName:wl,backendName:"webgl",kernelFunc:tAe};function Jm(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="complex64"){let s=mh({inputs:{input:r},backend:n}),a=Jm({inputs:{x:s},backend:n}),o=Ym({inputs:{input:r},backend:n}),i=Jm({inputs:{x:o},backend:n}),l=eo({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return pb({attrs:{shape:r.shape,dtype:r.dtype,value:r.dtype==="string"?"":0},backend:n})}var rAe={kernelName:hd,backendName:"webgl",kernelFunc:Jm};function l9(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(r.dtype==="complex64"){let s=mh({inputs:{input:r},backend:n}),a=l9({inputs:{x:s},backend:n}),o=Ym({inputs:{input:r},backend:n}),i=Jm({inputs:{x:o},backend:n}),l=eo({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return pb({attrs:{shape:r.shape,dtype:r.dtype,value:1},backend:n})}var sAe={kernelName:Xc,backendName:"webgl",kernelFunc:l9};function aAe(e){let{inputs:t,backend:n,attrs:r}=e,{axis:s}=r;if(t.length===1)return hb({inputs:{input:t[0]},backend:n,attrs:{dim:s}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{k.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),k.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let d=hb({inputs:{input:c},backend:n,attrs:{dim:s}});return i.push(d),d}),u=WE({inputs:l,backend:n,attrs:{axis:s}});return i.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var oAe={kernelName:Zc,backendName:"webgl",kernelFunc:aAe},iAe=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let r=e.length,s=It(r),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,r);if(r===1){this.userCode=`
        int start = ${a};
        int end = ${o};
        uniform float value;

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

      void main() {
        ${s} outC = getOutputCoords();
        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
          setOutput(value);
        } else {
          ${s} coords = outC - start;
          setOutput(getX(${i}));
        }
      }
    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},lAe=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let r=e.length,s=It(r),a=t.map(f=>f[0]).join(","),o=t.map((f,m)=>f[0]+e[m]).join(","),i=Vn("rc",r),l=Vn("source",r),u=`${i[r-1]} < ${this.outputShape[r-1]}`,c=r===1?"source":`vec2(${l.slice(-2).join()})`,d=[`${s} rc = outputLoc;`,`${i[r-1]} += 1;
       if(${u}) {
      `,r===1?"":`}
       rc = outputLoc;
       ${i[r-2]} += 1;
       if(${i[r-2]} < ${this.outputShape[r-2]}) {`,r===1?"":`  ${i[r-1]} += 1;
         if(${u}) {`],h=r===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",p="";for(let f=0,m=r===1?2:4;f<m;f++)p+=`
        ${d[f]}
        if (${h}) {
          result[${f}] = float(value);
        } else {
          ${s} source = rc - start;
          result[${f}] = getChannel(getX(${l.join()}), ${c});
        }
      `;p+=r===1?"} ":"}}",this.userCode=`
      const ${s} start = ${s}(${a});
      const ${s} end = ${s}(${o});
      uniform float value;

      void main() {
        ${s} outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ${p}
        setOutput(result);
      }
    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},u9=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{paddings:a,constantValue:o}=r,i=ae().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new lAe(s.shape,a,o):new iAe(s.shape,a,o),l=i.getCustomSetupFunc(o);return n.runWebGLProgram(i,[s],s.dtype,l)},uAe={kernelName:kl,backendName:"webgl",kernelFunc:u9},cAe=`
  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);
`,dAe=`
  // 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));
  `+Hm+`
  return result;
`,hAe=Nn({opSnippet:cAe,packedOpSnippet:dAe}),pAe={kernelName:Il,backendName:"webgl",kernelFunc:hAe};function fAe(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{axis:a,keepDims:o}=r,i=s.shape.length,l=[],u=k.parseAxisParam(a,s.shape),c=u,d=_.getAxesPermutation(c,i),h=s;d!=null&&(h=Un({inputs:{x:s},backend:n,attrs:{perm:d}}),c=_.getInnerMostAxes(c.length,i),l.push(h)),_.assertAxesAreInnerMostDims("prod",c,i);let p;if(n.shouldExecuteOnCPU([h])){let f=n.texData.get(h.dataId).values,{outVals:m,outShape:g,outDtype:y}=Ipe(h.shape,h.dtype,f,c);p=n.makeTensorInfo(g,y,m)}else{let[f,m]=_.computeOutAndReduceShapes(h.shape,c),g=k.sizeFromShape(m),y=ve({inputs:{x:h},backend:n,attrs:{shape:[-1,g]}}),A=fA(s.dtype),x=bi(y,A,"prod",n);p=ve({inputs:{x},backend:n,attrs:{shape:f}}),l.push(y),l.push(x)}if(o){l.push(p);let f=_.expandShapeToKeepDim(p.shape,u);p=ve({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var mAe={kernelName:Yc,backendName:"webgl",kernelFunc:fAe},c9=e=>{let{backend:t,attrs:n}=e,{start:r,stop:s,step:a,dtype:o}=n,i=Spe(r,s,a,o);return t.makeTensorInfo([i.length],o,i)},gAe={kernelName:sf,backendName:"webgl",kernelFunc:c9},yAe="return 1.0 / x;",AAe=it({opSnippet:yAe}),xAe={kernelName:Jc,backendName:"webgl",kernelFunc:AAe},bAe=ys+`
  return (x < 0.0) ? 0.0 : x;
`,vAe=`
  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;
`,wAe=it({opSnippet:bAe,packedOpSnippet:vAe}),kAe={kernelName:Tl,backendName:"webgl",kernelFunc:wAe},IAe=ys+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,SAe=`
  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;
`,TAe=it({opSnippet:IAe,packedOpSnippet:SAe}),NAe={kernelName:Cl,backendName:"webgl",kernelFunc:TAe},CAe=class{constructor(e,t,n,r,s){this.variableNames=["A"],this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[r&&t>1?o-1:o,r&&n>1?i-1:i],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],d;s?d="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":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 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);
      }
    `}},EAe=class{constructor(e,t,n,r,s){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=[r&&t>1?o-1:o,r&&n>1?i-1:i],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],d;s?d="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":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 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 $Ae(e){let{inputs:t,backend:n,attrs:r}=e,{images:s}=t,{alignCorners:a,halfPixelCenters:o,size:i}=r,[l,u]=i,c=ae().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new EAe(s.shape,l,u,a,o):new CAe(s.shape,l,u,a,o);return n.runWebGLProgram(c,[s],"float32")}var _Ae={kernelName:Nl,backendName:"webgl",kernelFunc:$Ae},RAe=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,s]=t,[,a,o]=e,i=[n&&a>1?r-1:r,n&&o>1?s-1:s],l=[n&&a>1?a-1:a,n&&o>1?o-1:o],u=i[0]/l[0],c=i[1]/l[1],d=1/u,h=1/c,p=Math.ceil(d)*2+2,f=Math.ceil(h)*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(${d});
        const float invWidthScale = float(${h});

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

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

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

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

          // Guard against the window exceeding the bounds of dy
          if (dyR < 0 || dyR >= ${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), ${r-1}.0));
            float dxRLerp = dxR - float(topDxRIndex);
            float inverseDxRLerp = 1.0 - dxRLerp;

            float dxC = float(dyC) * widthScale;
            int leftDxCIndex = int(floor(dxC));
            int rightDxCIndex = int(min(ceil(dxC), ${s-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 DAe(e){let{inputs:t,backend:n,attrs:r}=e,{images:s,dy:a}=t,{alignCorners:o}=r,i=new RAe(a.shape,s.shape,o);return n.runWebGLProgram(i,[a],a.dtype)}var FAe={kernelName:Ky,backendName:"webgl",kernelFunc:DAe},MAe=class{constructor(e,t,n,r,s){this.variableNames=["A"],this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[r&&t>1?o-1:o,r&&n>1?i-1:i],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],d=r?"0.5":"0.0",h;s?h="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":h="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 = ${h};

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

        setOutput(newValue);
      }
    `}},OAe=class{constructor(e,t,n,r,s){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=[r&&t>1?o-1:o,r&&n>1?i-1:i],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],d=r?"0.5":"0.0",h;s?h="max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec3 effectiveInputOverOutputRatioRC = vec3(
          ${u[0]/c[0]},
          ${u[1]/c[1]},
          ${u[1]/c[1]});
      const vec3 inputShapeRC = vec3(${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 = ${h};

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

        // 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 PAe(e){let{inputs:t,backend:n,attrs:r}=e,{images:s}=t,{alignCorners:a,halfPixelCenters:o,size:i}=r,[l,u]=i,c=ae().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new OAe(s.shape,l,u,a,o):new MAe(s.shape,l,u,a,o);return n.runWebGLProgram(c,[s],s.dtype)}var zAe={kernelName:af,backendName:"webgl",kernelFunc:PAe},LAe=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,s]=t,[,a,o]=e,i=[n&&a>1?r-1:r,n&&o>1?s-1:s],l=[n&&a>1?a-1:a,n&&o>1?o-1:o],u=i[0]/l[0],c=i[1]/l[1],d=1/u,h=1/c,p=Math.ceil(d)*2+2,f=Math.ceil(h)*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(${d});
        const float invWidthScale = float(${h});

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

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

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

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

          // Guard against the window exceeding the bounds of dy
          if (dyR < 0 || dyR >= ${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(${r}) - 1),
                ${n} ? float(round(sourceFracRow)) :
                                  float(floor(sourceFracRow))));

            int sourceNearestCol = int(min(
                float(int(${s}) - 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 BAe(e){let{inputs:t,backend:n,attrs:r}=e,{images:s,dy:a}=t,{alignCorners:o}=r,i=new LAe(a.shape,s.shape,o);return n.runWebGLProgram(i,[a],a.dtype)}var WAe={kernelName:qy,backendName:"webgl",kernelFunc:BAe},VAe=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
        void main() {
          int coord = getOutputCoords();
          setOutput(getX(${e[0]} - coord - 1));
        }
      `;return}let r=o=>t.indexOf(o)!==-1&&e[o]!==1?`${e[o]} - coords[${o}] - 1`:`coords[${o}]`,s=e.map((o,i)=>r(i)).join(","),a=It(n);this.userCode=`
      void main() {
        ${a} coords = getOutputCoords();
        setOutput(getX(${s}));
      }
    `}},UAe=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=e;let r=Vn("rc",n),s=`${r[n-1]} + 1 < ${this.outputShape[n-1]}`,a=`${r[n-2]} + 1 < ${this.outputShape[n-2]}`,o=It(n);n===1?this.userCode=`
        void main(){
          int rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = getChannel(getX(${e[0]} - rc - 1),
            ${e[0]} - rc - 1);
          if(${s}){
              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 = ${i(r.slice())};
          if(${s}){
            result.g = ${l(r.slice())};
          }
          if(${a}) {
            result.b = ${u(r.slice())};
            if(${s}) {
              result.a = ${c(r.slice())};
            }
          }
          setOutput(result);
        }
    `;function i(p){return d(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",d(p)}function u(p){return p[n-2]="("+p[n-2]+" + 1)",d(p)}function c(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",d(p)}function d(p){let f=e.map((y,A)=>h(A,p)),m=f.join(","),g=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${g}))`}function h(p,f){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${f[p]} - 1`:`${f[p]}`}}};function HAe(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{dims:a}=r,o=s.shape.length,i=k.parseAxisParam(a,s.shape);if(o===0)return mr({inputs:{x:s},backend:n});let l=ae().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new UAe(s.shape,i):new VAe(s.shape,i);return n.runWebGLProgram(l,[s],s.dtype)}var GAe={kernelName:El,backendName:"webgl",kernelFunc:HAe},jAe=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[];let n=e[1],r=e[2];this.outputShape=e;let s="";typeof t=="number"?s=`float outputValue = ${t.toFixed(2)};`:s=`
        vec3 fill = vec3(${t.join(",")});
        float outputValue = fill[coords[3]];`,this.userCode=`
        uniform vec4 params;
        void main() {
          ivec4 coords = getOutputCoords();
          int x = coords[2];
          int y = coords[1];
          float coordXFloat = (float(x) - params[0]) * params[3] -
            (float(y) - params[1]) * params[2];
          float coordYFloat = (float(x) - params[0]) * params[2] +
            (float(y) - params[1]) * params[3];
          int coordX = int(round(coordXFloat + params[0]));
          int coordY = int(round(coordYFloat + params[1]));
          ${s}
          if(coordX >= 0 && coordX < ${r} && coordY >= 0 && coordY < ${n}) {
            outputValue = getImage(coords[0], coordY, coordX, coords[3]);
          }
          setOutput(outputValue);
        }
    `}getCustomSetupFunc(e,t,n,r){return(s,a)=>{this.paramsLoc==null&&(this.paramsLoc=s.getUniformLocationNoThrow(a,"params")),s.gl.uniform4f(this.paramsLoc,e,t,n,r)}}},qAe={kernelName:pd,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,{radians:s,fillValue:a,center:o}=t,i=n,l=new jAe(r.shape,a),[u,c]=_.getImageCenter(o,r.shape[1],r.shape[2]),d=l.getCustomSetupFunc(u,c,Math.sin(s),Math.cos(s));return i.runWebGLProgram(l,[r],r.dtype,d)}},KAe=`
  // OpenGL ES does not support round function.
  // The algorithm is based on banker's rounding.
  float base = floor(x);
  if ((x - base) < 0.5) {
    return floor(x);
  } else if ((x - base) > 0.5) {
    return ceil(x);
  } else {
    if (mod(base, 2.0) == 0.0) {
      return base;
    } else {
      return base + 1.0;
    }
  }
`,XAe=it({opSnippet:KAe}),ZAe={kernelName:$l,backendName:"webgl",kernelFunc:XAe},YAe="return inversesqrt(x);",JAe=it({opSnippet:YAe,cpuKernelImpl:Tpe}),QAe={kernelName:Oo,backendName:"webgl",kernelFunc:JAe},d9=class{constructor(e,t,n,r,s,a,o=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=a;let i=It(s.length),l=It(a.length),u="";n===1?u="i":n===2&&(u="i, j");let c=`getIndices(${u})`,d="";r===1?d="i":r===2&&(d="i, coords[1]");let h=`getUpdates(${d})`,p=t>1?"strides[j]":"strides";this.userCode=`
        ${i} strides = ${i}(${s});

        void main() {
          ${l} coords = getOutputCoords();
          float sum = 0.0;
          bool found = false;
          for (int i = 0; i < ${e}; i++) {
            int flattenedIndex = 0;
            for (int j = 0; j < ${t}; j++) {
              int index = round(${c});
              flattenedIndex += index * ${p};
            }
            if (flattenedIndex == coords[0]) {
              sum += ${h};
              found = true;
            }
          }
          setOutput(mix(getDefaultValue(), sum, float(found)));
        }
      `}};function e1e(e){let{inputs:t,backend:n,attrs:r}=e,{indices:s,updates:a}=t,{shape:o}=r,{sliceRank:i,numUpdates:l,sliceSize:u,strides:c,outputSize:d}=_.calculateShapes(a,s,o),h=[d/u,u];if(d===0)return n.makeTensorInfo(o,s.dtype);let p=ve({inputs:{x:s},backend:n,attrs:{shape:[l,i]}}),f=ve({inputs:{x:a},backend:n,attrs:{shape:[l,u]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),g=new d9(l,i,p.shape.length,f.shape.length,c,h),y=n.runWebGLProgram(g,[f,p,m],f.dtype),A=ve({inputs:{x:y},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),A}var t1e={kernelName:ed,backendName:"webgl",kernelFunc:e1e},n1e=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let r,s;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)s="resRC",r="resRC";else{let o=["resRC.x","resRC.y","resRC.z","resRC.w"],i=[],l=[];for(let u=0;u<t.length;u++)l.push(`${o[u]}`),u<e&&i.push(`${o[u]}`);r=i.join(),s=l.join()}let a=It(n);this.userCode=`
      void main() {
        ${a} resRC = getOutputCoords();
        float cVal = getC(${r});
        if (cVal >= 1.0) {
          setOutput(getA(${s}));
        } else {
          setOutput(getB(${s}));
        }
      }
    `}};function r1e(e){let{inputs:t,backend:n}=e,{condition:r,t:s,e:a}=t,o=new n1e(r.shape.length,s.shape,s.shape.length);return n.runWebGLProgram(o,[r,s,a],qr(s.dtype,a.dtype))}var s1e={kernelName:td,backendName:"webgl",kernelFunc:r1e},a1e=`
  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
  // see: https://arxiv.org/abs/1706.02515
  float scaleAlpha = ${_.SELU_SCALEALPHA};
  float scale = ${_.SELU_SCALE};
  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,o1e=it({opSnippet:a1e}),i1e={kernelName:nd,backendName:"webgl",kernelFunc:o1e},l1e="return 1.0 / (1.0 + exp(-1.0 * x));",u1e=it({opSnippet:l1e}),c1e={kernelName:Rl,backendName:"webgl",kernelFunc:u1e},d1e=`
  if (isnan(x)) { return 0.0; }
  return sign(x);
`,h1e=it({opSnippet:d1e}),p1e={kernelName:ad,backendName:"webgl",kernelFunc:h1e},f1e=TE+`
  return sin(x);
`,m1e=it({opSnippet:f1e}),g1e={kernelName:_l,backendName:"webgl",kernelFunc:m1e},y1e=`
  float e2x = exp(x);
  return (e2x - 1.0 / e2x) / 2.0;
`,A1e=it({opSnippet:y1e}),x1e={kernelName:sd,backendName:"webgl",kernelFunc:A1e},b1e=`
  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;
`,v1e=it({opSnippet:b1e}),w1e={kernelName:od,backendName:"webgl",kernelFunc:v1e},k1e=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{blockShape:a,paddings:o}=r;k.assert(s.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let i=a.reduce((y,A)=>y*A),l=[[0,0]];l.push(...o);for(let y=1+a.length;y<s.shape.length;++y)l.push([0,0]);let u=[],c=u9({inputs:{x:s},backend:n,attrs:{paddings:l,constantValue:0}}),d=_.getReshaped(c.shape,a,i,!1),h=_.getPermuted(d.length,a.length,!1),p=_.getReshapedPermuted(c.shape,a,i,!1),f=ve({inputs:{x:c},backend:n,attrs:{shape:d}}),m=Un({inputs:{x:f},backend:n,attrs:{perm:h}}),g=ve({inputs:{x:m},backend:n,attrs:{shape:p}});return u.push(c),u.push(f),u.push(m),u.forEach(y=>n.disposeIntermediateTensorInfo(y)),g},I1e={kernelName:of,backendName:"webgl",kernelFunc:k1e};function S1e(e){let{inputs:t,backend:n}=e,{indices:r,values:s,denseShape:a,defaultValue:o}=t;if(a.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
         ${a.shape}`);if(r.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
         ${r.shape}`);if(s.shape.length!==1)throw new Error(`Values must be a vector, saw:
         ${s.shape}`);if(o.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
        ${o.shape}`);let i=n.readSync(r.dataId),l=n.readSync(s.dataId),u=n.readSync(a.dataId),c=n.readSync(o.dataId)[0],[d,h,p,f,m]=Cpe(i,r.shape,r.dtype,l,s.dtype,u,c);return[n.makeTensorInfo(h,r.dtype,d),n.makeTensorInfo([h[0]],s.dtype,p),n.makeTensorInfo([f.length],"bool",new Uint8Array(f.map(g=>Number(g)))),n.makeTensorInfo([m.length],r.dtype,new Int32Array(m))]}var T1e={kernelName:Xy,backendName:"webgl",kernelFunc:S1e};function N1e(e){let{inputs:t,backend:n}=e,{inputIndices:r,inputShape:s,newShape:a}=t;if(r.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape ${r.shape}`);if(s.shape.length!==1)throw new Error(`Input shape should be a vector but received shape ${s.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(s.dataId)),i=n.readSync(r.dataId),l=Array.from(n.readSync(a.dataId)),[u,c,d]=Epe(i,r.shape,r.dtype,o,l);return[n.makeTensorInfo(c,r.dtype,u),n.makeTensorInfo([d.length],a.dtype,new Int32Array(d))]}var C1e={kernelName:Zy,backendName:"webgl",kernelFunc:N1e};function E1e(e){let{inputs:t,backend:n}=e,{data:r,indices:s,segmentIds:a}=t;if(r.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(s.shape.length!==1)throw new Error(`Indices should be a vector but received shape
              ${s.shape}`);if(a.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
              ${a.shape}`);let o=n.readSync(r.dataId),i=n.readSync(s.dataId),l=n.readSync(a.dataId),[u,c]=hE(o,r.shape,r.dtype,i,l,!0);return n.makeTensorInfo(c,r.dtype,u)}var $1e={kernelName:Yy,backendName:"webgl",kernelFunc:E1e};function _1e(e){let{inputs:t,backend:n}=e,{data:r,indices:s,segmentIds:a}=t;if(r.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(s.shape.length!==1)throw new Error(`Indices should be a vector but received shape
             ${s.shape}`);if(a.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
             ${a.shape}`);let o=n.readSync(r.dataId),i=n.readSync(s.dataId),l=n.readSync(a.dataId),[u,c]=hE(o,r.shape,r.dtype,i,l);return n.makeTensorInfo(c,r.dtype,u)}var R1e={kernelName:Jy,backendName:"webgl",kernelFunc:_1e};function D1e(e){let{inputs:t,backend:n,attrs:r}=e,{sparseIndices:s,sparseValues:a,defaultValue:o}=t,{outputShape:i}=r,{sliceRank:l,numUpdates:u,strides:c,outputSize:d}=_.calculateShapes(a,s,i),h=!1,p=new d9(u,l,s.shape.length,a.shape.length,c,[d,1],h),f=n.runWebGLProgram(p,[a,s,o],a.dtype),m=ve({inputs:{x:f},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(f),m}var F1e={kernelName:Qy,backendName:"webgl",kernelFunc:D1e};function M1e(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{numOrSizeSplits:a,axis:o}=r,i=k.parseAxisParam(o,s.shape)[0],l=_.prepareSplitSize(s,a,i),u=s.shape.length,c=new Array(u).fill(0),d=s.shape.slice();return l.map(h=>{let p=[...d];p[i]=h;let f=fh({inputs:{x:s},backend:n,attrs:{begin:c,size:p}});return c[i]+=h,f})}var O1e={kernelName:id,backendName:"webgl",kernelFunc:M1e},P1e="return sqrt(x);",z1e=it({opSnippet:P1e}),L1e={kernelName:Dl,backendName:"webgl",kernelFunc:z1e},B1e="return x * x;",W1e=it({opSnippet:B1e}),V1e={kernelName:lf,backendName:"webgl",kernelFunc:W1e},h9="return (a - b) * (a - b);",U1e=Nn({opSnippet:h9,packedOpSnippet:h9}),H1e={kernelName:Po,backendName:"webgl",kernelFunc:U1e};function G1e({inputs:e,attrs:t,backend:n}){let{x:r}=e,s=ys+`
    return x > 0.0 ? 1.0 : float(${t.alpha});
  `,a=new Qa(r.shape,s);return n.runWebGLProgram(a,[r],r.dtype)}var j1e={kernelName:Bo,backendName:"webgl",kernelFunc:G1e},q1e=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let r=n.length,s=It(n.length),a=It(n.length),o="";if(r===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=`
      ${s} begin = ${s}(${e});
      ${s} strides = ${s}(${t});

      void main() {
        ${a} coords = getOutputCoords();
        setOutput(getX(${o}));
      }
    `}};function K1e(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{begin:a,end:o,strides:i,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:d,shrinkAxisMask:h}=r,{nonStrided:p,$begin:f,$strides:m,size:g,newShape:y,outShape:A}=En.sliceInfo(s.shape,a,o,i,l,u,c,d,h),x=ve({inputs:{x:s},backend:n,attrs:{shape:y}}),b;if(p){let w=fh({inputs:{x},backend:n,attrs:{begin:f,size:g}});b=ve({inputs:{x:w},backend:n,attrs:{shape:A}}),n.disposeIntermediateTensorInfo(w)}else if(A.some(w=>w===0))b=n.makeTensorInfo(A,s.dtype,[]);else if(n.shouldExecuteOnCPU([x])){let T=n.texData.get(x.dataId).values,C=Le(x.shape,x.dtype,T),M=$pe(A,C,m,f);b=n.makeTensorInfo(A,x.dtype,M.values)}else{let I=new q1e(f,m,A);b=n.runWebGLProgram(I,[x],x.dtype)}let v=ve({inputs:{x:b},backend:n,attrs:{shape:A}});return n.disposeIntermediateTensorInfo(x),n.disposeIntermediateTensorInfo(b),v}var X1e={kernelName:ld,backendName:"webgl",kernelFunc:K1e};function Z1e(e){let{inputs:t,backend:n,attrs:r}=e,{separator:s,nGramWidths:a,leftPad:o,rightPad:i,padWidth:l,preserveShortSequences:u}=r,{data:c,dataSplits:d}=t,h=n.readSync(c.dataId),p=n.readSync(d.dataId),[f,m]=_pe(h,p,s,a,o,i,l,u);return[n.makeTensorInfo([f.length],"string",f),n.makeTensorInfo(d.shape,"int32",m)]}var Y1e={kernelName:eA,backendName:"webgl",kernelFunc:Z1e};function J1e(e){let{inputs:t,backend:n,attrs:r}=e,{skipEmpty:s}=r,{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,d]=Rpe(i,l,s),h=c.length;return[n.makeTensorInfo([h,2],"int32",u),n.makeTensorInfo([h],"string",c),n.makeTensorInfo([2],"int32",new Int32Array(d))]}var Q1e={kernelName:tA,backendName:"webgl",kernelFunc:J1e};function exe(e){let{inputs:t,backend:n,attrs:r}=e,{numBuckets:s}=r,{input:a}=t;if(a.dtype!=="string")throw new Error("Input must be of datatype string");if(s<=0)throw new Error("Number of buckets must be at least 1");let o=n.readSync(a.dataId),i=Dpe(o,s);return n.makeTensorInfo(a.shape,"int32",i)}var txe={kernelName:nA,backendName:"webgl",kernelFunc:exe},nxe="return tan(x);",rxe=it({opSnippet:nxe}),sxe={kernelName:Ol,backendName:"webgl",kernelFunc:rxe},axe=`
  float e2x = exp(-2.0 * abs(x));
  return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,oxe=it({opSnippet:axe}),ixe={kernelName:Pl,backendName:"webgl",kernelFunc:oxe},lxe=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 r=It(this.rank),s=uxe(e);this.userCode=`
      void main() {
        ${r} resRC = getOutputCoords();
        setOutput(getA(${s}));
      }
    `}};function uxe(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[];for(let s=0;s<e.length;s++)r.push(`imod(${n[s]}, ${e[s]})`);return r.join()}function p9(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{reps:a}=r;if(s.dtype==="string"||s.shape.length>5){let l=n.readSync(s.dataId),u=s.dtype==="string"?l.map(h=>k.decodeString(h)):l,c=Le(s.shape,s.dtype,u),d=Mpe(c,a);return n.makeTensorInfo(d.shape,d.dtype,d.values)}let o=new lxe(s.shape,a);return n.runWebGLProgram(o,[s],s.dtype)}var cxe={kernelName:Lo,backendName:"webgl",kernelFunc:p9};function dxe(e){let{inputs:t,backend:n,attrs:r}=e,{x:s}=t,{k:a,sorted:o}=r,i=n.readSync(s.dataId),[l,u]=Ope(i,s.shape,s.dtype,a,o);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(u.shape,u.dtype,u.values)]}var hxe={kernelName:ud,backendName:"webgl",kernelFunc:dxe},pxe=class{constructor(e,t,n,r,s,a){this.variableNames=["Image","Transforms"],this.outputShape=a;let o=n==="nearest"?1:2,i;switch(r){case"constant":i=1;break;case"reflect":i=2;break;case"wrap":i=3;break;case"nearest":i=4;break;default:i=1;break}this.userCode=`
            float mapCoord(float outCoord, float len) {
              float inCoord = outCoord;
              if(${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 < ${t}) {
                  outputValue = getImage(batch, coordY, coordX, channel);
              } else {
                outputValue = float(${s});
              }
              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(${s});
              } else {
                float inX = (a1 * xf + a2 * yf + a3) / projection;
                float inY = (b1 * xf + b2 * yf + b3) / projection;
                float mapX = mapCoord(inX, float(${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 fxe(e){let{inputs:t,backend:n,attrs:r}=e,{image:s,transforms:a}=t,{interpolation:o,fillMode:i,fillValue:l,outputShape:u}=r,[c,d,h,p]=s.shape,[f,m]=u!=null?u:[d,h],g=[c,f,m,p],y=new pxe(d,h,o,i,l,g);return n.runWebGLProgram(y,[s,a],"float32")}var mxe={kernelName:cd,backendName:"webgl",kernelFunc:fxe};function gxe(e){let{inputs:t,attrs:n,backend:r}=e,{axis:s}=n,{x:a}=t;mu(a,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let o=r.readSync(a.dataId),{outputValues:i,outputShape:l,indices:u}=Ppe(o,s,a.shape,a.dtype);return[r.makeTensorInfo(l,a.dtype,i),r.makeTensorInfo([u.length],"int32",u)]}var yxe={kernelName:rA,backendName:"webgl",kernelFunc:gxe};function Axe(e){let{inputs:t,backend:n,attrs:r}=e,{value:s}=t,{axis:a}=r;a<0&&(a+=s.shape.length);let o=s,i=o.shape.length,l=s.shape[a],u=new Array(i-1),c=0;for(let m=0;m<i;m++)m!==a&&(u[c++]=o.shape[m]);let d=[],h=new Array(i).fill(0),p=o.shape.slice();p[a]=1;let f=new Array(l);for(let m=0;m<f.length;m++){h[a]=m;let g=fh({inputs:{x:o},backend:n,attrs:{begin:h,size:p}}),y=ve({inputs:{x:g},backend:n,attrs:{shape:u}});f[m]=y,d.push(g)}return d.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var xxe={kernelName:dd,backendName:"webgl",kernelFunc:Axe},bxe=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,r=e.batchSize,s=e.inSize,a=e.numSegments,o=a*Math.ceil(s/n);this.outputShape=[r,o];let i="0.0",l="sumValue",u=Math.floor(n/4)*4,c=n%4,d=`
        sumValue += dot(values, segFilter);
    `,h="";s%n>0&&(h=`
        if (inIdx < 0 || inIdx >= ${s}) {
          return initializationValue;
        }
      `);let p="";s%n>0&&(p=`
        if (inIdx < 0 || inIdx >= ${s}) {
          return -1.0;
        }
      `),this.userCode=`
      const float initializationValue = ${i};

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

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

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

          ${d}
        }

        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
          );

          ${d}
        } else if (${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
          );

          ${d}
        } else if (${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
          );

          ${d}
        }
        setOutput(${l});
      }
    `}};function vxe(e){let{inputs:t,backend:n,attrs:r}=e,{x:s,segmentIds:a}=t,{numSegments:o}=r,i=s.shape.length,l=[],u=0,c=_.getAxesPermutation([u],i),d=s;c!=null&&(d=Un({inputs:{x:s},backend:n,attrs:{perm:c}}),l.push(d),u=_.getInnerMostAxes(1,i)[0]);let h=_.segment_util.computeOutShape(d.shape,u,o),p=k.sizeFromShape([d.shape[u]]),f=ve({inputs:{x:d},backend:n,attrs:{shape:[-1,p]}});l.push(f);let m=fA(s.dtype),g=(b,v,w,I,T)=>{let C=b.shape[0],M=b.shape[1],$=_.segment_util.segOpComputeOptimalWindowSize(M,T),R={windowSize:$,inSize:M,batchSize:C,numSegments:T},N=new bxe(R,v),F=n.compileAndRun(N,[b,w],I);if(l.push(F),F.shape[1]===T)return F;let B=c9({backend:n,attrs:{start:0,stop:T,step:1,dtype:"float32"}}),j=p9({inputs:{x:B},backend:n,attrs:{reps:[M/$]}});return l.push(B),l.push(j),g(F,v,j,I,T)},y=g(f,"unsortedSegmentSum",a,m,o),A=ve({inputs:{x:y},backend:n,attrs:{shape:h}}),x=A;if(c!=null){l.push(A);let b=_.getUndoAxesPermutation(c);x=Un({inputs:{x},backend:n,attrs:{perm:b}})}return l.forEach(b=>n.disposeIntermediateTensorInfo(b)),x}var wxe={kernelName:uf,backendName:"webgl",kernelFunc:vxe},kxe=[Y2e,eye,Ofe,zfe,Wfe,Hfe,jfe,Xfe,Yfe,Qfe,rme,ame,lme,dme,Ame,fme,vme,Sme,kme,Eme,_me,Dme,Pme,Hme,jme,Jme,e0e,s0e,i0e,yfe,h0e,w0e,I0e,g0e,C0e,$0e,T0e,D0e,O0e,L0e,W0e,U0e,j0e,J0e,ege,K0e,rge,oge,lge,hge,gge,bge,kge,Ige,Sge,Nge,Ege,_ge,Dge,Mge,Lge,Vge,Gge,qge,Zge,e2e,s2e,l2e,gfe,c2e,c0e,p2e,g2e,x2e,xfe,k2e,N2e,E2e,O2e,D2e,B2e,U2e,q2e,nye,cye,lye,fye,gye,Aye,oye,bye,wye,Tye,$ye,Fye,Vye,Ife,Hye,qye,Zye,Qye,Kme,nAe,sAe,oAe,uAe,pAe,vfe,mAe,gAe,Xme,zye,xAe,NAe,kAe,Tfe,_Ae,FAe,zAe,WAe,GAe,qAe,ZAe,QAe,t1e,s1e,i1e,c1e,p1e,g1e,x1e,Vme,Bye,w1e,I1e,T1e,C1e,$1e,R1e,F1e,O1e,L1e,V1e,H1e,j1e,X1e,Y1e,Q1e,txe,Lye,Dfe,sxe,ixe,cxe,hxe,mxe,Ffe,yxe,xxe,wxe,rAe];for(let e of kxe)iA(e);var tr;(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"})(tr||(tr={}));var gh;(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"})(gh||(gh={}));var f9;function Ixe(e){f9=e.wasm.cwrap(Ll,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function Sxe(e){let{inputs:t,backend:n,attrs:r}=e,{a:s,b:a,bias:o,preluActivationWeights:i}=t;if(s.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:d}=r,h=n.dataIdMap.get(s.dataId).id,p=n.dataIdMap.get(a.dataId).id,f=0;if(o!=null){let T=n.dataIdMap.get(o.dataId);if(T.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${T.shape.length}.`);f=T.id}let m=i==null?0:n.dataIdMap.get(i.dataId).id,g=gh[c];if(g==null)throw new Error(`${c} activation not yet supported for FusedConv2D in the wasm backend.`);let y=l?s.shape[2]:s.shape[1],A=u?a.shape[1]:a.shape[2],x=s.shape[0],b=n.makeOutput([x,y,A],s.dtype),v=n.dataIdMap.get(b.dataId).id,w=new Uint8Array(new Int32Array(s.shape).buffer),I=new Uint8Array(new Int32Array(a.shape).buffer);return f9(h,w,s.shape.length,p,I,a.shape.length,l,u,g,f,m,d||0,v),b}var Txe={kernelName:Ll,backendName:"wasm",setupFunc:Ixe,kernelFunc:Sxe};function Hn(e){let t;function n(s){t=s.wasm.cwrap(e,null,["number","number"])}function r(s){let{backend:a,inputs:{x:o}}=s,i=a.dataIdMap.get(o.dataId).id,l=a.makeOutput(o.shape,o.dtype),u=a.dataIdMap.get(l.dataId).id;return k.sizeFromShape(l.shape)===0||t(i,u),l}return{kernelName:e,backendName:"wasm",setupFunc:n,kernelFunc:r}}var Nxe=Hn(xc);function Gn(e,t,n){let r;function s(o){r=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,d=i.dataIdMap.get(u.dataId).id,h=i.dataIdMap.get(c.dataId).id,p=n!=null?n:u.dtype,f=_.assertAndGetBroadcastShape(u.shape,c.shape),m=i.makeOutput(f,p);if(k.sizeFromShape(f)===0)return m;let g=new Uint8Array(new Int32Array(u.shape).buffer),y=new Uint8Array(new Int32Array(c.shape).buffer),A=i.dataIdMap.get(m.dataId).id,x=()=>r(d,g,u.shape.length,h,y,c.shape.length,tr[u.dtype],A);if(t&&u.dtype==="float32")return x(),m;let b=_.getBroadcastDims(u.shape,f),v=_.getBroadcastDims(c.shape,f),w=b.every((T,C)=>T===C),I=v.every((T,C)=>T===C);if(w&&I)return x(),m;throw new Error(`Broadcasting along outer dims is not yet supported for ${u.dtype} ${e}.`)}return{kernelName:e,backendName:"wasm",setupFunc:s,kernelFunc:a}}var Cxe=!0,Exe=Gn(Fa,Cxe),m9;function $xe(e){m9=e.wasm.cwrap(Zi,null,["array","number","number","number"])}function _xe(e){let{inputs:t,backend:n}=e,r=n.makeOutput(t[0].shape,t[0].dtype);if(k.sizeFromShape(r.shape)===0)return r;let s=t.map(i=>n.dataIdMap.get(i.dataId).id),a=new Uint8Array(new Int32Array(s).buffer),o=n.dataIdMap.get(r.dataId).id;return m9(a,s.length,tr[r.dtype],o),r}var Rxe={kernelName:Zi,backendName:"wasm",setupFunc:$xe,kernelFunc:_xe};function Qm(e){let{inputs:{x:t},backend:n}=e,r=n.makeOutput(t.shape,t.dtype),s=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(r).set(s),r}var Dxe={kernelName:hl,backendName:"wasm",kernelFunc:Qm},g9;function Fxe(e){g9=e.wasm.cwrap(zl,null,["number","array","number","number","number","array","number"])}function e0(e){let{inputs:t,backend:n,attrs:r}=e,[s,a]=Oxe(t.x.shape,r.perm),o=!0;for(let f=0;f<a.length;f++)a[f]!==f&&(o=!1);let i=Mxe(t.x.shape,r.perm),l={dataId:t.x.dataId,shape:s,dtype:t.x.dtype};if(o){let f=Qm({inputs:t,backend:n});return f.shape=i,f}let u=n.makeOutput(i,l.dtype),c=n.dataIdMap.get(l.dataId).id,d=n.dataIdMap.get(u.dataId).id,h=new Uint8Array(new Int32Array(a).buffer),p=new Uint8Array(new Int32Array(l.shape).buffer);return g9(c,p,l.shape.length,tr[l.dtype],d,h,a.length),u}function Mxe(e,t){let n=new Array(e.length);for(let r=0;r<n.length;r++)n[r]=e[t[r]];return n}function Oxe(e,t){let n=[],r=[];for(let s=0;s<e.length;++s)e[s]!==1&&n.push(e[s]),e[t[s]]!==1&&r.push(t[s]);for(let s=0;s<r.length;++s){let a=-1;for(let o=0;o<r.length;++o)r[o]>=s&&(a===-1||r[a]>r[o])&&(a=o);r[a]=s}return[n,r]}var Pxe={kernelName:zl,backendName:"wasm",kernelFunc:e0,setupFunc:Fxe};function to(e,t,n){let r=e.shape,s=e.shape.length,a=k.parseAxisParam(t,r),o=a,i=_.getAxesPermutation(o,s),l=null,u=!1;if(i!=null){let c=new Array(s);for(let p=0;p<c.length;p++)c[p]=r[i[p]];o=_.getInnerMostAxes(o.length,s),l=e0({inputs:{x:e},attrs:{perm:i},backend:n});let d=n.dataIdMap.get(e.dataId).id;n.dataIdMap.get(l.dataId).id!==d&&(u=!0)}return{transposed:l,originalAxes:a,axes:o,inputWasTransposed:u}}var y9;function zxe(e){y9=e.wasm.cwrap(wc,null,["number, number, number"])}function Lxe(e){let{backend:t,inputs:n,attrs:r}=e,{axis:s,keepDims:a}=r,{x:o}=n,l=t.dataIdMap.get(o.dataId).id,u=o,{transposed:c,axes:d,originalAxes:h,inputWasTransposed:p}=to(o,s,t);if(p){let x=t.dataIdMap.get(c.dataId).id;u=c,l=x}let f=u.shape.length;_.assertAxesAreInnerMostDims("all",d,f);let[m,g]=_.computeOutAndReduceShapes(u.shape,d),y=k.sizeFromShape(g),A=t.makeOutput(m,o.dtype);if(k.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(A.dataId).id;y9(l,y,x)}if(p&&t.disposeData(c.dataId),a){let x=_.expandShapeToKeepDim(A.shape,h);A.shape=x}return A}var Bxe={kernelName:wc,backendName:"wasm",setupFunc:zxe,kernelFunc:Lxe},A9;function Wxe(e){A9=e.wasm.cwrap(kc,null,["number, number, number"])}function Vxe(e){let{backend:t,inputs:n,attrs:r}=e,{axis:s,keepDims:a}=r,{x:o}=n,l=t.dataIdMap.get(o.dataId).id,u=o,{transposed:c,axes:d,originalAxes:h,inputWasTransposed:p}=to(o,s,t);if(p){let x=t.dataIdMap.get(c.dataId).id;u=c,l=x}let f=u.shape.length;_.assertAxesAreInnerMostDims("any",d,f);let[m,g]=_.computeOutAndReduceShapes(u.shape,d),y=k.sizeFromShape(g),A=t.makeOutput(m,o.dtype);if(k.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(A.dataId).id;A9(l,y,x)}if(p&&t.disposeData(c.dataId),a){let x=_.expandShapeToKeepDim(A.shape,h);A.shape=x}return A}var Uxe={kernelName:kc,backendName:"wasm",setupFunc:Wxe,kernelFunc:Vxe},x9;function Hxe(e){x9=e.wasm.cwrap(Yi,null,["number","number","number","number","number"])}function Gxe(e){let{backend:t,inputs:n,attrs:r}=e,{axis:s}=r,{x:a}=n,o=t.dataIdMap.get(a.dataId).id,i=o,l=a,{transposed:u,axes:c,inputWasTransposed:d}=to(a,s,t);if(d){let y=t.dataIdMap.get(u.dataId).id;y!==o&&(l=u,i=y)}let h=l.shape.slice(0,-1),p=t.makeOutput(h,"int32"),f=t.dataIdMap.get(p.dataId).id,m=k.sizeFromShape(p.shape),g=l.shape[c[0]];return x9(i,tr[l.dtype],m,g,f),d&&t.disposeData(u.dataId),p}var jxe={kernelName:Yi,backendName:"wasm",kernelFunc:Gxe,setupFunc:Hxe},b9;function qxe(e){b9=e.wasm.cwrap(Ji,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Kxe(e){let{inputs:t,attrs:n,backend:r}=e,s=t.x,a=r.dataIdMap.get(s.dataId).id,{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=n,c=_.computePool2DInfo(s.shape,o,i,1,l,u),d=c.filterHeight,h=c.filterWidth,p=c.padInfo.top,f=c.padInfo.right,m=c.padInfo.bottom,g=c.padInfo.left,y=c.strideHeight,A=c.strideWidth,x=c.inChannels;if(c.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${c.dataFormat}'. Please use 'channelsLast'.`);if(c.dilationWidth!==1||c.dilationHeight!==1)throw new Error(`was backend only supports average pooling with dilation = [1, 1], got [${c.dilationHeight}, ${c.dilationWidth}].`);let b=r.makeOutput(c.outShape,"float32"),v=r.dataIdMap.get(b.dataId).id;return b9(a,s.shape[0],s.shape[1],s.shape[2],d,h,p,f,m,g,y,A,x,v),b}var Xxe={kernelName:Ji,backendName:"wasm",setupFunc:qxe,kernelFunc:Kxe};function As(e){let{inputs:t,attrs:n}=e,{x:r}=t,{shape:s}=n,a=k.sizeFromShape(r.shape),o=k.inferFromImplicitShape(s,a);return k.assert(a===k.sizeFromShape(o),()=>`new shape: ${o}, old shape: ${r.shape}. New shape and old shape must have the same number of elements.`),e.backend.incRef(r.dataId),{dataId:r.dataId,shape:o,dtype:r.dtype}}var Zxe={kernelName:Qc,backendName:"wasm",kernelFunc:As},v9;function Yxe(e){v9=e.wasm.cwrap(Qi,null,["number","array","number","number","array","number","number","number","number"])}function Jxe(e){let{inputs:t,backend:n,attrs:r}=e,{a:s,b:a}=t,{transposeA:o,transposeB:i}=r;if(s.dtype!=="float32"||a.dtype!=="float32")throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");let l=s.shape.length,u=a.shape.length,c=o?s.shape[l-2]:s.shape[l-1],d=i?a.shape[u-1]:a.shape[u-2],h=o?s.shape[l-1]:s.shape[l-2],p=i?a.shape[u-2]:a.shape[u-1],f=s.shape.slice(0,-2),m=a.shape.slice(0,-2),g=k.sizeFromShape(f),y=k.sizeFromShape(m),A=g===y||g===1||y===1;k.assert(l>=2&&u>=2&&A,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. 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Please use 'channelsLast'.`);let $=r.makeOutput(p.outShape,"float32"),R=r.dataIdMap.get($.dataId).id;return E9(o,s.shape[0],s.shape[1],s.shape[2],i,f,m,g,y,A,x,M,b,v,w,I,T,C,R),$}var I5e={kernelName:al,backendName:"wasm",setupFunc:w5e,kernelFunc:k5e},S5e=!1,T5e=Gn(il,S5e,"bool"),N5e=Hn(Eo);function mb(e){let{inputs:t,attrs:n,backend:r}=e,{input:s}=t,{dim:a}=n,o=s.shape.length,i=s.shape.slice(),l=a;return a<0&&(k.assert(-(o+1)<=a,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+a+1),i.splice(l,0,1),As({inputs:{x:s},backend:r,attrs:{shape:i}})}var C5e={kernelName:Mc,backendName:"wasm",kernelFunc:mb};function E5e(e){let{attrs:{shape:t,value:n,dtype:r},backend:s}=e,a=s.makeOutput(t,r);return s.typedArrayFromHeap(a).fill(n),a}var $5e={kernelName:Qp,backendName:"wasm",kernelFunc:E5e},$9;function _5e(e){$9=e.wasm.cwrap(Oc,null,["number","number","number","number","number","number"])}function R5e(e){let{inputs:t,backend:n}=e,{image:r}=t,s=n.makeOutput(r.shape,r.dtype),a=n.dataIdMap.get(r.dataId).id,o=n.dataIdMap.get(s.dataId).id,[i,l,u,c]=r.shape;return $9(a,i,l,u,c,o),s}var D5e={kernelName:Oc,backendName:"wasm",kernelFunc:R5e,setupFunc:_5e},F5e=Hn($o),M5e=!1,O5e=Gn(ul,M5e),_9;function P5e(e){_9=e.wasm.cwrap(cl,null,["number","number","number","number","number","number","number"])}function z5e(e){let{backend:t,inputs:n,attrs:r}=e,{varianceEpsilon:s}=r,{x:a,mean:o,variance:i,offset:l,scale:u}=n,c=t.dataIdMap.get(a.dataId).id,d=t.dataIdMap.get(o.dataId).id,h=t.dataIdMap.get(i.dataId).id,p=l!=null?t.dataIdMap.get(l.dataId).id:0,f=u!=null?t.dataIdMap.get(u.dataId).id:0,m=t.makeOutput(a.shape,a.dtype);if(k.sizeFromShape(a.shape)===0)return m;let g=t.dataIdMap.get(m.dataId).id;return _9(c,d,h,p,f,s,g),m}var L5e={kernelName:cl,backendName:"wasm",setupFunc:P5e,kernelFunc:z5e},R9;function B5e(e){R9=e.wasm.cwrap(Bl,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function W5e(e){let{inputs:t,attrs:n,backend:r}=e,{x:s,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dataFormat:d,dimRoundingMode:h,activation:p,leakyreluAlpha:f}=n,m=_.computeConv2DInfo(s.shape,a.shape,l,c,u,h),g=gh[p];if(g==null)throw new Error(`${p} activation not yet supported for FusedConv2D in the wasm backend.`);let y=r.dataIdMap.get(s.dataId).id,A=r.dataIdMap.get(a.dataId).id,x=m.outChannels,b=0;if(o!=null){let ne=r.dataIdMap.get(o.dataId);if(ne.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${ne.shape.length}.`);if(ne.shape[0]!==x)throw new Error(`FusedConv2D bias shape (${ne.shape}) does not match the number of output channels (${x})`);b=ne.id}let v=m.filterHeight,w=m.filterWidth,I=m.padInfo.top,T=m.padInfo.right,C=m.padInfo.bottom,M=m.padInfo.left,$=m.dilationHeight,R=m.dilationWidth,N=m.strideHeight,F=m.strideWidth,B=m.inChannels,j=m.padInfo.type==="SAME"?1:0,X=m.batchSize,Y=m.inHeight,ee=m.inWidth;if(d!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${d}'. Please use 'NHWC'.`);let oe=r.makeOutput(m.outShape,"float32"),se=r.dataIdMap.get(oe.dataId).id,ie=i==null?0:r.dataIdMap.get(i.dataId).id;return R9(y,X,Y,ee,A,v,w,b,I,T,C,M,j,$,R,N,F,B,x,g,ie,f||0,se),oe}var V5e={kernelName:Bl,backendName:"wasm",setupFunc:B5e,kernelFunc:W5e},D9;function U5e(e){D9=e.wasm.cwrap(Wl,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function H5e(e){let{inputs:t,attrs:n,backend:r}=e,{x:s,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dataFormat:d,dimRoundingMode:h,activation:p,leakyreluAlpha:f}=n,m=_.computeConv2DInfo(s.shape,a.shape,l,c,u,h,!0),g=gh[p];if(g==null)throw new Error(`${p} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);let y=r.dataIdMap.get(s.dataId).id,A=r.dataIdMap.get(a.dataId).id,x=m.outChannels,b=0;if(o!=null){let ne=r.dataIdMap.get(o.dataId);if(ne.shape.length!==1)throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${ne.shape.length}.`);if(ne.shape[0]!==x)throw new Error(`FusedDepthwiseConv2D bias shape (${ne.shape}) does not match the number of output channels (${x})`);b=ne.id}let v=m.filterHeight,w=m.filterWidth,I=m.padInfo.top,T=m.padInfo.right,C=m.padInfo.bottom,M=m.padInfo.left,$=m.dilationHeight,R=m.dilationWidth,N=m.strideHeight,F=m.strideWidth,B=m.inChannels,j=m.padInfo.type==="SAME"?1:0,X=m.batchSize,Y=m.inHeight,ee=m.inWidth;if(d!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${d}'. 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b=_.expandShapeToKeepDim(x.shape,h);x.shape=b}return u.dtype!=="float32"&&t.disposeData(A.dataId),x}var wbe={kernelName:Al,backendName:"wasm",setupFunc:bbe,kernelFunc:vbe},B9;function kbe(e){B9=e.wasm.cwrap(xl,null,["number, number, number"])}function Ibe(e){let{backend:t,inputs:n,attrs:r}=e,{axis:s,keepDims:a}=r,{x:o}=n,i=t.dataIdMap.get(o.dataId).id,l=i,u=o,{transposed:c,axes:d,originalAxes:h,inputWasTransposed:p}=to(o,s,t);if(p){let x=t.dataIdMap.get(c.dataId).id;x!==i&&(u=c,l=x)}let f=u.shape.length;_.assertAxesAreInnerMostDims("min",d,f);let[m,g]=_.computeOutAndReduceShapes(u.shape,d),y=k.sizeFromShape(g),A=t.makeOutput(m,u.dtype);if(k.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(A.dataId).id;B9(l,y,x)}if(p&&t.disposeData(c.dataId),a){let x=_.expandShapeToKeepDim(A.shape,h);A.shape=x}return A}var Sbe={kernelName:xl,backendName:"wasm",setupFunc:kbe,kernelFunc:Ibe},Tbe=!1,Nbe=Gn(Fo,Tbe),gb;(function(e){e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric"})(gb||(gb={}));var W9;function Cbe(e){W9=e.wasm.cwrap(bl,null,["number","array","number","number","array","array","number","number"])}function Ebe(e){let{inputs:{x:t},backend:n,attrs:{paddings:r,mode:s}}=e,a=r.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=r.map(f=>f[0]),d=r.map(f=>f[1]),h=new Uint8Array(new Int32Array(c).buffer),p=new Uint8Array(new Int32Array(d).buffer);return W9(o,u,t.shape.length,tr[t.dtype],h,p,gb[s],l),i}var $be={kernelName:bl,backendName:"wasm",kernelFunc:Ebe,setupFunc:Cbe},_be=!0,Rbe=Gn(Mo,_be),Dbe=Hn(Gc);function yb(e,t){let n=new Int32Array(e.wasm.HEAPU8.buffer,t,4),r=n[0],s=n[1],a=n[2],o=n[3];return e.wasm._free(t),{pSelectedIndices:r,selectedSize:s,pSelectedScores:a,pValidOutputs:o}}var V9;function Fbe(e){V9=e.wasm.cwrap(jc,"number",["number","number","number","number","number"])}function Mbe(e){let{backend:t,inputs:n,attrs:r}=e,{iouThreshold:s,maxOutputSize:a,scoreThreshold:o}=r,{boxes:i,scores:l}=n,u=t.dataIdMap.get(i.dataId).id,c=t.dataIdMap.get(l.dataId).id,d=V9(u,c,a,s,o),{pSelectedIndices:h,selectedSize:p,pSelectedScores:f,pValidOutputs:m}=yb(t,d);return t.wasm._free(f),t.wasm._free(m),t.makeOutput([p],"int32",h)}var Obe={kernelName:jc,backendName:"wasm",setupFunc:Fbe,kernelFunc:Mbe},U9;function Pbe(e){U9=e.wasm.cwrap(qc,"number",["number","number","number","number","number","bool"])}function zbe(e){let{backend:t,inputs:n,attrs:r}=e,{iouThreshold:s,maxOutputSize:a,scoreThreshold:o,padToMaxOutputSize:i}=r,{boxes:l,scores:u}=n,c=t.dataIdMap.get(l.dataId).id,d=t.dataIdMap.get(u.dataId).id,h=U9(c,d,a,s,o,i),{pSelectedIndices:p,selectedSize:f,pSelectedScores:m,pValidOutputs:g}=yb(t,h);t.wasm._free(m);let y=t.makeOutput([f],"int32",p),A=t.makeOutput([],"int32",g);return[y,A]}var Lbe={kernelName:qc,backendName:"wasm",setupFunc:Pbe,kernelFunc:zbe},H9;function Bbe(e){H9=e.wasm.cwrap(Kc,"number",["number","number","number","number","number","number"])}function Wbe(e){let{backend:t,inputs:n,attrs:r}=e,{iouThreshold:s,maxOutputSize:a,scoreThreshold:o,softNmsSigma:i}=r,{boxes:l,scores:u}=n,c=t.dataIdMap.get(l.dataId).id,d=t.dataIdMap.get(u.dataId).id,h=H9(c,d,a,s,o,i),{pSelectedIndices:p,selectedSize:f,pSelectedScores:m,pValidOutputs:g}=yb(t,h);t.wasm._free(g);let y=t.makeOutput([f],"int32",p),A=t.makeOutput([f],"float32",m);return[y,A]}var Vbe={kernelName:Kc,backendName:"wasm",setupFunc:Bbe,kernelFunc:Wbe},Ube=!1,Hbe=Gn(vl,Ube,"bool"),G9;function Gbe(e){G9=e.wasm.cwrap(wl,null,["number","number","number","number","number"])}function jbe(e){let{inputs:t,backend:n,attrs:r}=e,{indices:s}=t,{depth:a,onValue:o,offValue:i}=r,l=n.makeOutput([...s.shape,a],"int32"),u=n.dataIdMap.get(l.dataId).id,d=n.dataIdMap.get(s.dataId).id;return G9(d,a,o,i,u),l}var qbe={kernelName:wl,backendName:"wasm",setupFunc:Gbe,kernelFunc:jbe};function Kbe(e){let{inputs:{x:t},backend:n}=e,r=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(r).fill(1),r}var Xbe={kernelName:Xc,backendName:"wasm",kernelFunc:Kbe};function Zbe(e){let{inputs:t,backend:n,attrs:r}=e,{axis:s}=r;if(t.length===1)return mb({inputs:{input:t[0]},backend:n,attrs:{dim:s}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{k.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),k.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let d=mb({inputs:{input:c},backend:n,attrs:{dim:s}});return i.push(d),d}),u=k9({inputs:l,backend:n,attrs:{axis:s}});return i.forEach(c=>n.disposeData(c.dataId)),u}var Ybe={kernelName:Zc,backendName:"wasm",kernelFunc:Zbe},j9;function Jbe(e){j9=e.wasm.cwrap(kl,null,["number","array","number","number","array","array","number","number"])}function Qbe(e){let{inputs:{x:t},backend:n,attrs:{paddings:r,constantValue:s}}=e,a=r.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=r.map(f=>f[0]),d=r.map(f=>f[1]),h=new Uint8Array(new Int32Array(c).buffer),p=new Uint8Array(new Int32Array(d).buffer);return j9(o,u,t.shape.length,tr[t.dtype],h,p,s,l),i}var e3e={kernelName:kl,backendName:"wasm",kernelFunc:Qbe,setupFunc:Jbe},t3e=!1,n3e=Gn(Il,t3e),q9;function r3e(e){q9=e.wasm.cwrap(Sl,null,["number","number","number"])}function s3e(e){let{inputs:t,backend:n}=e,{x:r,alpha:s}=t,a=n.dataIdMap.get(r.dataId).id,o=n.dataIdMap.get(s.dataId).id,i=n.makeOutput(r.shape,"float32"),l=n.dataIdMap.get(i.dataId).id;return q9(a,o,l),i}var a3e={kernelName:Sl,backendName:"wasm",setupFunc:r3e,kernelFunc:s3e},K9;function o3e(e){K9=e.wasm.cwrap(Yc,null,["number","number","number","number"])}function 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Ove=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],Pve=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],zve=[33,133,362,263,1,78,308],y7e=Ove.map(e=>wh[e]),A7e=Pve.map(e=>wh[e]),x7e=zve.map(e=>wh[e]);var kb=Bs.leftEyeLower0,Ib=Bs.rightEyeLower0,Cu={leftBounds:[kb[0],kb[kb.length-1]],rightBounds:[Ib[0],Ib[Ib.length-1]]},l0={count:468,mouth:13,symmetryLine:[13,Bs.midwayBetweenEyes[0]]},w$={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},Eu={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function u0(e,t,n,r){for(let s=0;s<wb.length;s++){let{key:a,indices:o}=wb[s],i=Bs[`${n}${a}`];if(!r||r.includes(a))for(let l=0;l<o.length;l++){let u=o[l];e[i[l]]=[t[u][0],t[u][1],(t[u][2]+e[i[l]][2])/2]}}}var Sb=class{constructor(t,n,r){var s,a;this.storedBoxes=[],this.boundingBoxDetector=t,this.meshDetector=n,this.irisModel=r,this.boxSize=((s=t==null?void 0:t.model)==null?void 0:s.inputs[0].shape[2])||0,this.meshSize=(n==null?void 0:n.inputs[0].shape[2])||((a=t==null?void 0:t.model)==null?void 0:a.inputs[0].shape[2]),this.irisSize=(r==null?void 0:r.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(t,n,r,s){let a=vh({startPoint:n.startPoint,endPoint:n.endPoint}),o=t.map(d=>[a[0]/this.meshSize*(d[0]-this.meshSize/2),a[1]/this.meshSize*(d[1]-this.meshSize/2),d[2]]),i=r!==0?i0(r,[0,0]):o0,l=r!==0?o.map(d=>[...y$(d,i),d[2]]):o,u=r!==0?g$(s):o0,c=[...Tu({startPoint:n.startPoint,endPoint:n.endPoint}),1];return l.map(d=>[Math.round(d[0]+no(c,u[0])),Math.round(d[1]+no(c,u[1])),Math.round(d[2])])}getLeftToRightEyeDepthDifference(t){let n=t[Cu.leftBounds[0]][2],r=t[Cu.rightBounds[0]][2];return n-r}getEyeBox(t,n,r,s,a=!1){let o=a0(s0(bb([t[r],t[s]]),this.irisEnlarge)),i=vh(o),l=Ye.cropAndResize(n,[[o.startPoint[1]/this.meshSize,o.startPoint[0]/this.meshSize,o.endPoint[1]/this.meshSize,o.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return a&&Sr.flags.IS_BROWSER&&(l=Ye.flipLeftRight(l)),{box:o,boxSize:i,crop:l}}getEyeCoords(t,n,r,s=!1){let a=[];for(let o=0;o<Eu.numCoordinates;o++){let i=t[o*3],l=t[o*3+1],u=t[o*3+2];a.push([(s?1-i/this.irisSize:i/this.irisSize)*r[0]+n.startPoint[0],l/this.irisSize*r[1]+n.startPoint[1],u])}return{rawCoords:a,iris:a.slice(Eu.index)}}getAdjustedIrisCoords(t,n,r){let s=t[Bs[`${r}EyeUpper0`][Eu.upperCenter]][2],a=t[Bs[`${r}EyeLower0`][Eu.lowerCenter]][2],o=(s+a)/2;return n.map((i,l)=>{let u=o;return l===2?u=s:l===4&&(u=a),[i[0],i[1],u]})}async predict(t,n){let r=!1,s;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.skipFrame)&&(s=await this.boundingBoxDetector.getBoundingBoxes(t),this.skipped=0),n.skipFrame&&this.skipped++,!n.skipFrame||s&&s.boxes&&(!n.face.mesh.enabled||s.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxDetected)){this.storedBoxes=[],this.detectedFaces=0;for(let o of s.boxes)this.storedBoxes.push({startPoint:o.box.startPoint.dataSync(),endPoint:o.box.endPoint.dataSync(),landmarks:o.landmarks.arraySync(),confidence:o.confidence});this.storedBoxes.length>0&&(r=!0)}if(r){if(!s||!s.boxes||s.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let o=0;o<this.storedBoxes.length;o++){let i=h$({startPoint:this.storedBoxes[o].startPoint,endPoint:this.storedBoxes[o].endPoint},s.scaleFactor),l=s0(i),u=a0(l),c=this.storedBoxes[o].landmarks,d=this.storedBoxes[o].confidence;this.storedBoxes[o]={...u,confidence:d,landmarks:c}}}s&&s.boxes&&s.boxes.forEach(o=>{o.box.startPoint.dispose(),o.box.endPoint.dispose(),o.landmarks.dispose()});let a=Ue(()=>this.storedBoxes.map((o,i)=>{let l,u=0,c;if(n.face.detector.rotation&&n.face.mesh.enabled&&Sr.flags.IS_BROWSER){let[x,b]=o.landmarks.length>=l0.count?l0.symmetryLine:w$.symmetryLine;u=vb(o.landmarks[x],o.landmarks[b]);let v=Tu({startPoint:o.startPoint,endPoint:o.endPoint}),w=[v[0]/t.shape[2],v[1]/t.shape[1]],I=Ye.rotateWithOffset(t,u,0,w);c=i0(-u,v),n.face.mesh.enabled?l=Nu({startPoint:o.startPoint,endPoint:o.endPoint},I,[this.meshSize,this.meshSize]).div(255):l=Nu({startPoint:o.startPoint,endPoint:o.endPoint},I,[this.boxSize,this.boxSize]).div(255)}else{c=o0;let x=t.clone();n.face.mesh.enabled?l=Nu({startPoint:o.startPoint,endPoint:o.endPoint},x,[this.meshSize,this.meshSize]).div(255):l=Nu({startPoint:o.startPoint,endPoint:o.endPoint},x,[this.boxSize,this.boxSize]).div(255)}if(!n.face.mesh.enabled)return{mesh:[],box:o,faceConfidence:null,boxConfidence:o.confidence,confidence:o.confidence,image:l};let[,d,h]=this.meshDetector.execute(l),p=d.dataSync()[0];if(p<n.face.detector.minConfidence)return this.storedBoxes[i].confidence=p,null;let m=ue(h,[-1,3]).arraySync();if(n.face.iris.enabled){let{box:x,boxSize:b,crop:v}=this.getEyeBox(m,l,Cu.leftBounds[0],Cu.leftBounds[1],!0),{box:w,boxSize:I,crop:T}=this.getEyeBox(m,l,Cu.rightBounds[0],Cu.rightBounds[1]),M=this.irisModel.predict(an([v,T])).dataSync(),$=M.slice(0,Eu.numCoordinates*3),{rawCoords:R,iris:N}=this.getEyeCoords($,x,b,!0),F=M.slice(Eu.numCoordinates*3),{rawCoords:B,iris:j}=this.getEyeCoords(F,w,I),X=this.getLeftToRightEyeDepthDifference(m);Math.abs(X)<30?(u0(m,R,"left",null),u0(m,B,"right",null)):X<1?u0(m,R,"left",["EyeUpper0","EyeLower0"]):u0(m,B,"right",["EyeUpper0","EyeLower0"]);let Y=this.getAdjustedIrisCoords(m,N,"left"),ee=this.getAdjustedIrisCoords(m,j,"right");m=m.concat(Y).concat(ee)}let g=this.transformRawCoords(m,o,u,c),y=o.confidence;if(o=s0(bb(g),1.5),o.confidence=y,n.face.detector.rotation&&n.face.mesh.enabled&&n.face.description.enabled&&Sr.flags.IS_BROWSER){let[x,b]=o.landmarks.length>=l0.count?l0.symmetryLine:w$.symmetryLine;u=vb(o.landmarks[x],o.landmarks[b]);let v=Tu({startPoint:o.startPoint,endPoint:o.endPoint}),w=[v[0]/t.shape[2],v[1]/t.shape[1]],I=Ye.rotateWithOffset(t.toFloat(),u,0,w);c=i0(-u,v),l=Nu({startPoint:o.startPoint,endPoint:o.endPoint},I,[this.meshSize,this.meshSize]).div(255)}let A={mesh:g,box:o,faceConfidence:p,boxConfidence:o.confidence,image:l};return this.storedBoxes[i]={...a0(o),confidence:o.confidence,faceConfidence:p},A}));return n.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(o=>o.confidence>n.face.detector.minConfidence)),this.detectedFaces=a.length,a}};var Zt=[null,null,null],Tb;async function k$(e,t){let n=await Tb.predict(e,t),r=[],s=0;for(let a of n||[]){if(!a||a.isDisposedInternal)continue;let o=a.mesh.map(c=>[c[0]/(e.shape[2]||0),c[1]/(e.shape[1]||0),c[2]/Tb.meshSize]),i={};if(a.mesh&&a.mesh.length>0)for(let c of Object.keys(Bs))i[c]=Bs[c].map(d=>a.mesh[d]);let l=a.box?[Math.trunc(Math.max(0,a.box.startPoint[0])),Math.trunc(Math.max(0,a.box.startPoint[1])),Math.trunc(Math.min(e.shape[2]||0,a.box.endPoint[0])-Math.max(0,a.box.startPoint[0])),Math.trunc(Math.min(e.shape[1]||0,a.box.endPoint[1])-Math.max(0,a.box.startPoint[1]))]:[0,0,0,0],u=a.box?[a.box.startPoint[0]/(e.shape[2]||0),a.box.startPoint[1]/(e.shape[1]||0),(a.box.endPoint[0]-a.box.startPoint[0])/(e.shape[2]||0),(a.box.endPoint[1]-a.box.startPoint[1])/(e.shape[1]||0)]:[0,0,0,0];r.push({id:s++,score:Math.round(100*a.faceConfidence||100*a.boxConfidence||0)/100,boxScore:Math.round(100*a.boxConfidence)/100,faceScore:Math.round(100*a.faceConfidence)/100,box:l,boxRaw:u,mesh:a.mesh,meshRaw:o,annotations:i,image:a.image,tensor:a.image}),a.coords&&a.coords.dispose()}return r}async function Nb(e){return!Zt[0]&&e.face.enabled||!Zt[1]&&e.face.mesh.enabled||!Zt[2]&&e.face.iris.enabled?(Zt=await Promise.all([!Zt[0]&&e.face.enabled?v$(e):null,!Zt[1]&&e.face.mesh.enabled?Et($t(e.modelBasePath,e.face.mesh.modelPath),{fromTFHub:e.face.mesh.modelPath.includes("tfhub.dev")}):null,!Zt[2]&&e.face.iris.enabled?Et($t(e.modelBasePath,e.face.iris.modelPath),{fromTFHub:e.face.iris.modelPath.includes("tfhub.dev")}):null]),e.face.mesh.enabled&&(!Zt[1]||!Zt[1].modelUrl?me("load model failed:",e.face.mesh.modelPath):e.debug&&me("load model:",Zt[1].modelUrl)),e.face.iris.enabled&&(!Zt[2]||!Zt[2].modelUrl?me("load model failed:",e.face.iris.modelPath):e.debug&&me("load model:",Zt[2].modelUrl))):e.debug&&(Zt[0]&&me("cached model:",Zt[0].model.modelUrl),Zt[1]&&me("cached model:",Zt[1].modelUrl),Zt[2]&&me("cached model:",Zt[2].modelUrl)),Tb=new Sb(Zt[0],Zt[1],Zt[2]),Zt}var I$=vi,S$=wh;var Lve=["angry","disgust","fear","happy","sad","surprise","neutral"],xs,c0=[],T$=0,Cb=Number.MAX_SAFE_INTEGER,Eb=[.2989,.587,.114];async function $b(e){return xs?e.debug&&me("cached model:",xs.modelUrl):(xs=await Et($t(e.modelBasePath,e.face.emotion.modelPath)),!xs||!xs.modelUrl?me("load model failed:",e.face.emotion.modelPath):e.debug&&me("load model:",xs.modelUrl)),xs}async function _b(e,t,n,r){return xs?Cb<t.face.emotion.skipFrames&&t.skipFrame&&T$===r&&c0[n]&&c0[n].length>0?(Cb++,c0[n]):(Cb=0,new Promise(async s=>{let a=Ye.resizeBilinear(e,[xs.inputs[0].shape[2],xs.inputs[0].shape[1]],!1),[o,i,l]=ta(a,3,3);a.dispose();let u=fe(o,Eb[0]),c=fe(i,Eb[1]),d=fe(l,Eb[2]);o.dispose(),i.dispose(),l.dispose();let h=Z2([u,c,d]);u.dispose(),c.dispose(),d.dispose();let p=Ue(()=>h.sub(.5).mul(2));h.dispose();let f=[];if(t.face.emotion.enabled){let m=await xs.predict(p),g=m.dataSync();Ve(m);for(let y=0;y<g.length;y++)g[y]>t.face.emotion.minConfidence&&f.push({score:Math.min(.99,Math.trunc(100*g[y])/100),emotion:Lve[y]});f.sort((y,A)=>A.score-y.score)}p.dispose(),c0[n]=f,T$=r,s(f)})):null}var bs,d0=[],N$=0,Rb=Number.MAX_SAFE_INTEGER;async function Db(e){let t=$t(e.modelBasePath,e.face.description.modelPath);return bs?e.debug&&me("cached model:",t):(bs=await Et(t),bs?e.debug&&me("load model:",t):me("load model failed:",e.face.description.modelPath)),bs}function Fb(e,t,n=2){if(!e||!t||(e==null?void 0:e.length)===0||(t==null?void 0:t.length)===0||(e==null?void 0:e.length)!==(t==null?void 0:t.length))return 0;let r=5*e.map((a,o)=>Math.abs(e[o]-t[o])**n).reduce((a,o)=>a+o,0)**(1/n);return Math.max(0,100-r)/100}function C$(e,t,n=0){let r={similarity:0,name:"",source:"",embedding:[]};if(!e||!t||!Array.isArray(e)||!Array.isArray(t))return r;for(let s of t)if(s.embedding&&s.name){let a=Fb(e,s.embedding);a>n&&a>r.similarity&&(r={...s,similarity:a})}return r}function Mb(e){return Ue(()=>{let n=e.image||e.tensor||e;if(!(n instanceof Tt))return null;let r=[[.05,.15,.85,.85]];return bs.inputs[0].shape?(n.shape.length===3?Ye.cropAndResize(ea(n,0),r,[0],[bs.inputs[0].shape[2],bs.inputs[0].shape[1]]):Ye.cropAndResize(n,r,[0],[bs.inputs[0].shape[2],bs.inputs[0].shape[1]])).mul(255):null})}async function Ob(e,t,n,r){var s,a;return bs?Rb<t.face.description.skipFrames&&t.skipFrame&&N$===r&&((s=d0[n])==null?void 0:s.age)&&((a=d0[n])==null?void 0:a.age)>0?(Rb++,d0[n]):(Rb=0,new Promise(async o=>{let i=Mb(e),l,u={age:0,gender:"unknown",genderScore:0,descriptor:[]};t.face.description.enabled&&(l=await bs.predict(i)),Ve(i),l&&(Ue(()=>{let c=l.find(m=>m.shape[1]===1).dataSync(),d=Math.trunc(200*Math.abs(c[0]-.5))/100;d>t.face.description.minConfidence&&(u.gender=c[0]<=.5?"female":"male",u.genderScore=Math.min(.99,d));let h=l.find(m=>m.shape[1]===100).argMax(1).dataSync()[0],p=l.find(m=>m.shape[1]===100).dataSync();u.age=Math.round(p[h-1]>p[h+1]?10*h-100*p[h-1]:10*h+100*p[h+1])/10;let f=l.find(m=>m.shape[1]===1024);u.descriptor=[...f.dataSync()]}),l.forEach(c=>Ve(c))),d0[n]=u,N$=r,o(u)})):null}var Bve=e=>{let t=(d,h)=>Math.atan2(d[1]-h[1],d[0]-h[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let n=[0,-.1],r=1,s=e.mesh[33][2]>e.mesh[263][2],a=s?e.mesh[473]:e.mesh[468],o=s?[(e.mesh[133][0]+e.mesh[33][0])/2,(e.mesh[133][1]+e.mesh[33][1])/2]:[(e.mesh[263][0]+e.mesh[362][0])/2,(e.mesh[263][1]+e.mesh[362][1])/2],i=s?[e.mesh[133][0]-e.mesh[33][0],e.mesh[23][1]-e.mesh[27][1]]:[e.mesh[263][0]-e.mesh[362][0],e.mesh[253][1]-e.mesh[257][1]],l=[(o[0]-a[0])/i[0]-n[0],r*(a[1]-o[1])/i[1]-n[1]],u=Math.sqrt(l[0]**2+l[1]**2);return u=Math.min(u,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],l)+Math.PI/2)%Math.PI,strength:u}},Wve=(e,t)=>{let n=g=>{let y=Math.sqrt(g[0]*g[0]+g[1]*g[1]+g[2]*g[2]);return g[0]/=y,g[1]/=y,g[2]/=y,g},r=(g,y)=>{let A=g[0]-y[0],x=g[1]-y[1],b=g[2]-y[2];return[A,x,b]},s=(g,y)=>{let A=g[1]*y[2]-g[2]*y[1],x=g[2]*y[0]-g[0]*y[2],b=g[0]*y[1]-g[1]*y[0];return[A,x,b]},a=g=>{let[y,A,x,b,v,w,I,T,C]=g,M,$,R;return b<1?b>-1?(R=Math.asin(b),$=Math.atan2(-I,y),M=Math.atan2(-w,v)):(R=-Math.PI/2,$=-Math.atan2(T,C),M=0):(R=Math.PI/2,$=Math.atan2(T,C),M=0),{pitch:2*-M,yaw:2*-$,roll:2*-R}},o=g=>{let y=(x,b,v,w)=>Math.atan2(w-b,v-x);return{pitch:y(g[10][1],g[10][2],g[152][1],g[152][2]),yaw:y(g[33][0],g[33][2],g[263][0],g[263][2]),roll:y(g[33][0],g[33][1],g[263][0],g[263][1])}},i=e.meshRaw;if(!i||i.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 l=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,u=[i[10],i[152],i[234],i[454]].map(g=>[g[0]*t[0]/l,g[1]*t[1]/l,g[2]]),c=n(r(u[1],u[0])),d=n(r(u[3],u[2])),h=n(s(d,c));d=s(c,h);let p=[d[0],d[1],d[2],c[0],c[1],c[2],h[0],h[1],h[2]],f=a(p),m=i.length===478?Bve(e):{bearing:0,strength:0};return{angle:f,matrix:p,gaze:m}},Pb=async(e,t)=>{var c,d,h,p,f,m;let n,r,s,a,o,i,l=[];e.state="run:face",n=at();let u=await k$(t,e.config);if(e.performance.face=Math.trunc(at()-n),!t.shape||t.shape.length!==4)return[];if(!u)return[];for(let g=0;g<u.length;g++){if(e.analyze("Get Face"),!u[g].image||u[g].image.isDisposedInternal){me("Face object is disposed:",u[g].image);continue}let y=Wve(u[g],[t.shape[2],t.shape[1]]);e.analyze("Start Emotion:"),e.config.async?a=e.config.face.emotion.enabled?_b(u[g].image||ts([]),e.config,g,u.length):{}:(e.state="run:emotion",n=at(),a=e.config.face.emotion.enabled?await _b(u[g].image||ts([]),e.config,g,u.length):{},e.performance.emotion=Math.trunc(at()-n)),e.analyze("End Emotion:"),e.analyze("Start Description:"),e.config.async?i=e.config.face.description.enabled?Ob(u[g].image||ts([]),e.config,g,u.length):[]:(e.state="run:description",n=at(),i=e.config.face.description.enabled?await Ob(u[g].image||ts([]),e.config,g,u.length):[],e.performance.embedding=Math.trunc(at()-n)),e.analyze("End Description:"),e.config.async&&([r,s,a,o,i]=await Promise.all([r,s,a,o,i])),e.analyze("Finish Face:"),!e.config.face.iris.enabled&&((d=(c=u[g])==null?void 0:c.annotations)==null?void 0:d.leftEyeIris)&&((p=(h=u[g])==null?void 0:h.annotations)==null?void 0:p.rightEyeIris)&&(delete u[g].annotations.leftEyeIris,delete u[g].annotations.rightEyeIris);let A=((f=u[g].annotations)==null?void 0:f.leftEyeIris)&&((m=u[g].annotations)==null?void 0:m.rightEyeIris)?Math.max(Math.abs(u[g].annotations.leftEyeIris[3][0]-u[g].annotations.leftEyeIris[1][0]),Math.abs(u[g].annotations.rightEyeIris[4][1]-u[g].annotations.rightEyeIris[2][1]))/t.shape[2]:0;l.push({...u[g],id:g,age:i.age,gender:i.gender,genderScore:i.genderScore,embedding:i.descriptor,emotion:a,iris:A!==0?Math.trunc(500/A/11.7)/100:0,rotation:y,tensor:e.config.face.detector.return?Zn(u[g].image):null}),Ve(u[g].image),u[g].image&&delete u[g].image,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),l};var kh=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],E$=kh.length,Ih=kh.reduce((e,t,n)=>(e[t]=n,e),{}),Vve=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],Uve=Vve.map(([e,t])=>[Ih[e],Ih[t]]),$$=[["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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Ye.nonMaxSuppressionAsync(l,o,n.hand.maxDetected,n.hand.iouThreshold,n.hand.minConfidence),c=u.arraySync();a.dispose(),u.dispose();let d=[];for(let h of c)if(o[h]>=n.hand.minConfidence){let p=Ze(l,[h,0],[1,-1]),f=Ze(s,[h,5],[1,14]),m=Ue(()=>this.normalizeLandmarks(f,h).reshape([-1,2]));f.dispose(),d.push({box:p,palmLandmarks:m,confidence:o[h]})}return s.dispose(),l.dispose(),d}async estimateHandBounds(t,n){let r=t.shape[1],s=t.shape[2],a=Ue(()=>t.resizeBilinear([this.inputSize,this.inputSize]).div(127.5).sub(1)),o=await this.getBoxes(a,n);a.dispose();let i=[];if(!o||o.length===0)return i;for(let l of o){let u=l.box.dataSync(),c=u.slice(0,2),d=u.slice(2,4),h=l.palmLandmarks.arraySync();l.box.dispose(),l.palmLandmarks.dispose(),i.push(z$({startPoint:c,endPoint:d,palmLandmarks:h,confidence:l.confidence},[s/this.inputSize,r/this.inputSize]))}return i}};function Zve(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function B$(e,t){let n=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return Zve(n)}var W$=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function ro(e,t){let n=0;for(let r=0;r<e.length;r++)n+=e[r]*t[r];return n}function Yve(e,t){let n=[];for(let r=0;r<e.length;r++)n.push(e[r][t]);return n}function V$(e,t){let n=[],r=e.length;for(let s=0;s<r;s++){n.push([]);for(let a=0;a<r;a++)n[s].push(ro(e[s],Yve(t,a)))}return n}function jb(e,t){let n=Math.cos(e),r=Math.sin(e),s=[[n,-r,0],[r,n,0],[0,0,1]],a=W$(t[0],t[1]),o=V$(a,s),i=W$(-t[0],-t[1]);return V$(o,i)}function U$(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],n=[e[0][2],e[1][2]],r=[-ro(t[0],n),-ro(t[1],n)];return[t[0].concat(r[0]),t[1].concat(r[1]),[0,0,1]]}function qb(e,t){return[ro(e,t[0]),ro(e,t[1])]}var Jve=5,H$=1.65,G$=[0,5,9,13,17,1,2],Qve=0,ewe=2,Kb=class{constructor(t,n){var r;this.handDetector=t,this.handPoseModel=n,this.inputSize=(r=this.handPoseModel)==null?void 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r=!1,s;(this.skipped===0||this.skipped>n.hand.skipFrames||!n.hand.landmarks||!n.skipFrame)&&(s=await this.handDetector.estimateHandBounds(t,n),this.skipped=0),n.skipFrame&&this.skipped++,s&&s.length>0&&(s.length!==this.detectedHands&&this.detectedHands!==n.hand.maxDetected||!n.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...s],this.storedBoxes.length>0&&(r=!0));let a=[];for(let o=0;o<this.storedBoxes.length;o++){let i=this.storedBoxes[o];if(!!i)if(n.hand.landmarks){let l=n.hand.rotation?B$(i.palmLandmarks[Qve],i.palmLandmarks[ewe]):0,u=Sh(i),c=[u[0]/t.shape[2],u[1]/t.shape[1]],d=n.hand.rotation&&Sr.flags.IS_BROWSER?Ye.rotateWithOffset(t,l,0,c):t.clone(),h=jb(-l,u),p=r?this.getBoxForPalmLandmarks(i.palmLandmarks,h):i,f=P$(p,d,[this.inputSize,this.inputSize]),m=f.div(255);f.dispose(),d.dispose();let[g,y]=await this.handPoseModel.predict(m);m.dispose();let A=g.dataSync()[0];if(g.dispose(),A>=n.hand.minConfidence){let x=ue(y,[-1,3]),b=x.arraySync();y.dispose(),x.dispose();let v=this.transformRawCoords(b,p,l,h),w=this.getBoxForHandLandmarks(v);this.storedBoxes[o]={...w,confidence:A};let I={landmarks:v,confidence:A,box:{topLeft:w.startPoint,bottomRight:w.endPoint}};a.push(I)}else this.storedBoxes[o]=null;y.dispose()}else{let l=f0(m0(i),H$),u={confidence:i.confidence,box:{topLeft:l.startPoint,bottomRight:l.endPoint}};a.push(u)}}return this.storedBoxes=this.storedBoxes.filter(o=>o!==null),this.detectedHands=a.length,a}};var j$={thumb:[1,2,3,4],indexFinger:[5,6,7,8],middleFinger:[9,10,11,12],ringFinger:[13,14,15,16],pinky:[17,18,19,20],palmBase:[0]},so,ao,q$;async function Xb(e,t){let n=await q$.estimateHands(e,t);if(!n)return[];let r=[];for(let s=0;s<n.length;s++){let a={};if(n[s].landmarks)for(let u of Object.keys(j$))a[u]=j$[u].map(c=>n[s].landmarks[c]);let o=n[s].landmarks,i=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],l=[0,0,0,0];if(o&&o.length>0){for(let u of 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g=0;g<o.length/u;g++)i.push({id:g,part:l[g],position:[Math.trunc(n.width*o[u*g+0]/255),Math.trunc(n.height*o[u*g+1]/255),Math.trunc(o[u*g+2])+0],positionRaw:[o[u*g+0]/255,o[u*g+1]/255,o[u*g+2]+0],score:(100-Math.trunc(100/(1+Math.exp(o[u*g+3]))))/100,presence:(100-Math.trunc(100/(1+Math.exp(o[u*g+4]))))/100});let c=i.map(g=>g.position[0]),d=i.map(g=>g.position[1]),h=[Math.min(...c),Math.min(...d),Math.max(...c)-Math.min(...c),Math.max(...d)-Math.min(...c)],p=[0,0,0,0],f=i.reduce((g,y)=>y.score>g?y.score:g,0);return[{id:0,score:f,box:h,boxRaw:p,keypoints:i}]}var rr,Ws=[],Jb=[0,0,0,0],Qb=[0,0,0,0],y0=0,e3=Number.MAX_SAFE_INTEGER,twe=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","pelvis","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"];async function Z$(e){return rr?e.debug&&me("cached model:",rr.modelUrl):(rr=await Et($t(e.modelBasePath,e.body.modelPath)),!rr||!rr.modelUrl?me("load model 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d=0;d<c.length;d++){let[h,p,f]=nwe(c[d],t.body.minConfidence);y0>t.body.minConfidence&&Ws.push({score:Math.round(100*f)/100,part:twe[d],positionRaw:[h/rr.inputs[0].shape[2],p/rr.inputs[0].shape[1]],position:[Math.round(e.shape[2]*h/rr.inputs[0].shape[2]),Math.round(e.shape[1]*p/rr.inputs[0].shape[1])]})}c.forEach(d=>Ve(d))}y0=Ws.reduce((u,c)=>c.score>u?c.score:u,0);let a=Ws.map(u=>u.position[0]),o=Ws.map(u=>u.position[1]);Jb=[Math.min(...a),Math.min(...o),Math.max(...a)-Math.min(...a),Math.max(...o)-Math.min(...o)];let i=Ws.map(u=>u.positionRaw[0]),l=Ws.map(u=>u.positionRaw[1]);Qb=[Math.min(...i),Math.min(...l),Math.max(...i)-Math.min(...i),Math.max(...l)-Math.min(...l)],n([{id:0,score:y0,box:Jb,boxRaw:Qb,keypoints:Ws}])}))}var vs,Vs=[],n3=[0,0,0,0],r3=[0,0,0,0],_u=0,s3=Number.MAX_SAFE_INTEGER,rwe=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"];async function a3(e){return vs?e.debug&&me("cached model:",vs.modelUrl):(vs=await Et($t(e.modelBasePath,e.body.modelPath)),!vs||!vs.modelUrl?me("load model failed:",e.body.modelPath):e.debug&&me("load model:",vs.modelUrl)),vs}async function o3(e,t){return s3<t.body.skipFrames&&t.skipFrame&&Object.keys(Vs).length>0?(s3++,[{id:0,score:_u,box:n3,boxRaw:r3,keypoints:Vs}]):(s3=0,new Promise(async n=>{let r=Ue(()=>{if(!vs.inputs[0].shape)return null;let u=Ye.resizeBilinear(e,[vs.inputs[0].shape[2],vs.inputs[0].shape[1]],!1);return Pt(u,"int32")}),s;if(t.body.enabled&&(s=await vs.predict(r)),r.dispose(),s){Vs.length=0;let u=s.arraySync();Ve(s);let c=u[0][0];for(let d=0;d<c.length;d++)_u=c[d][2],_u>t.body.minConfidence&&Vs.push({score:Math.round(100*_u)/100,part:rwe[d],positionRaw:[c[d][1],c[d][0]],position:[Math.round((e.shape[2]||0)*c[d][1]),Math.round((e.shape[1]||0)*c[d][0])]})}_u=Vs.reduce((u,c)=>c.score>u?c.score:u,0);let a=Vs.map(u=>u.position[0]),o=Vs.map(u=>u.position[1]);n3=[Math.min(...a),Math.min(...o),Math.max(...a)-Math.min(...a),Math.max(...o)-Math.min(...o)];let i=Vs.map(u=>u.positionRaw[0]),l=Vs.map(u=>u.positionRaw[1]);r3=[Math.min(...i),Math.min(...l),Math.max(...i)-Math.min(...i),Math.max(...l)-Math.min(...l)],n([{id:0,score:_u,box:n3,boxRaw:r3,keypoints:Vs}])}))}var Ru=[{class:1,label:"person"},{class:2,label:"bicycle"},{class:3,label:"car"},{class:4,label:"motorcycle"},{class:5,label:"airplane"},{class:6,label:"bus"},{class:7,label:"train"},{class:8,label:"truck"},{class:9,label:"boat"},{class:10,label:"traffic light"},{class:11,label:"fire hydrant"},{class:12,label:"stop sign"},{class:13,label:"parking meter"},{class:14,label:"bench"},{class:15,label:"bird"},{class:16,label:"cat"},{class:17,label:"dog"},{class:18,label:"horse"},{class:19,label:"sheep"},{class:20,label:"cow"},{class:21,label:"elephant"},{class:22,label:"bear"},{class:23,label:"zebra"},{class:24,label:"giraffe"},{class:25,label:"backpack"},{class:26,label:"umbrella"},{class:27,label:"handbag"},{class:28,label:"tie"},{class:29,label:"suitcase"},{class:30,label:"frisbee"},{class:31,label:"skis"},{class:32,label:"snowboard"},{class:33,label:"sports ball"},{class:34,label:"kite"},{class:35,label:"baseball bat"},{class:36,label:"baseball glove"},{class:37,label:"skateboard"},{class:38,label:"surfboard"},{class:39,label:"tennis racket"},{class:40,label:"bottle"},{class:41,label:"wine glass"},{class:42,label:"cup"},{class:43,label:"fork"},{class:44,label:"knife"},{class:45,label:"spoon"},{class:46,label:"bowl"},{class:47,label:"banana"},{class:48,label:"apple"},{class:49,label:"sandwich"},{class:50,label:"orange"},{class:51,label:"broccoli"},{class:52,label:"carrot"},{class:53,label:"hot dog"},{class:54,label:"pizza"},{class:55,label:"donut"},{class:56,label:"cake"},{class:57,label:"chair"},{class:58,label:"couch"},{class:59,label:"potted plant"},{class:60,label:"bed"},{class:61,label:"dining table"},{class:62,label:"toilet"},{class:63,label:"tv"},{class:64,label:"laptop"},{class:65,label:"mouse"},{class:66,label:"remote"},{class:67,label:"keyboard"},{class:68,label:"cell phone"},{class:69,label:"microwave"},{class:70,label:"oven"},{class:71,label:"toaster"},{class:72,label:"sink"},{class:73,label:"refrigerator"},{class:74,label:"book"},{class:75,label:"clock"},{class:76,label:"vase"},{class:77,label:"scissors"},{class:78,label:"teddy bear"},{class:79,label:"hair drier"},{class:80,label:"toothbrush"}];var Ar,i3=[],l3=Number.MAX_SAFE_INTEGER,A0=2.5;async function u3(e){if(Ar)e.debug&&me("cached model:",Ar.modelUrl);else{Ar=await Et($t(e.modelBasePath,e.object.modelPath));let t=Object.values(Ar.modelSignature.inputs);if(Ar.inputSize=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):null,!Ar.inputSize)throw new Error(`Human: Cannot determine model inputSize: ${e.object.modelPath}`);!Ar||!Ar.modelUrl?me("load model failed:",e.object.modelPath):e.debug&&me("load model:",Ar.modelUrl)}return Ar}async function swe(e,t,n,r){let s=0,a=[];for(let u of[1,2,4])Ue(()=>{var g,y;let c=u*13,d=(g=e.find(A=>A.shape[1]===c**2&&A.shape[2]===Ru.length))==null?void 0:g.squeeze(),h=(y=e.find(A=>A.shape[1]===c**2&&A.shape[2]<Ru.length))==null?void 0:y.squeeze(),f=h.reshape([-1,4,h.shape[1]/4]).argMax(2).arraySync(),m=d.arraySync();for(let A=0;A<d.shape[0];A++)for(let x=0;x<d.shape[1];x++){let b=m[A][x];if(b>r.object.minConfidence&&x!==61){let 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s=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,a=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0;if(!s||!a)return{tensor:null,canvas:Oe};let o=s,i=a;if(o>x0&&(o=x0,i=o*a/s),i>x0&&(i=x0,o=i*s/a),t.filter.width>0?o=t.filter.width:t.filter.height>0&&(o=s*(t.filter.height/a)),t.filter.height>0?i=t.filter.height:t.filter.width>0&&(i=a*(t.filter.width/s)),!o||!i)throw new Error("Human: Input cannot determine dimension");(!Oe||(Oe==null?void 0:Oe.width)!==o||(Oe==null?void 0:Oe.height)!==i)&&(Oe=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(o,i):document.createElement("canvas"),(Oe==null?void 0:Oe.width)!==o&&(Oe.width=o),(Oe==null?void 0:Oe.height)!==i&&(Oe.height=i));let l=Oe.getContext("2d");if(e instanceof ImageData?l.putImageData(e,0,0):t.filter.flip&&typeof l.translate!="undefined"?(l.translate(s,0),l.scale(-1,1),l.drawImage(e,0,0,s,a,0,0,Oe==null?void 0:Oe.width,Oe==null?void 0:Oe.height),l.setTransform(1,0,0,1,0,0)):l.drawImage(e,0,0,s,a,0,0,Oe==null?void 0:Oe.width,Oe==null?void 0:Oe.height),t.filter.enabled){if((!rn||!Bt||Oe.width!==Bt.width||(Oe==null?void 0:Oe.height)!==(Bt==null?void 0:Bt.height))&&(Bt=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(Oe==null?void 0:Oe.width,Oe==null?void 0:Oe.height):document.createElement("canvas"),(Bt==null?void 0:Bt.width)!==(Oe==null?void 0:Oe.width)&&(Bt.width=Oe==null?void 0:Oe.width),(Bt==null?void 0:Bt.height)!==(Oe==null?void 0:Oe.height)&&(Bt.height=Oe==null?void 0:Oe.height),rn=Sr.flags.IS_BROWSER?new t_({canvas:Bt}):null),!rn)return{tensor:null,canvas:Oe};rn.reset(),rn.addFilter("brightness",t.filter.brightness),t.filter.contrast!==0&&rn.addFilter("contrast",t.filter.contrast),t.filter.sharpness!==0&&rn.addFilter("sharpen",t.filter.sharpness),t.filter.blur!==0&&rn.addFilter("blur",t.filter.blur),t.filter.saturation!==0&&rn.addFilter("saturation",t.filter.saturation),t.filter.hue!==0&&rn.addFilter("hue",t.filter.hue),t.filter.negative&&rn.addFilter("negative"),t.filter.sepia&&rn.addFilter("sepia"),t.filter.vintage&&rn.addFilter("brownie"),t.filter.sepia&&rn.addFilter("sepia"),t.filter.kodachrome&&rn.addFilter("kodachrome"),t.filter.technicolor&&rn.addFilter("technicolor"),t.filter.polaroid&&rn.addFilter("polaroid"),t.filter.pixelate!==0&&rn.addFilter("pixelate",t.filter.pixelate),rn.apply(Oe)}else Bt=Oe,rn&&(rn=null);let u;if(Bt.data){let c=[Bt.height,Bt.width,3];u=mp(Bt.data,c,"int32")}else if(Bt instanceof ImageData)u=Hr?Hr.fromPixels(Bt):null;else if(t.backend==="webgl"||t.backend==="humangl"){let c=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(o,i):document.createElement("canvas");c.width=o,c.height=i;let d=c.getContext("2d");d==null||d.drawImage(Bt,0,0),u=Hr?Hr.fromPixels(c):null}else{let c=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(o,i):document.createElement("canvas");c.width=o,c.height=i;let d=c.getContext("2d");d==null||d.drawImage(Bt,0,0);let h=d==null?void 0:d.getImageData(0,0,o,i);u=Hr?Hr.fromPixels(h):null}if(u){let c=u.toFloat();n=c.expandDims(0),u.dispose(),c.dispose()}}let r=t.filter.return?Bt:null;return{tensor:n,canvas:r}}var y3={};e2(y3,{all:()=>uwe,body:()=>s_,canvas:()=>lwe,face:()=>r_,gesture:()=>n_,hand:()=>a_,object:()=>o_,options:()=>oo,person:()=>iwe});var oo={color:"rgba(173, 216, 230, 0.6)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",font:'small-caps 14px "Segoe UI"',lineHeight:24,lineWidth:6,pointSize:2,roundRect:28,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawPolygons:!0,drawGaze:!0,fillPolygons:!1,useDepth:!0,useCurves:!1,bufferedOutput:!0},b0=e=>Math.round(e*180/Math.PI);function m3(e,t,n,r=0,s){e.fillStyle=s.useDepth&&r?`rgba(${127.5+2*r}, ${127.5-2*r}, 255, 0.3)`:s.color,e.beginPath(),e.arc(t,n,s.pointSize,0,2*Math.PI),e.fill()}function Th(e,t,n,r,s,a){if(e.beginPath(),a.useCurves){let o=(t+t+r)/2,i=(n+n+s)/2;e.ellipse(o,i,r/2,s/2,0,0,2*Math.PI)}else e.lineWidth=a.lineWidth,e.moveTo(t+a.roundRect,n),e.lineTo(t+r-a.roundRect,n),e.quadraticCurveTo(t+r,n,t+r,n+a.roundRect),e.lineTo(t+r,n+s-a.roundRect),e.quadraticCurveTo(t+r,n+s,t+r-a.roundRect,n+s),e.lineTo(t+a.roundRect,n+s),e.quadraticCurveTo(t,n+s,t,n+s-a.roundRect),e.lineTo(t,n+a.roundRect),e.quadraticCurveTo(t,n,t+a.roundRect,n),e.closePath();e.stroke()}function g3(e,t=[],n){if(!(t===void 0||t.length===0)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let r of t){let s=r[2]||0;e.strokeStyle=n.useDepth&&s?`rgba(${127.5+2*s}, ${127.5-2*s}, 255, 0.3)`:n.color,e.fillStyle=n.useDepth&&s?`rgba(${127.5+2*s}, ${127.5-2*s}, 255, 0.3)`:n.color,e.lineTo(r[0],Math.round(r[1]))}e.stroke(),n.fillPolygons&&(e.closePath(),e.fill())}}function Nh(e,t=[],n){if(!(t===void 0||t.length===0)){if(!n.useCurves||t.length<=2){g3(e,t,n);return}e.moveTo(t[0][0],t[0][1]);for(let r=0;r<t.length-2;r++){let s=(t[r][0]+t[r+1][0])/2,a=(t[r][1]+t[r+1][1])/2;e.quadraticCurveTo(t[r][0],t[r][1],s,a)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),n.fillPolygons&&(e.closePath(),e.fill())}}async function n_(e,t,n){let r=ir(oo,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return;let s=e.getContext("2d");if(!s)return;s.font=r.font,s.fillStyle=r.color;let a=1;for(let o=0;o<t.length;o++){let i=[],l=[];if([i,l]=Object.entries(t[o]),l.length>1&&l[1].length>0){let u=i[1]>0?`#${i[1]}`:"",c=`${i[0]} ${u}: ${l[1]}`;r.shadowColor&&r.shadowColor!==""&&(s.fillStyle=r.shadowColor,s.fillText(c,8,2+a*r.lineHeight)),s.fillStyle=r.labelColor,s.fillText(c,6,0+a*r.lineHeight),a+=1}}}async function r_(e,t,n){var a,o,i,l;let r=ir(oo,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return;let s=e.getContext("2d");if(!!s)for(let u of t){s.font=r.font,s.strokeStyle=r.color,s.fillStyle=r.color,r.drawBoxes&&Th(s,u.box[0],u.box[1],u.box[2],u.box[3],r);let c=[];if(c.push(`face: ${Math.trunc(100*u.score)}%`),u.genderScore&&c.push(`${u.gender||""} ${Math.trunc(100*u.genderScore)}%`),u.age&&c.push(`age: ${u.age||""}`),u.iris&&c.push(`distance: ${u.iris}`),u.emotion&&u.emotion.length>0){let d=u.emotion.map(h=>`${Math.trunc(100*h.score)}% ${h.emotion}`);d.length>3&&(d.length=3),c.push(d.join(" "))}u.rotation&&u.rotation.angle&&u.rotation.gaze&&(u.rotation.angle.roll&&c.push(`roll: ${b0(u.rotation.angle.roll)}\xB0 yaw:${b0(u.rotation.angle.yaw)}\xB0 pitch:${b0(u.rotation.angle.pitch)}\xB0`),u.rotation.gaze.bearing&&c.push(`gaze: ${b0(u.rotation.gaze.bearing)}\xB0`)),c.length===0&&c.push("face"),s.fillStyle=r.color;for(let d=c.length-1;d>=0;d--){let h=Math.max(u.box[0],0),p=d*r.lineHeight+u.box[1];r.shadowColor&&r.shadowColor!==""&&(s.fillStyle=r.shadowColor,s.fillText(c[d],h+5,p+16)),s.fillStyle=r.labelColor,s.fillText(c[d],h+4,p+15)}if(s.lineWidth=1,u.mesh&&u.mesh.length>0){if(r.drawPoints)for(let d of u.mesh)m3(s,d[0],d[1],d[2],r);if(r.drawPolygons){s.lineWidth=1;for(let d=0;d<vi.length/3;d++){let h=[vi[d*3+0],vi[d*3+1],vi[d*3+2]].map(p=>u.mesh[p]);g3(s,h,r)}if(u.annotations&&u.annotations.leftEyeIris){s.strokeStyle=r.useDepth?"rgba(255, 200, 255, 0.3)":r.color,s.beginPath();let d=Math.abs(u.annotations.leftEyeIris[3][0]-u.annotations.leftEyeIris[1][0])/2,h=Math.abs(u.annotations.leftEyeIris[4][1]-u.annotations.leftEyeIris[2][1])/2;s.ellipse(u.annotations.leftEyeIris[0][0],u.annotations.leftEyeIris[0][1],d,h,0,0,2*Math.PI),s.stroke(),r.fillPolygons&&(s.fillStyle=r.useDepth?"rgba(255, 255, 200, 0.3)":r.color,s.fill())}if(u.annotations&&u.annotations.rightEyeIris){s.strokeStyle=r.useDepth?"rgba(255, 200, 255, 0.3)":r.color,s.beginPath();let d=Math.abs(u.annotations.rightEyeIris[3][0]-u.annotations.rightEyeIris[1][0])/2,h=Math.abs(u.annotations.rightEyeIris[4][1]-u.annotations.rightEyeIris[2][1])/2;s.ellipse(u.annotations.rightEyeIris[0][0],u.annotations.rightEyeIris[0][1],d,h,0,0,2*Math.PI),s.stroke(),r.fillPolygons&&(s.fillStyle=r.useDepth?"rgba(255, 255, 200, 0.3)":r.color,s.fill())}if(r.drawGaze&&((o=(a=u.rotation)==null?void 0:a.gaze)==null?void 0:o.strength)&&((l=(i=u.rotation)==null?void 0:i.gaze)==null?void 0:l.bearing)&&u.annotations.leftEyeIris&&u.annotations.rightEyeIris&&u.annotations.leftEyeIris[0]&&u.annotations.rightEyeIris[0]){s.strokeStyle="pink",s.beginPath();let d=[u.annotations.leftEyeIris[0][0]+Math.sin(u.rotation.gaze.bearing)*u.rotation.gaze.strength*u.box[3],u.annotations.leftEyeIris[0][1]+Math.cos(u.rotation.gaze.bearing)*u.rotation.gaze.strength*u.box[2]];s.moveTo(u.annotations.leftEyeIris[0][0],u.annotations.leftEyeIris[0][1]),s.lineTo(d[0],d[1]);let h=[u.annotations.rightEyeIris[0][0]+Math.sin(u.rotation.gaze.bearing)*u.rotation.gaze.strength*u.box[3],u.annotations.rightEyeIris[0][1]+Math.cos(u.rotation.gaze.bearing)*u.rotation.gaze.strength*u.box[2]];s.moveTo(u.annotations.rightEyeIris[0][0],u.annotations.rightEyeIris[0][1]),s.lineTo(h[0],h[1]),s.stroke()}}}}}async function s_(e,t,n){var a;let r=ir(oo,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return;let s=e.getContext("2d");if(!!s){s.lineJoin="round";for(let o=0;o<t.length;o++){if(s.strokeStyle=r.color,s.fillStyle=r.color,s.lineWidth=r.lineWidth,s.font=r.font,r.drawBoxes&&t[o].box&&((a=t[o].box)==null?void 0:a.length)===4&&(Th(s,t[o].box[0],t[o].box[1],t[o].box[2],t[o].box[3],r),r.drawLabels&&(r.shadowColor&&r.shadowColor!==""&&(s.fillStyle=r.shadowColor,s.fillText(`body ${100*t[o].score}%`,t[o].box[0]+3,1+t[o].box[1]+r.lineHeight,t[o].box[2])),s.fillStyle=r.labelColor,s.fillText(`body ${100*t[o].score}%`,t[o].box[0]+2,0+t[o].box[1]+r.lineHeight,t[o].box[2]))),r.drawPoints)for(let i=0;i<t[o].keypoints.length;i++)s.fillStyle=r.useDepth&&t[o].keypoints[i].position[2]?`rgba(${127.5+2*(t[o].keypoints[i].position[2]||0)}, ${127.5-2*(t[o].keypoints[i].position[2]||0)}, 255, 0.5)`:r.color,m3(s,t[o].keypoints[i].position[0],t[o].keypoints[i].position[1],0,r);if(r.drawLabels&&(s.font=r.font,t[o].keypoints))for(let i of t[o].keypoints)s.fillStyle=r.useDepth&&i.position[2]?`rgba(${127.5+2*i.position[2]}, ${127.5-2*i.position[2]}, 255, 0.5)`:r.color,s.fillText(`${i.part} ${Math.trunc(100*i.score)}%`,i.position[0]+4,i.position[1]+4);if(r.drawPolygons&&t[o].keypoints){let i,l=[];l.length=0,i=t[o].keypoints.find(u=>u.part==="leftShoulder"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightShoulder"),i&&l.push([i.position[0],i.position[1]]),Nh(s,l,r),l.length=0,i=t[o].keypoints.find(u=>u.part==="rightShoulder"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightHip"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftHip"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftShoulder"),i&&l.push([i.position[0],i.position[1]]),l.length===4&&g3(s,l,r),l.length=0,i=t[o].keypoints.find(u=>u.part==="leftHip"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftKnee"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftAnkle"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftHeel"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftFoot"),i&&l.push([i.position[0],i.position[1]]),Nh(s,l,r),l.length=0,i=t[o].keypoints.find(u=>u.part==="rightHip"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightKnee"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightAnkle"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightHeel"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightFoot"),i&&l.push([i.position[0],i.position[1]]),Nh(s,l,r),l.length=0,i=t[o].keypoints.find(u=>u.part==="leftShoulder"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftElbow"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftWrist"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftPalm"),i&&l.push([i.position[0],i.position[1]]),Nh(s,l,r),l.length=0,i=t[o].keypoints.find(u=>u.part==="rightShoulder"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightElbow"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightWrist"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightPalm"),i&&l.push([i.position[0],i.position[1]]),Nh(s,l,r)}}}}async function a_(e,t,n){let r=ir(oo,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return;let s=e.getContext("2d");if(!!s){s.lineJoin="round",s.font=r.font;for(let a of t){if(r.drawBoxes&&(s.strokeStyle=r.color,s.fillStyle=r.color,Th(s,a.box[0],a.box[1],a.box[2],a.box[3],r),r.drawLabels&&(r.shadowColor&&r.shadowColor!==""&&(s.fillStyle=r.shadowColor,s.fillText("hand",a.box[0]+3,1+a.box[1]+r.lineHeight,a.box[2])),s.fillStyle=r.labelColor,s.fillText("hand",a.box[0]+2,0+a.box[1]+r.lineHeight,a.box[2])),s.stroke()),r.drawPoints&&a.keypoints&&a.keypoints.length>0)for(let o of a.keypoints)s.fillStyle=r.useDepth?`rgba(${127.5+2*o[2]}, ${127.5-2*o[2]}, 255, 0.5)`:r.color,m3(s,o[0],o[1],0,r);if(r.drawLabels){let o=(i,l)=>{s.fillStyle=r.useDepth?`rgba(${127.5+2*i[i.length-1][2]}, ${127.5-2*i[i.length-1][2]}, 255, 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n=e.getContext("2d");n==null||n.drawImage(e,0,0)}async function uwe(e,t,n){let r=at(),s=ir(oo,n);!t||!e||e instanceof HTMLCanvasElement&&(r_(e,t.face,s),s_(e,t.body,s),a_(e,t.hand,s),o_(e,t.object,s),n_(e,t.gesture,s),t.performance.draw=Math.trunc(at()-r))}function i_(e,t,n,r,s){var i,l,u,c,d,h,p,f,m,g,y,A,x,b,v,w;let a=0,o=[];for(let I of e){let T={id:a++,face:I,body:null,hands:{left:null,right:null},gestures:[],box:[0,0,0,0]};for(let F of t)I.box[0]>F.box[0]&&I.box[0]<F.box[0]+F.box[2]&&I.box[1]+I.box[3]>F.box[1]&&I.box[1]+I.box[3]<F.box[1]+F.box[3]&&(T.body=F);if(T.body)for(let F of n)F.box[0]+F.box[2]>T.body.box[0]&&F.box[0]+F.box[2]<T.body.box[0]+T.body.box[2]&&F.box[1]+F.box[3]>T.body.box[1]&&F.box[1]+F.box[3]<T.body.box[1]+T.body.box[3]&&T.hands&&(T.hands.left=F),F.box[0]<T.body.box[0]+T.body.box[2]&&F.box[0]>T.body.box[0]&&F.box[1]+F.box[3]>T.body.box[1]&&F.box[1]+F.box[3]<T.body.box[1]+T.body.box[3]&&T.hands&&(T.hands.right=F);for(let F of r)F.face!==void 0&&F.face===I.id?(i=T.gestures)==null||i.push(F):F.iris!==void 0&&F.iris===I.id?(l=T.gestures)==null||l.push(F):F.body!==void 0&&F.body===((u=T.body)==null?void 0:u.id)?(c=T.gestures)==null||c.push(F):F.hand!==void 0&&F.hand===((h=(d=T.hands)==null?void 0:d.left)==null?void 0:h.id)?(p=T.gestures)==null||p.push(F):F.hand!==void 0&&F.hand===((m=(f=T.hands)==null?void 0:f.right)==null?void 0:m.id)&&((g=T.gestures)==null||g.push(F));let C=[],M=[],$=F=>{F&&F.length===4&&(C.push(F[0],F[0]+F[2]),M.push(F[1],F[1]+F[3]))};$((y=T.face)==null?void 0:y.box),$((A=T.body)==null?void 0:A.box),$((b=(x=T.hands)==null?void 0:x.left)==null?void 0:b.box),$((w=(v=T.hands)==null?void 0:v.right)==null?void 0:w.box);let R=Math.min(...C),N=Math.min(...M);T.box=[R,N,Math.max(...C)-R,Math.max(...M)-N],s&&s.length===4&&(T.boxRaw=[T.box[0]/s[2],T.box[1]/s[1],T.box[2]/s[2],T.box[3]/s[1]]),o.push(T)}return o}var Be={face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0};function l_(e){var s,a,o,i,l,u,c,d,h,p,f,m,g,y,A,x,b,v,w,I,T;let t=Date.now()-e.timestamp,n=t<1e3?8-Math.log(t):1;if(Be.canvas=e.canvas,!Be.body||e.body.length!==Be.body.length)Be.body=JSON.parse(JSON.stringify(e.body));else for(let C=0;C<e.body.length;C++){let M=e.body[C].box.map((N,F)=>((n-1)*Be.body[C].box[F]+N)/n),$=e.body[C].boxRaw.map((N,F)=>((n-1)*Be.body[C].boxRaw[F]+N)/n),R=e.body[C].keypoints.map((N,F)=>({score:N.score,part:N.part,position:[Be.body[C].keypoints[F]?((n-1)*Be.body[C].keypoints[F].position[0]+N.position[0])/n:N.position[0],Be.body[C].keypoints[F]?((n-1)*Be.body[C].keypoints[F].position[1]+N.position[1])/n:N.position[1]],positionRaw:[Be.body[C].keypoints[F]?((n-1)*Be.body[C].keypoints[F].positionRaw[0]+N.positionRaw[0])/n:N.position[0],Be.body[C].keypoints[F]?((n-1)*Be.body[C].keypoints[F].positionRaw[1]+N.positionRaw[1])/n:N.position[1]]}));Be.body[C]={...e.body[C],box:M,boxRaw:$,keypoints:R}}if(!Be.hand||e.hand.length!==Be.hand.length)Be.hand=JSON.parse(JSON.stringify(e.hand));else for(let C=0;C<e.hand.length;C++){let 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2Q==`;var c_="2.0.0";var Du,Ch,Eh,ki,Ii,Fu,I0,$h,S0,T0,N0,C0,d_=class{constructor(t){Ir(this,Du,void 0);Ir(this,Ch,void 0);Ir(this,Eh,void 0);Ir(this,ki,void 0);Ir(this,Ii,void 0);Ir(this,Fu,void 0);this.analyze=(...t)=>{if(!Fn(this,Ch))return;let n=this.tf.engine().state.numTensors,r=Fn(this,Du);Qr(this,Du,n);let s=n-r;s!==0&&me(...t,s)};Ir(this,I0,t=>{if(!Fn(this,Eh))return null;if(!t)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(t instanceof Tt))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});Ir(this,$h,async(t=!1)=>{var n;if(this.config.backend&&this.config.backend.length>0&&t||this.tf.getBackend()!==this.config.backend){let r=at();if(this.state="backend",this.config.backend&&this.config.backend.length>0){if(typeof window=="undefined"&&typeof WorkerGlobalScope!="undefined"&&this.config.debug&&me("running inside web worker"),this.tf.ENV.flags.IS_BROWSER&&this.config.backend==="tensorflow"&&(this.config.backend="webgl"),this.tf.ENV.flags.IS_NODE&&(this.config.backend==="webgl"||this.config.backend==="humangl")&&(this.config.backend="tensorflow"),this.config.debug&&me("setting backend:",this.config.backend),this.config.backend==="wasm"){if(this.config.debug&&me("wasm path:",this.config.wasmPath),typeof((n=this.tf)==null?void 0:n.setWasmPaths)!="undefined")this.tf.setWasmPaths(this.config.wasmPath);else throw new Error("Human: WASM backend is not loaded");let s=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),a=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&me(`wasm execution: ${s?"SIMD":"no SIMD"} ${a?"multithreaded":"singlethreaded"}`),this.config.debug&&!s&&me("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&d$();try{await this.tf.setBackend(this.config.backend)}catch(s){me("error: cannot set backend:",this.config.backend,s)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"||this.tf.getBackend()==="humangl"){this.tf.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),this.tf.ENV.set("WEBGL_CPU_FORWARD",!0),this.tf.ENV.set("WEBGL_PACK_DEPTHWISECONV",!0),typeof this.config.deallocate!="undefined"&&this.config.deallocate&&(me("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",!0),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",0));let s=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&me(`gl version:${s.getParameter(s.VERSION)} renderer:${s.getParameter(s.RENDERER)}`)}await this.tf.ready(),this.performance.backend=Math.trunc(at()-r)}});this.next=t=>l_(t||this.result);Ir(this,S0,async t=>{if(this.config.cacheSensitivity===0)return!1;let n=32,r=t.resizeBilinear([Math.trunc(t.shape[1]/n),Math.trunc(t.shape[2]/n)]),s=r.dataSync(),a=0;for(let l=0;l<s.length/3;l++)a+=s[3*l+2];r.dispose();let o=100*(Math.max(a,Fn(this,Ii))/Math.min(a,Fn(this,Ii))-1);Qr(this,Ii,a);let i=o<Math.max(this.config.cacheSensitivity,Fn(this,Fu));return Qr(this,Fu,o>10*this.config.cacheSensitivity?0:o),i});Ir(this,T0,async()=>{let t=(s,a="application/octet-stream")=>fetch(`data:${a};base64,${s}`).then(o=>o.blob()),n,r;switch(this.config.warmup){case"face":n=await t(w0);break;case"full":n=await t(k0);break;default:n=null}if(n){let s=await createImageBitmap(n);r=await this.detect(s,this.config),s.close()}return r});Ir(this,N0,async()=>new Promise(t=>{let n,r=0;switch(this.config.warmup){case"face":r=256,n="data:image/jpeg;base64,"+w0;break;case"full":case"body":r=1200,n="data:image/jpeg;base64,"+k0;break;default:n=null}let s=new Image;s.onload=async()=>{let a=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(r,r):document.createElement("canvas");a.width=s.naturalWidth,a.height=s.naturalHeight;let o=a.getContext("2d");o==null||o.drawImage(s,0,0);let i=await this.detect(a,this.config);t(i)},n?s.src=n:t(null)}));Ir(this,C0,async()=>{let t=s=>Buffer.from(s,"base64"),n;if(this.config.warmup==="face"&&(n=t(w0)),(this.config.warmup==="body"||this.config.warmup==="full")&&(n=t(k0)),!n)return null;let r;if(typeof void 0!="undefined"){let s=(void 0).decodeJpeg(n),a=s.expandDims(0);this.tf.dispose(s),r=await this.detect(a,this.config),this.tf.dispose(a)}else this.config.debug&&me("Warmup tfjs-node not loaded");return r});this.config=ir(D3,t||{}),this.tf=bh,this.draw=y3,this.version=c_,this.state="idle",Qr(this,Du,0),Qr(this,Ch,!1),Qr(this,Eh,!1),Qr(this,ki,!0),Qr(this,Fu,0),this.performance={backend:0,load:0,image:0,frames:0,cached:0,changed:0,total:0,draw:0},this.models={face:null,posenet:null,blazepose:null,efficientpose:null,movenet:null,handpose:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null,centernet:null,faceres:null,segmentation:null},this.image=n=>wi(n,this.config),this.faceTriangulation=I$,this.faceUVMap=S$,this.sysinfo=F3(),Qr(this,Ii,1)}similarity(t,n){return Fb(t,n)}segmentation(t,n){return u_(t,n,this.config)}enhance(t){return Mb(t)}match(t,n,r=0){return C$(t,n,r)}async load(t){this.state="load";let n=at();t&&(this.config=ir(this.config,t)),Fn(this,ki)&&(this.config.debug&&me(`version: ${this.version}`),this.config.debug&&me(`tfjs version: ${this.tf.version_core}`),this.config.debug&&me("platform:",this.sysinfo.platform),this.config.debug&&me("agent:",this.sysinfo.agent),await Fn(this,$h).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&me("configuration:",this.config),this.config.debug&&me("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.emotion,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.efficientpose,this.models.movenet,this.models.nanodet,this.models.centernet,this.models.faceres,this.models.segmentation]=await Promise.all([this.models.face||(this.config.face.enabled?Nb(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?$b(this.config):null),this.models.handpose||(this.config.hand.enabled?Zb(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?Hb(this.config):null),this.models.blazepose||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?g0(this.config):null),this.models.efficientpose||(this.config.body.enabled&&this.config.body.modelPath.includes("efficientpose")?Z$(this.config):null),this.models.movenet||(this.config.body.enabled&&this.config.body.modelPath.includes("movenet")?a3(this.config):null),this.models.nanodet||(this.config.object.enabled&&this.config.object.modelPath.includes("nanodet")?u3(this.config):null),this.models.centernet||(this.config.object.enabled&&this.config.object.modelPath.includes("centernet")?p3(this.config):null),this.models.faceres||(this.config.face.enabled&&this.config.face.description.enabled?Db(this.config):null),this.models.segmentation||(this.config.segmentation.enabled?v0(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await Nb(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await $b(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await Zb(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await Hb(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await g0(this.config)),this.config.body.enabled&&!this.models.efficientpose&&this.config.body.modelPath.includes("efficientpose")&&(this.models.efficientpose=await g0(this.config)),this.config.body.enabled&&!this.models.movenet&&this.config.body.modelPath.includes("movenet")&&(this.models.movenet=await a3(this.config)),this.config.object.enabled&&!this.models.nanodet&&this.config.object.modelPath.includes("nanodet")&&(this.models.nanodet=await u3(this.config)),this.config.object.enabled&&!this.models.centernet&&this.config.object.modelPath.includes("centernet")&&(this.models.centernet=await p3(this.config)),this.config.face.enabled&&this.config.face.description.enabled&&!this.models.faceres&&(this.models.faceres=await Db(this.config)),this.config.segmentation.enabled&&!this.models.segmentation&&(this.models.segmentation=await v0(this.config))),Fn(this,ki)&&(this.config.debug&&me("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),Qr(this,ki,!1));let r=Math.trunc(at()-n);r>(this.performance.load||0)&&(this.performance.load=r)}async detect(t,n){return new Promise(async r=>{this.state="config";let s,a;this.config=ir(this.config,n),this.state="check";let o=Fn(this,I0).call(this,t);o&&(me(o,t),r({error:o}));let i=at();await Fn(this,$h).call(this),await this.load(),s=at();let l=wi(t,this.config);if(this.performance.image=Math.trunc(at()-s),this.analyze("Get Image:"),this.config.segmentation.enabled&&l&&l.tensor&&(this.analyze("Start Segmentation:"),this.state="run:segmentation",s=at(),await x3(l),a=Math.trunc(at()-s),a>0&&(this.performance.segmentation=a),l.canvas&&(l.tensor.dispose(),l=wi(l.canvas,this.config)),this.analyze("End Segmentation:")),!l||!l.tensor){me("could not convert input to tensor"),r({error:"could not convert input to tensor"});return}s=at(),this.config.skipFrame=await Fn(this,S0).call(this,l.tensor),this.performance.frames||(this.performance.frames=0),this.performance.cached||(this.performance.cached=0),this.performance.frames++,this.config.skipFrame&&this.performance.cached++,this.performance.changed=Math.trunc(at()-s),this.analyze("Check Changed:");let u,c,d,h;this.config.async?(u=this.config.face.enabled?Pb(this,l.tensor):[],this.performance.face&&delete this.performance.face):(this.state="run:face",s=at(),u=this.config.face.enabled?await Pb(this,l.tensor):[],a=Math.trunc(at()-s),a>0&&(this.performance.face=a)),this.analyze("Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?c=this.config.body.enabled?Ub(l.tensor,this.config):[]:this.config.body.modelPath.includes("blazepose")?c=this.config.body.enabled?Yb(l.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")?c=this.config.body.enabled?t3(l.tensor,this.config):[]:this.config.body.modelPath.includes("movenet")&&(c=this.config.body.enabled?o3(l.tensor,this.config):[]),this.performance.body&&delete this.performance.body):(this.state="run:body",s=at(),this.config.body.modelPath.includes("posenet")?c=this.config.body.enabled?await Ub(l.tensor,this.config):[]:this.config.body.modelPath.includes("blazepose")?c=this.config.body.enabled?await Yb(l.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")?c=this.config.body.enabled?await t3(l.tensor,this.config):[]:this.config.body.modelPath.includes("movenet")&&(c=this.config.body.enabled?await o3(l.tensor,this.config):[]),a=Math.trunc(at()-s),a>0&&(this.performance.body=a)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(d=this.config.hand.enabled?Xb(l.tensor,this.config):[],this.performance.hand&&delete this.performance.hand):(this.state="run:hand",s=at(),d=this.config.hand.enabled?await Xb(l.tensor,this.config):[],a=Math.trunc(at()-s),a>0&&(this.performance.hand=a)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.config.async?(this.config.object.modelPath.includes("nanodet")?h=this.config.object.enabled?c3(l.tensor,this.config):[]:this.config.object.modelPath.includes("centernet")&&(h=this.config.object.enabled?f3(l.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(this.state="run:object",s=at(),this.config.object.modelPath.includes("nanodet")?h=this.config.object.enabled?await c3(l.tensor,this.config):[]:this.config.object.modelPath.includes("centernet")&&(h=this.config.object.enabled?await f3(l.tensor,this.config):[]),a=Math.trunc(at()-s),a>0&&(this.performance.object=a)),this.analyze("End Object:"),this.config.async&&([u,c,d,h]=await Promise.all([u,c,d,h]));let p=[];this.config.gesture.enabled&&(s=at(),p=[...J$(u),...Y$(c),...e_(d),...Q$(u)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=Math.trunc(at()-s)),this.performance.total=Math.trunc(at()-i),this.state="idle",this.result={face:u,body:c,hand:d,gesture:p,object:h,performance:this.performance,canvas:l.canvas,timestamp:Date.now(),get persons(){var f;return i_(u,c,d,p,(f=l==null?void 0:l.tensor)==null?void 0:f.shape)}},Ve(l.tensor),r(this.result)})}async warmup(t){let n=at();if(t&&(this.config=ir(this.config,t)),!this.config.warmup||this.config.warmup==="none")return{error:"null"};let r;typeof createImageBitmap=="function"?r=await Fn(this,T0).call(this):typeof Image!="undefined"?r=await Fn(this,N0).call(this):r=await Fn(this,C0).call(this);let s=at();return this.config.debug&&me("Warmup",this.config.warmup,Math.round(s-n),"ms",r),r}};Du=new WeakMap,Ch=new WeakMap,Eh=new WeakMap,ki=new WeakMap,Ii=new WeakMap,Fu=new WeakMap,I0=new WeakMap,$h=new WeakMap,S0=new WeakMap,T0=new WeakMap,N0=new WeakMap,C0=new WeakMap;return dwe;})();
/**
 * @license
 * Copyright 2017 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2018 Google LLC
 *
 * Use of this source code is governed by an MIT-style
 * license that can be found in the LICENSE file or at
 * https://opensource.org/licenses/MIT.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2018 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 *
 * =============================================================================
 */
/**
 * @license
 * Copyright 2018 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2019 Google LLC
 *
 * Use of this source code is governed by an MIT-style
 * license that can be found in the LICENSE file or at
 * https://opensource.org/licenses/MIT.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2019 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 *
 * =============================================================================
 */
/**
 * @license
 * Copyright 2019 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2020 Google Inc. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2020 Google LLC
 *
 * Use of this source code is governed by an MIT-style
 * license that can be found in the LICENSE file or at
 * https://opensource.org/licenses/MIT.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2020 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2020 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the License);
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an AS IS BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2021 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2021 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * https://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/** @license See the LICENSE file. */